# Système de Pathfinding Hybride

## Vue d'Ensemble

Le système de pathfinding de Warfactory utilise une **architecture hybride à 3 algorithmes** pour optimiser performance et précision selon le contexte tactique. Ce n'est pas un simple A* : c'est un système adaptatif qui choisit automatiquement le bon algorithme selon la distance, le nombre d'unités, et les contraintes tactiques.

### Principes Fondamentaux

- **Hybride** : A*, HPA*, Flow Fields selon contexte
- **Poids Dynamiques** : Threat maps, cover, terrain, doctrine
- **Multi-Path** : Génération chemins alternatifs (flanking)
- **Tactique** : Cover-to-cover, évitement menaces, choix terrain
- **Performance** : Budget 4ms/frame (60fps), scaling linéaire

---

## Architecture Globale

### Les 3 Algorithmes

```cpp
enum PathfindingAlgorithm {
    ASTAR,           // Courte distance, précision
    HIERARCHICAL,    // Longue distance, rapide
    FLOW_FIELD       // Groupes massifs, 1 calcul pour N unités
};

PathfindingAlgorithm selectAlgorithm(Unit unit, Position goal) {
    float distance = calculateDistance(unit.pos, goal);
    int group_size = countUnitsWithSameGoal(unit, goal);

    // Groupe massif → Flow Field
    if (group_size >= 10) {
        return FLOW_FIELD;
    }

    // Longue distance → Hierarchical
    if (distance > 100.0f) {
        return HIERARCHICAL;
    }

    // Court + précis → A*
    return ASTAR;
}
```

### Règles de Décision

| Situation | Algorithme | Raison | Performance |
|-----------|------------|--------|-------------|
| 1 unité, < 100m | A* | Précision tactique | 1-2ms |
| 1 unité, > 100m | HPA* | Vitesse longue distance | 5-10ms |
| 10+ unités, même but | Flow Field | 1 calcul partagé | 15ms total |
| N unités, buts différents | A* × N ou HPA* × N | Chemins divergents | Variable |

---

## 1. A* - Pathfinding Précis

### Usage

**Quand** :
- Distance courte (< 100m)
- Unité solo ou petit groupe (< 10)
- Besoin précision tile-par-tile
- Mouvement tactique (cover-to-cover)

**Performance Target** :
- < 2ms pour 50m
- < 5ms pour 100m
- Budget : 25% d'un frame (4ms @ 60fps)

### Algorithme de Base

```cpp
class AStarPathfinder {
public:
    Path findPath(Position start, Position goal, PathConstraints constraints) {
        std::priority_queue<Node> open_set;
        std::unordered_set<Position> closed_set;

        Node start_node = {start, 0.0f, heuristic(start, goal)};
        open_set.push(start_node);

        while (!open_set.empty()) {
            Node current = open_set.top();
            open_set.pop();

            if (current.pos == goal) {
                return reconstructPath(current);
            }

            closed_set.insert(current.pos);

            // Explorer voisins
            for (auto& neighbor : getNeighbors(current.pos)) {
                if (closed_set.contains(neighbor)) continue;

                // ✅ COÛT AVEC POIDS DYNAMIQUES
                float g_cost = current.g_cost + calculateCost(current, neighbor, constraints);
                float h_cost = heuristic(neighbor, goal);
                float f_cost = g_cost + h_cost;

                open_set.push({neighbor, g_cost, f_cost});
            }
        }

        return Path(); // Pas de chemin trouvé
    }

private:
    float heuristic(Position a, Position b) {
        // Manhattan distance (grille 4-directionnelle)
        return abs(a.x - b.x) + abs(a.y - b.y);

        // Ou Euclidean (grille 8-directionnelle)
        // return sqrt(pow(a.x - b.x, 2) + pow(a.y - b.y, 2));
    }
};
```

### Poids Dynamiques (Weighted A*)

**Principe** : Coût ≠ distance pure, intègre facteurs tactiques

```cpp
float calculateCost(Node current, Node neighbor, PathConstraints constraints) {
    float base_cost = distance(current.pos, neighbor.pos); // 1.0 ou 1.41 (diagonal)

    // Poids tactiques
    float threat_penalty = getThreat(neighbor.pos) * constraints.threat_weight;
    float cover_bonus = hasCover(neighbor.pos) ? -constraints.cover_weight : 0.0f;
    float elevation_penalty = abs(neighbor.elevation - current.elevation) * constraints.elevation_weight;
    float terrain_penalty = getTerrainCost(neighbor.terrain, constraints.unit_type) * constraints.terrain_weight;
    float exposure_penalty = isExposed(neighbor.pos) ? constraints.exposure_weight : 0.0f;

    float total_cost = base_cost + threat_penalty + cover_bonus + elevation_penalty + terrain_penalty + exposure_penalty;

    // Contraintes absolues
    if (constraints.avoid_water && neighbor.terrain == WATER) {
        return INFINITY; // Interdit
    }

    if (neighbor.slope > constraints.max_slope) {
        return INFINITY; // Trop raide
    }

    return max(0.1f, total_cost); // Minimum 0.1 pour éviter coût nul
}
```

### PathConstraints Structure

```cpp
struct PathConstraints {
    // Poids dynamiques (0.0 = ignore, higher = plus important)
    float threat_weight = 1.0f;        // Éviter zones menace
    float cover_weight = 0.5f;         // Préférer cover
    float elevation_weight = 0.3f;     // Pénalité montées/descentes
    float terrain_weight = 1.0f;       // Pénalité terrains difficiles
    float exposure_weight = 0.8f;      // Pénalité terrain ouvert

    // Contraintes absolues
    bool avoid_water = false;
    bool avoid_roads = false;
    bool prefer_roads = false;
    float max_slope = 30.0f;           // Degrés

    // Contexte unité
    UnitType unit_type = INFANTRY;
    float unit_speed = 1.0f;

    // Doctrine (preset poids)
    Doctrine doctrine = BALANCED;
};

enum Doctrine {
    AGGRESSIVE,    // threat_weight=0.2, prefer_roads=true
    BALANCED,      // threat_weight=1.0, cover_weight=0.5
    CAUTIOUS,      // threat_weight=5.0, cover_weight=3.0
    STEALTH        // threat_weight=10.0, exposure_weight=5.0, avoid_roads=true
};
```

### Multi-Path A* (Chemins Divergents)

**Usage** : Flanking, chemins alternatifs tactiques

```cpp
std::vector<Path> findAllPaths(Position start, Position goal, int max_paths, PathConstraints constraints) {
    std::vector<Path> paths;
    std::unordered_set<Position> penalized_nodes;

    for (int i = 0; i < max_paths; i++) {
        // A* avec pénalités sur nœuds déjà utilisés
        Path path = aStarWithPenalties(start, goal, constraints, penalized_nodes);

        if (path.empty()) break; // Plus de chemins valides

        paths.push_back(path);

        // Pénalise 40% milieu du chemin (garde start/goal communs)
        int start_idx = path.waypoints.size() * 0.3;
        int end_idx = path.waypoints.size() * 0.7;

        for (int j = start_idx; j < end_idx; j++) {
            penalized_nodes.insert(path.waypoints[j]);
        }
    }

    return paths;
}

Path aStarWithPenalties(Position start, Position goal, PathConstraints constraints,
                        const std::unordered_set<Position>& penalized) {
    // A* standard mais avec coût additionnel pour nœuds pénalisés
    // cost += penalized.contains(node) ? PENALTY_COST : 0.0f;
    // PENALTY_COST = 50.0 (force divergence sans interdire)
}
```

### Exemples d'Utilisation

#### Exemple 1 : Mouvement Simple

```cpp
PathConstraints basic;
basic.threat_weight = 1.0f;
basic.unit_type = INFANTRY;

Path path = pathfinder->findPath(soldier.pos, objective, basic);
// Chemin équilibré, évite menaces modérément
```

#### Exemple 2 : Tank Blessé (Priorité Survie)

```cpp
PathConstraints wounded;
wounded.threat_weight = 10.0f;    // ÉVITER COMBAT
wounded.cover_weight = 5.0f;      // MAXIMUM COVER
wounded.terrain_weight = 0.5f;    // Distance secondaire
wounded.unit_type = TANK_MEDIUM;

Path path = pathfinder->findPath(damaged_tank.pos, repair_base, wounded);
// Peut doubler distance mais SÉCURISÉ
```

#### Exemple 3 : Flanking 3 Directions

```cpp
PathConstraints flanking;
flanking.threat_weight = 3.0f;
flanking.cover_weight = 2.0f;
flanking.exposure_weight = 5.0f;

auto paths = pathfinder->findAllPaths(tank.pos, enemy.pos, 3, flanking);

// paths[0] : Frontal (court, threat=HIGH)
// paths[1] : Flanking gauche (détour, threat=MEDIUM, cover=HIGH)
// paths[2] : Flanking droite (long, threat=LOW)

// TacticalModule score et choisit
int best_idx = tacticalModule->selectBestPath(paths, enemy);
tank.setPath(paths[best_idx]);
```

---

## 2. HPA* - Hierarchical Pathfinding

### Usage

**Quand** :
- Distance longue (> 100m)
- Traversée multi-chunks
- Navigation stratégique
- Pas besoin précision tile-par-tile

**Performance Target** :
- < 5ms pour 500m
- < 10ms pour 5000m
- Scaling logarithmique avec distance

### Concept Hiérarchique

```
NIVEAU 1 : Abstraction Globale (Clusters 256×256)
  Map 2048×2048 divisée en 8×8 clusters

  [Cluster A] --edge--> [Cluster B] --edge--> [Cluster C]
        ↓                    ↓                    ↓
     Start             (traversée)             Goal

NIVEAU 2 : Chemins Intra-Cluster (Pré-calculés)
  Dans Cluster A : Entry → Exit (A* cached)
  Dans Cluster B : Entry → Exit (A* cached)
  Dans Cluster C : Entry → Goal (A* cached)

NIVEAU 3 : Smoothing Final
  Combine chemins clusters + smooth transitions
```

### Architecture

```cpp
class HierarchicalPathfinder {
public:
    Path findPath(Position start, Position goal, PathConstraints constraints) {
        // 1. Identifier clusters start/goal
        ClusterId start_cluster = getCluster(start);
        ClusterId goal_cluster = getCluster(goal);

        // 2. A* sur graphe abstrait clusters
        std::vector<ClusterId> cluster_path = findClusterPath(start_cluster, goal_cluster);

        // 3. Pour chaque cluster, récupérer chemin intra-cluster (cached)
        Path full_path;
        for (int i = 0; i < cluster_path.size(); i++) {
            ClusterId cluster = cluster_path[i];

            Position entry = (i == 0) ? start : getClusterEntry(cluster, cluster_path[i-1]);
            Position exit = (i == cluster_path.size()-1) ? goal : getClusterExit(cluster, cluster_path[i+1]);

            Path segment = getIntraClusterPath(cluster, entry, exit, constraints);
            full_path.append(segment);
        }

        // 4. Smooth path (éliminer waypoints redondants)
        return smoothPath(full_path);
    }

private:
    struct Cluster {
        int id;
        Bounds bounds;              // Rectangle 256×256
        std::vector<Edge> edges;    // Connexions autres clusters
        PathCache intra_paths;      // Chemins pré-calculés
    };

    struct Edge {
        ClusterId from_cluster;
        ClusterId to_cluster;
        Position entry_point;
        Position exit_point;
        float cost;                 // Distance entre entry/exit
    };

    // Cache chemins intra-cluster
    std::map<ClusterId, PathCache> cluster_caches;
};
```

### Cluster Graph Construction

```cpp
void buildClusterGraph() {
    // 1. Diviser map en clusters 256×256
    int clusters_x = map_width / CLUSTER_SIZE;
    int clusters_y = map_height / CLUSTER_SIZE;

    for (int x = 0; x < clusters_x; x++) {
        for (int y = 0; y < clusters_y; y++) {
            Cluster cluster = createCluster(x, y);
            clusters.push_back(cluster);
        }
    }

    // 2. Identifier edges entre clusters adjacents
    for (auto& cluster : clusters) {
        // Check voisins (4-directional)
        for (auto& neighbor : getAdjacentClusters(cluster)) {
            // Trouver points passage entre clusters
            auto edges = findClusterEdges(cluster, neighbor);
            cluster.edges.insert(cluster.edges.end(), edges.begin(), edges.end());
        }
    }

    // 3. Pré-calculer chemins intra-cluster (edges → edges)
    for (auto& cluster : clusters) {
        precomputeIntraClusterPaths(cluster);
    }
}

std::vector<Edge> findClusterEdges(Cluster a, Cluster b) {
    std::vector<Edge> edges;

    // Frontière entre clusters
    Bounds border = getBorderBounds(a, b);

    // Scan border, trouver passages navigables
    for (int i = 0; i < border.length; i++) {
        Position pos = border.start + i;

        if (isWalkable(pos)) {
            // Début passage
            Position entry = pos;

            // Trouver fin passage
            while (isWalkable(pos) && i < border.length) {
                pos = border.start + (++i);
            }
            Position exit = pos - 1;

            // Créer edge (peut être multi-tiles large)
            Edge edge = {a.id, b.id, entry, exit, distance(entry, exit)};
            edges.push_back(edge);
        }
    }

    return edges;
}
```

### Path Caching

```cpp
class PathCache {
public:
    Path getCachedPath(Position start, Position goal) {
        CacheKey key = {start, goal};

        if (cache.contains(key)) {
            return cache[key];
        }

        // Pas en cache, calculer avec A*
        Path path = astar->findPath(start, goal);
        cache[key] = path;

        return path;
    }

    void invalidate(Position pos) {
        // Obstacle ajouté/retiré, invalider chemins affectés
        for (auto it = cache.begin(); it != cache.end();) {
            if (pathContains(it->second, pos)) {
                it = cache.erase(it);
            } else {
                ++it;
            }
        }
    }

private:
    struct CacheKey {
        Position start;
        Position goal;

        bool operator==(const CacheKey& other) const {
            return start == other.start && goal == other.goal;
        }
    };

    std::unordered_map<CacheKey, Path> cache;
};
```

### Optimisations

**1. Multi-Level Hierarchies**

Pour maps très grandes (> 4096×4096), utiliser 3+ niveaux :

```
Niveau 1 : Méga-clusters 1024×1024 (abstraction continents)
Niveau 2 : Clusters 256×256 (abstraction régions)
Niveau 3 : A* local 64×64 (précision tactique)
```

**2. Dynamic Edge Costs**

Mettre à jour coûts edges selon congestion, menaces :

```cpp
void updateEdgeCosts() {
    for (auto& edge : edges) {
        // Base cost (distance)
        float cost = distance(edge.entry, edge.exit);

        // Congestion (nb unités traversant)
        int congestion = countUnitsInEdge(edge);
        cost += congestion * CONGESTION_PENALTY;

        // Menace (ennemis proximité)
        float threat = getThreatLevel(edge.entry, edge.exit);
        cost += threat * THREAT_PENALTY;

        edge.cost = cost;
    }
}
```

---

## 3. Flow Fields - Mouvement de Groupe

### Usage

**Quand** :
- Groupe massif (≥ 10 unités)
- Même destination
- Contraintes tactiques identiques
- RTS-style group movement

**Performance Target** :
- < 15ms pour 50 unités
- < 20ms pour 100 unités
- < 30ms pour 500 unités
- Scaling linéaire avec nombre unités

### Concept Flow Field

Au lieu de calculer N chemins individuels, calcule **1 champ vectoriel** que toutes les unités suivent.

```
Destination = G

Chaque tile contient vecteur direction optimale :

↗ ↗ ↗ → → →
↗ ↗ ↗ → → G
↑ ↗ → → ↑ ↑
↑ ↑ → # # #
↑ ↑ ↑ # # #
S ↑ ↑ # # #

Unité en S : Lit vecteur ↑, se déplace nord
Unité en (2,2) : Lit vecteur ↗, se déplace nord-est

100 unités : 1 seul field calculé!
```

### Algorithme Dijkstra Inverse

```cpp
class FlowFieldGenerator {
public:
    FlowField generate(Position goal, PathConstraints constraints) {
        // 1. Créer cost field (coût depuis goal)
        CostField cost_field = generateCostField(goal, constraints);

        // 2. Générer integration field (Dijkstra depuis goal)
        IntegrationField integration_field = integrateField(cost_field, goal);

        // 3. Générer flow field (gradients direction)
        FlowField flow_field = generateFlowVectors(integration_field);

        return flow_field;
    }

private:
    CostField generateCostField(Position goal, PathConstraints constraints) {
        CostField field(map_width, map_height);

        // Chaque tile a coût basé sur terrain, menaces, etc.
        for (int x = 0; x < map_width; x++) {
            for (int y = 0; y < map_height; y++) {
                Position pos = {x, y};

                if (!isWalkable(pos)) {
                    field.set(pos, INFINITY);
                } else {
                    float cost = calculateCost(pos, constraints);
                    field.set(pos, cost);
                }
            }
        }

        return field;
    }

    IntegrationField integrateField(CostField& cost_field, Position goal) {
        IntegrationField integration(map_width, map_height, INFINITY);

        // Dijkstra INVERSE (depuis goal vers toutes positions)
        std::priority_queue<Node> open;
        integration.set(goal, 0.0f);
        open.push({goal, 0.0f});

        while (!open.empty()) {
            Node current = open.top();
            open.pop();

            for (auto& neighbor : getNeighbors(current.pos)) {
                float cost = cost_field.get(neighbor);
                if (cost == INFINITY) continue; // Non-walkable

                float new_cost = integration.get(current.pos) + cost;

                if (new_cost < integration.get(neighbor)) {
                    integration.set(neighbor, new_cost);
                    open.push({neighbor, new_cost});
                }
            }
        }

        return integration;
    }

    FlowField generateFlowVectors(IntegrationField& integration) {
        FlowField flow(map_width, map_height);

        // Pour chaque tile, calculer gradient (direction vers goal)
        for (int x = 0; x < map_width; x++) {
            for (int y = 0; y < map_height; y++) {
                Position pos = {x, y};

                // Trouver voisin avec coût minimum
                Position best_neighbor = pos;
                float min_cost = integration.get(pos);

                for (auto& neighbor : getNeighbors(pos)) {
                    float cost = integration.get(neighbor);
                    if (cost < min_cost) {
                        min_cost = cost;
                        best_neighbor = neighbor;
                    }
                }

                // Vecteur direction
                Vector2 direction = normalize(best_neighbor - pos);
                flow.set(pos, direction);
            }
        }

        return flow;
    }
};
```

### Utilisation Flow Field

```cpp
void moveUnitAlongFlowField(Unit& unit, FlowField& field) {
    // Lire direction depuis field
    Vector2 direction = field.get(unit.pos);

    // Appliquer mouvement
    Vector2 desired_velocity = direction * unit.max_speed;

    // Steering behaviors (éviter collisions)
    Vector2 separation = calculateSeparation(unit);
    Vector2 cohesion = calculateCohesion(unit);

    unit.velocity = desired_velocity + separation * 0.5f + cohesion * 0.2f;
    unit.pos += unit.velocity * delta_time;
}

Vector2 calculateSeparation(Unit& unit) {
    // Éviter unités trop proches
    Vector2 separation = {0, 0};
    int count = 0;

    for (auto& other : getNearbyUnits(unit, SEPARATION_RADIUS)) {
        if (other.id == unit.id) continue;

        Vector2 diff = unit.pos - other.pos;
        float distance = length(diff);

        if (distance > 0) {
            separation += normalize(diff) / distance; // Repousse inversement proportionnel distance
            count++;
        }
    }

    if (count > 0) {
        separation /= count;
    }

    return separation;
}
```

### Optimisations Flow Field

**1. Spatial Partitioning**

Ne générer field que dans zone active (autour groupe) :

```cpp
FlowField generateLocalField(Position goal, BoundingBox active_area) {
    // Field seulement dans active_area (ex: 512×512 autour groupe)
    // Réduit calcul de 2048×2048 → 512×512 (16× plus rapide)
}
```

**2. Multi-Resolution Fields**

```cpp
// Distant du goal : résolution basse (16×16 tiles par cell)
// Proche du goal : résolution haute (1×1 tiles par cell)

FlowField coarse_field = generate(goal, 16);  // Loin
FlowField fine_field = generate(goal, 1);     // Proche

Unit utilise field selon distance au goal
```

**3. Field Caching**

```cpp
std::unordered_map<Position, FlowField> field_cache;

FlowField getOrGenerateField(Position goal, PathConstraints constraints) {
    CacheKey key = {goal, constraints.hash()};

    if (field_cache.contains(key)) {
        return field_cache[key];
    }

    FlowField field = generator.generate(goal, constraints);
    field_cache[key] = field;

    return field;
}
```

---

## Intégration Recastnavigation

### Recastnavigation = NavMesh Professionnel

Le projet a **déjà intégré** Recastnavigation (AAA-grade library).

**Composants** :
- **Recast** : Génération NavMesh depuis geometry
- **Detour** : Queries pathfinding sur NavMesh
- **DetourCrowd** : Crowd simulation, collision avoidance
- **DetourTileCache** : Streaming NavMesh par tiles

### NavMesh vs Grid

**Grid A*** :
```
. . . # # # . .
. . . # # # . .
. . . . . . . .

Chaque tile = walkable/blocked
Pathfinding sur grille discrète
```

**NavMesh (Recast)** :
```
    Polygon 1
   /----------\
  /            \
 |   Obstacle   |  ← Zones navigables = polygones
 |              |
  \            /
   \----------/
    Polygon 2

Pathfinding sur polygones continus
```

**Avantages NavMesh** :
- ✅ Moins de nœuds (polygones vs tiles)
- ✅ Mouvement plus naturel (any-angle)
- ✅ Optimisé AAA (Recast utilisé par des dizaines jeux)

### Architecture Hybride : NavMesh + Grid

**Proposition Warfactory** :

```cpp
// NavMesh pour A* et HPA*
Path findPath_NavMesh(Position start, Position goal) {
    dtNavMeshQuery* query = navmesh->getQuery();

    dtPolyRef start_poly = query->findNearestPoly(start);
    dtPolyRef goal_poly = query->findNearestPoly(goal);

    std::vector<dtPolyRef> poly_path;
    query->findPath(start_poly, goal_poly, poly_path);

    // Convertir poly path → waypoints
    return convertToWaypoints(poly_path);
}

// Grid pour Flow Fields (plus simple génération field)
FlowField generateField_Grid(Position goal) {
    // Dijkstra sur grille 64×64
    // Plus efficace pour fields que NavMesh
}
```

**Justification** :
- NavMesh excelle pour chemins individuels (A*, HPA*)
- Grid plus simple pour flow fields (calcul uniforme)

### Intégration Chunks 64×64

```cpp
class NavMeshManager {
public:
    // Génère NavMesh tile par chunk 64×64
    void buildChunkNavMesh(Chunk& chunk) {
        rcConfig config;
        config.cs = 1.0f;              // Cell size = 1m (tile size)
        config.ch = 0.5f;              // Cell height = 0.5m
        config.walkableSlopeAngle = 45.0f;
        config.walkableHeight = 2;     // 2m min clearance
        config.walkableClimb = 1;      // 1m max step
        config.walkableRadius = 1;     // 1m agent radius

        // Extraire geometry depuis chunk
        rcPolyMesh* poly_mesh = generatePolyMesh(chunk, config);

        // Créer NavMesh tile
        dtNavMeshCreateParams params;
        // ... setup params ...

        unsigned char* nav_data = nullptr;
        int nav_data_size = 0;
        dtCreateNavMeshData(&params, &nav_data, &nav_data_size);

        // Ajouter tile au NavMesh global
        int tile_x = chunk.x / CHUNK_SIZE;
        int tile_y = chunk.y / CHUNK_SIZE;
        navmesh->addTile(nav_data, nav_data_size, 0, tile_x, tile_y);
    }

    // Rebuild tile si chunk modifié
    void onChunkModified(Chunk& chunk) {
        removeTile(chunk);
        buildChunkNavMesh(chunk);

        // Invalider chemins affectés
        invalidatePathsInChunk(chunk);
    }

private:
    dtNavMesh* navmesh;
    std::unordered_map<ChunkId, dtTileRef> chunk_tiles;
};
```

### Streaming NavMesh

```cpp
void updateNavMeshStreaming(Position player_pos) {
    const int LOAD_RADIUS = 5; // Charger 5 chunks autour joueur

    ChunkCoords player_chunk = getChunkCoords(player_pos);

    // Charger chunks proches
    for (int dx = -LOAD_RADIUS; dx <= LOAD_RADIUS; dx++) {
        for (int dy = -LOAD_RADIUS; dy <= LOAD_RADIUS; dy++) {
            ChunkCoords chunk = {player_chunk.x + dx, player_chunk.y + dy};

            if (!isNavMeshTileLoaded(chunk)) {
                loadNavMeshTile(chunk);
            }
        }
    }

    // Unload chunks lointains
    for (auto& [chunk_id, tile_ref] : loaded_tiles) {
        int distance = manhattanDistance(chunk_id, player_chunk);

        if (distance > LOAD_RADIUS + 2) {
            unloadNavMeshTile(chunk_id);
        }
    }
}
```

---

## Threat Maps & Tactical Pathfinding

### Threat Map Generation

```cpp
class ThreatMap {
public:
    void update(std::vector<Enemy>& enemies) {
        // Reset threat grid
        threat_grid.fill(0.0f);

        // Pour chaque ennemi, propager menace
        for (auto& enemy : enemies) {
            propagateThreat(enemy);
        }

        // Smooth field (blur Gaussien)
        smoothThreats(SMOOTH_RADIUS);
    }

    float getThreat(Position pos) const {
        return threat_grid.get(pos);
    }

private:
    void propagateThreat(Enemy& enemy) {
        float range = enemy.weapon_range;
        float firepower = enemy.firepower;
        Position pos = enemy.position;

        // Cercle de menace autour ennemi
        int radius = (int)range;

        for (int dx = -radius; dx <= radius; dx++) {
            for (int dy = -radius; dy <= radius; dy++) {
                float dist = sqrt(dx*dx + dy*dy);

                if (dist > range) continue;

                // Threat decay linéaire avec distance
                float threat_value = firepower * (1.0f - dist / range);

                // Line of sight check (optionnel, coûteux)
                if (USE_LOS && !hasLineOfSight(pos, pos + Vector2{dx, dy})) {
                    threat_value *= 0.2f; // Menace réduite sans LOS
                }

                int x = pos.x + dx;
                int y = pos.y + dy;

                if (inBounds(x, y)) {
                    threat_grid.add({x, y}, threat_value);
                }
            }
        }
    }

    void smoothThreats(int radius) {
        // Blur Gaussien pour smooth transitions
        Grid<float> temp = threat_grid;

        for (int x = 0; x < width; x++) {
            for (int y = 0; y < height; y++) {
                float sum = 0.0f;
                float weight_sum = 0.0f;

                for (int dx = -radius; dx <= radius; dx++) {
                    for (int dy = -radius; dy <= radius; dy++) {
                        int nx = x + dx;
                        int ny = y + dy;

                        if (!inBounds(nx, ny)) continue;

                        float dist = sqrt(dx*dx + dy*dy);
                        float weight = exp(-dist*dist / (2.0f * radius*radius));

                        sum += temp.get({nx, ny}) * weight;
                        weight_sum += weight;
                    }
                }

                threat_grid.set({x, y}, sum / weight_sum);
            }
        }
    }

    Grid<float> threat_grid;
};
```

### Cover Map

```cpp
class CoverMap {
public:
    void buildFromTerrain(TerrainMap& terrain) {
        for (int x = 0; x < width; x++) {
            for (int y = 0; y < height; y++) {
                Position pos = {x, y};

                CoverInfo info = analyzeCover(pos, terrain);
                cover_grid.set(pos, info);
            }
        }
    }

    CoverInfo getCover(Position pos) const {
        return cover_grid.get(pos);
    }

private:
    struct CoverInfo {
        bool has_cover;
        Vector2 cover_direction;    // Direction protection
        float cover_height;         // 0.0 = pas cover, 1.0 = full cover
        CoverType type;             // WALL, ROCK, BUILDING, VEGETATION
    };

    CoverInfo analyzeCover(Position pos, TerrainMap& terrain) {
        CoverInfo info;
        info.has_cover = false;

        // Check tiles adjacents pour obstacles
        for (auto& dir : CARDINAL_DIRECTIONS) {
            Position neighbor = pos + dir;

            if (terrain.isObstacle(neighbor)) {
                info.has_cover = true;
                info.cover_direction = dir;
                info.cover_height = terrain.getHeight(neighbor) / MAX_HEIGHT;
                info.type = terrain.getCoverType(neighbor);
                break;
            }
        }

        return info;
    }

    Grid<CoverInfo> cover_grid;
};
```

### Cover-to-Cover Pathfinding

```cpp
Path findCoverToCoverPath(Position start, Position goal, ThreatMap& threats, CoverMap& covers) {
    PathConstraints constraints;
    constraints.threat_weight = 5.0f;
    constraints.cover_weight = 3.0f;

    // A* avec scoring spécial pour cover
    Path path = astar->findPath(start, goal, constraints);

    // Post-process : identifier points cover sur chemin
    std::vector<Waypoint> cover_waypoints;

    for (auto& wp : path.waypoints) {
        CoverInfo cover = covers.getCover(wp.pos);

        wp.has_cover = cover.has_cover;
        wp.cover_quality = cover.cover_height;

        if (cover.has_cover) {
            wp.pause_duration = 2.0f; // Pause 2s dans cover
            cover_waypoints.push_back(wp);
        }
    }

    // Ajouter metadata pour MovementModule
    path.cover_points = cover_waypoints;
    path.movement_style = COVER_TO_COVER;

    return path;
}
```

---

## Terrain Costs

### Terrain Types

```cpp
enum TerrainType {
    ROAD,           // Asphalte, béton
    GRASS,          // Prairie, herbe
    FOREST,         // Forêt dense
    SWAMP,          // Marécage
    MOUNTAIN,       // Montagne rocheuse
    URBAN,          // Ville, bâtiments
    SAND,           // Désert
    SNOW,           // Neige profonde
    WATER,          // Eau (généralement impassable)
    RUBBLE          // Décombres
};
```

### Cost Matrix (Terrain × UnitType)

```cpp
class TerrainCostTable {
public:
    float getCost(TerrainType terrain, UnitType unit) const {
        return cost_table[terrain][unit];
    }

private:
    // [Terrain][UnitType] = multiplicateur coût
    static constexpr float cost_table[10][5] = {
        //       Infantry  Tank_Light  Tank_Heavy  Wheeled  Tracked
        /* ROAD     */ {0.5,     0.3,        0.3,       0.2,     0.4},
        /* GRASS    */ {1.0,     1.0,        1.2,       1.2,     0.9},
        /* FOREST   */ {1.5,     3.0,        5.0,       8.0,     2.5},
        /* SWAMP    */ {3.0,     8.0,        12.0,      15.0,    6.0},
        /* MOUNTAIN */ {2.0,     5.0,        8.0,       99.0,    4.0},
        /* URBAN    */ {1.2,     2.0,        2.5,       1.5,     2.0},
        /* SAND     */ {1.8,     1.5,        2.0,       3.0,     1.2},
        /* SNOW     */ {2.5,     2.0,        3.0,       4.0,     1.8},
        /* WATER    */ {99.0,    99.0,       99.0,      99.0,    99.0},
        /* RUBBLE   */ {2.0,     3.0,        4.0,       5.0,     2.5}
    };
};
```

### Dynamic Terrain Modification

```cpp
void onBuildingDestroyed(Building& building) {
    // Bâtiment détruit → terrain devient RUBBLE
    for (auto& tile : building.occupiedTiles()) {
        terrain_map.setType(tile, RUBBLE);
    }

    // Rebuild NavMesh du chunk
    Chunk& chunk = getChunk(building.pos);
    navmesh_manager->onChunkModified(chunk);

    // Invalider chemins passant par zone
    pathfinder->invalidatePathsInArea(building.bounds);
}

void onCraterCreated(Position pos, float radius) {
    // Explosion crée cratère → terrain difficile
    for (int dx = -radius; dx <= radius; dx++) {
        for (int dy = -radius; dy <= radius; dy++) {
            float dist = sqrt(dx*dx + dy*dy);
            if (dist <= radius) {
                Position tile = pos + Vector2{dx, dy};
                terrain_map.setType(tile, RUBBLE);
            }
        }
    }

    // Rebuild NavMesh
    navmesh_manager->onChunkModified(getChunk(pos));
}
```

---

## Architecture Intégration ITaskScheduler

### Vue d'Ensemble

PathfinderModule utilise **ITaskScheduler** pour déléguer pathfinding lourd au thread pool global géré par IModuleSystem, tout en conservant des opérations sync pour flow fields et queries tactiques.

```
┌─────────────────────────────────────────┐
│       IModuleSystem (ThreadPool)        │
│  ┌───────────────────────────────────┐  │
│  │      ITaskScheduler (Async)       │  │
│  │  - A* pathfinding                 │  │
│  │  - HPA* pathfinding               │  │
│  │  - Multi-path generation          │  │
│  └───────────────────────────────────┘  │
└─────────────────────────────────────────┘
           ↓ scheduleTask()
           ↓ getCompletedTask()
┌─────────────────────────────────────────┐
│        PathfinderModule                 │
│  ┌──────────────┐  ┌─────────────────┐ │
│  │  IPathfinder │  │  FlowFieldCache │ │
│  │  (internal)  │  │     (sync)      │ │
│  └──────────────┘  └─────────────────┘ │
│  ┌──────────────┐  ┌─────────────────┐ │
│  │  ThreatMap   │  │  NavMeshManager │ │
│  │   (sync)     │  │     (sync)      │ │
│  └──────────────┘  └─────────────────┘ │
└─────────────────────────────────────────┘
           ↓ publish()
           ↓ pull()
┌─────────────────────────────────────────┐
│            IIO (Pub/Sub)                │
│  - pathfinder/requests                  │
│  - pathfinder/results                   │
│  - pathfinder/flow_fields               │
└─────────────────────────────────────────┘
```

### Délégation Async vs Sync

| Opération | Threading | Justification |
|-----------|-----------|---------------|
| A* pathfinding | **ITaskScheduler (async)** | Peut prendre 5-10ms, bloque pas game loop |
| HPA* pathfinding | **ITaskScheduler (async)** | Longue distance, calcul lourd |
| Multi-path generation | **ITaskScheduler (async)** | 3× calculs A*, déléguer |
| Flow Fields | **Sync (cache)** | 15ms acceptable, 1 calcul pour N unités |
| Threat Map update | **Sync (periodic)** | Mise à jour 1×/seconde suffit |
| Cover queries | **Sync** | Lookup instantané (pre-computed) |
| NavMesh queries | **Sync** | Recastnavigation thread-safe, rapide |

---

## IPathfinder Interface (Internal)

Interface abstraite permettant swap Classic ↔ ML pathfinding.

```cpp
/**
 * @brief Abstract pathfinding interface for algorithm implementations
 *
 * Allows swapping between Classic (A*/HPA*) and ML-based pathfinding
 * without changing PathfinderModule code.
 */
class IPathfinder {
public:
    virtual ~IPathfinder() = default;

    /**
     * @brief Find single optimal path
     * @param start Starting position (float world space)
     * @param goal Goal position (float world space)
     * @param constraints Tactical constraints (threat, cover, terrain)
     * @return Computed path with waypoints
     */
    virtual Path findPath(Position start, Position goal,
                          PathConstraints constraints) = 0;

    /**
     * @brief Find N alternative paths for flanking
     * @param start Starting position
     * @param goal Goal position
     * @param max_paths Number of alternative paths (default 3)
     * @param constraints Tactical constraints
     * @return Vector of divergent paths
     */
    virtual std::vector<Path> findAllPaths(Position start, Position goal,
                                           int max_paths,
                                           PathConstraints constraints) = 0;

    /**
     * @brief Validate if path is still walkable
     * @param path Path to validate
     * @return true if path valid, false if obstacles appeared
     */
    virtual bool validatePath(const Path& path) = 0;
};

// Classic implementation (A*, HPA*, multi-path)
class ClassicPathfinder : public IPathfinder {
    Path findPath(Position start, Position goal, PathConstraints constraints) override;
    std::vector<Path> findAllPaths(Position start, Position goal, int max_paths, PathConstraints constraints) override;
    bool validatePath(const Path& path) override;
};

// ML implementation (future)
class MLPathfinder : public IPathfinder {
    // Neural network trained on Classic pathfinder outputs
    Path findPath(Position start, Position goal, PathConstraints constraints) override;
    std::vector<Path> findAllPaths(Position start, Position goal, int max_paths, PathConstraints constraints) override;
    bool validatePath(const Path& path) override;
};
```

---

## PathfinderModule Implementation

### Class Definition

```cpp
class PathfinderModule : public IModule {
private:
    // ===== FRAMEWORK INTERFACES =====
    ITaskScheduler* scheduler;  // Thread pool delegation (provided by IModuleSystem)
    IIO* io;                    // Pub/sub communication

    // ===== INTERNAL COMPONENTS =====

    // Pathfinding logic (swappable Classic ↔ ML)
    std::unique_ptr<IPathfinder> pathfinder;

    // Flow fields (sync, cached)
    FlowFieldCache flow_cache;

    // Tactical data (sync, periodic updates)
    ThreatMap threat_map;
    CoverMap cover_map;

    // NavMesh (sync queries, managed by Recastnavigation)
    NavMeshManager navmesh_mgr;
    dtNavMesh* global_navmesh;

    // Configuration
    const IDataNode* config;

public:
    // ========== IMODULE INTERFACE ==========

    void setConfiguration(const IDataNode& config, IIO* io, ITaskScheduler* scheduler) override {
        this->config = &config;
        this->io = io;
        this->scheduler = scheduler;

        // Select pathfinder implementation from config
        std::string impl = config.getString("pathfinder_impl", "classic");

        if (impl == "classic") {
            pathfinder = std::make_unique<ClassicPathfinder>();
        }
        else if (impl == "ml") {
            pathfinder = std::make_unique<MLPathfinder>();
        }

        // Initialize NavMesh manager
        navmesh_mgr.initialize(config.getChildNode("navmesh"));

        // Build initial NavMesh for loaded chunks
        buildInitialNavMesh();
    }

    json process(const json& input) override {
        // 1. Process incoming requests via IIO
        processIORequests();

        // 2. Pull completed pathfinding tasks from ITaskScheduler
        processCompletedTasks();

        // 3. Periodic threat map update (1×/second)
        if (shouldUpdateThreatMap()) {
            updateThreatMapSync();
        }

        return {};
    }

    const IDataNode& getConfiguration() override {
        return *config;
    }

    json getHealthStatus() override {
        return {
            {"module", "pathfinder"},
            {"pathfinder_impl", pathfinder ? "active" : "null"},
            {"pending_tasks", scheduler->hasCompletedTasks()},
            {"flow_fields_cached", flow_cache.size()},
            {"navmesh_tiles", navmesh_mgr.getTileCount()}
        };
    }

private:
    // ========== REQUEST PROCESSING ==========

    void processIORequests() {
        // Pull requests from IIO
        auto requests = io->pull("pathfinder/requests");

        for (auto& req : requests) {
            std::string type = req["type"];

            if (type == "single_path") {
                handleSinglePathRequest(req);
            }
            else if (type == "multi_path") {
                handleMultiPathRequest(req);
            }
            else if (type == "flow_field") {
                handleFlowFieldRequest(req);
            }
            else if (type == "tactical_query") {
                handleTacticalQuery(req);
            }
        }
    }

    void handleSinglePathRequest(const json& req) {
        // Delegate to ITaskScheduler (async multithread)
        scheduler->scheduleTask("pathfinding", {
            {"request_id", req["request_id"]},
            {"unit_id", req["unit_id"]},
            {"start", req["start"]},
            {"goal", req["goal"]},
            {"constraints", req["constraints"]},
            {"path_type", "single"}
        });
    }

    void handleMultiPathRequest(const json& req) {
        // Delegate multi-path to ITaskScheduler
        scheduler->scheduleTask("pathfinding", {
            {"request_id", req["request_id"]},
            {"unit_id", req["unit_id"]},
            {"start", req["start"]},
            {"goal", req["goal"]},
            {"constraints", req["constraints"]},
            {"path_type", "multi"},
            {"max_paths", req.value("max_paths", 3)}
        });
    }

    void handleFlowFieldRequest(const json& req) {
        // Flow fields generated SYNC (15ms acceptable, 1 calc for N units)
        Position goal = parsePosition(req["goal"]);
        PathConstraints constraints = parseConstraints(req["constraints"]);

        // Get or generate (cached)
        FlowField field = flow_cache.getOrGenerate(goal, constraints);
        FlowFieldId id = flow_cache.add(field);

        // Publish immediately
        io->publish("pathfinder/flow_fields", {
            {"request_id", req["request_id"]},
            {"field_id", id},
            {"goal", req["goal"]}
        });
    }

    void handleTacticalQuery(const json& req) {
        // Tactical queries are sync (fast lookups)
        std::string query_type = req["query_type"];

        if (query_type == "nearest_cover") {
            Position from = parsePosition(req["from"]);
            Vector2 threat_dir = parseVector2(req["threat_direction"]);
            float max_dist = req.value("max_distance", 50.0f);

            Position cover_pos = findNearestCoverSync(from, threat_dir, max_dist);

            io->publish("pathfinder/tactical_results", {
                {"request_id", req["request_id"]},
                {"query_type", "nearest_cover"},
                {"result", {cover_pos.x, cover_pos.y}}
            });
        }
        else if (query_type == "flanking_positions") {
            Position target = parsePosition(req["target"]);
            int count = req.value("count", 3);
            float distance = req.value("distance", 30.0f);

            auto positions = findFlankingPositionsSync(target, count, distance);

            io->publish("pathfinder/tactical_results", {
                {"request_id", req["request_id"]},
                {"query_type", "flanking_positions"},
                {"result", serializePositions(positions)}
            });
        }
    }

    // ========== TASK COMPLETION ==========

    void processCompletedTasks() {
        // Pull all completed pathfinding tasks from scheduler
        while (scheduler->hasCompletedTasks() > 0) {
            json result = scheduler->getCompletedTask();

            // Add tactical metadata
            enrichPathResult(result);

            // Publish result via IIO
            io->publish("pathfinder/results", result);
        }
    }

    void enrichPathResult(json& result) {
        // Add threat/cover metrics to path
        if (result.contains("path")) {
            auto waypoints = result["path"];

            float total_threat = 0.0f;
            int cover_count = 0;

            for (auto& wp : waypoints) {
                Position pos = {wp["x"], wp["y"]};

                total_threat += threat_map.getThreat(pos);
                if (cover_map.getCover(pos).has_cover) {
                    cover_count++;
                }
            }

            result["threat_level"] = total_threat / waypoints.size();
            result["cover_percentage"] = (float)cover_count / waypoints.size();
        }
    }

    // ========== SYNC OPERATIONS ==========

    bool shouldUpdateThreatMap() {
        static int last_update_frame = 0;
        int current_frame = getCurrentFrame();

        // Update 1×/second (60 frames @ 60fps)
        if (current_frame - last_update_frame >= 60) {
            last_update_frame = current_frame;
            return true;
        }

        return false;
    }

    void updateThreatMapSync() {
        // Get enemies from game state (via IIO or direct query)
        auto enemies = getEnemiesFromGameState();

        // Update threat map (sync, ~2-5ms)
        threat_map.update(enemies);
    }

    Position findNearestCoverSync(Position from, Vector2 threat_dir, float max_dist) {
        // Sync lookup in pre-computed cover map
        return cover_map.findNearest(from, threat_dir, max_dist);
    }

    std::vector<Position> findFlankingPositionsSync(Position target, int count, float distance) {
        // Generate positions around target
        std::vector<Position> positions;

        float angle_step = 2.0f * M_PI / count;

        for (int i = 0; i < count; i++) {
            float angle = i * angle_step;
            Position pos = {
                target.x + cos(angle) * distance,
                target.y + sin(angle) * distance
            };

            // Validate walkable
            if (navmesh_mgr.isWalkable(pos)) {
                positions.push_back(pos);
            }
        }

        return positions;
    }
};
```

---

## ITaskScheduler Backend (Execution)

Le backend est géré par **IModuleSystem** (pas par PathfinderModule).

```cpp
/**
 * @brief Task execution in worker threads (managed by IModuleSystem)
 *
 * PathfinderModule delegates tasks via ITaskScheduler.
 * MultithreadedModuleSystem executes tasks in thread pool.
 */
class MultithreadedModuleSystem : public IModuleSystem {
private:
    ThreadPool thread_pool;

    // Task scheduler per module
    std::map<std::string, std::unique_ptr<TaskSchedulerImpl>> schedulers;

    class TaskSchedulerImpl : public ITaskScheduler {
    private:
        ThreadPool* pool;
        std::queue<json> completed_tasks;
        std::mutex completed_mutex;

    public:
        void scheduleTask(const std::string& taskType, const json& taskData) override {
            // Submit to thread pool
            pool->enqueue([this, taskType, taskData]() {
                json result;

                if (taskType == "pathfinding") {
                    result = executePathfindingTask(taskData);
                }
                // ... other task types

                // Store result
                std::lock_guard<std::mutex> lock(completed_mutex);
                completed_tasks.push(result);
            });
        }

        int hasCompletedTasks() const override {
            std::lock_guard<std::mutex> lock(completed_mutex);
            return completed_tasks.size();
        }

        json getCompletedTask() override {
            std::lock_guard<std::mutex> lock(completed_mutex);

            if (completed_tasks.empty()) {
                return {};
            }

            json result = completed_tasks.front();
            completed_tasks.pop();
            return result;
        }

    private:
        json executePathfindingTask(const json& taskData) {
            // Thread-local pathfinder (no shared state)
            static thread_local ClassicPathfinder pathfinder;

            Position start = parsePosition(taskData["start"]);
            Position goal = parsePosition(taskData["goal"]);
            PathConstraints constraints = parseConstraints(taskData["constraints"]);

            if (taskData["path_type"] == "single") {
                Path path = pathfinder.findPath(start, goal, constraints);

                return {
                    {"task_type", "pathfinding"},
                    {"request_id", taskData["request_id"]},
                    {"unit_id", taskData["unit_id"]},
                    {"path", serializePath(path)}
                };
            }
            else if (taskData["path_type"] == "multi") {
                int max_paths = taskData["max_paths"];
                auto paths = pathfinder.findAllPaths(start, goal, max_paths, constraints);

                return {
                    {"task_type", "pathfinding"},
                    {"request_id", taskData["request_id"]},
                    {"unit_id", taskData["unit_id"]},
                    {"paths", serializePaths(paths)}
                };
            }

            return {};
        }
    };
};
```

---

## Flow Fields avec Float Positions

### Problème : Grid Discrète vs Unités Float

```
Flow Field = grille discrète (tiles entiers)
Unités = positions float continues

Unit pos = (127.34, 89.67)  ← Float world space
Flow Field cell = [127, 89]  ← Grid space
```

### Solution : Interpolation Bilinéaire

```cpp
/**
 * @brief Get flow direction at continuous float position
 * @param field Flow field (discrete grid)
 * @param float_pos Unit position (continuous float)
 * @return Interpolated direction vector
 */
Vector2 getFlowDirection(FlowField& field, Position float_pos) {
    // Convert float → grid coords
    int x0 = (int)floor(float_pos.x);
    int y0 = (int)floor(float_pos.y);
    int x1 = x0 + 1;
    int y1 = y0 + 1;

    // Interpolation factors (0.0-1.0)
    float fx = float_pos.x - x0;
    float fy = float_pos.y - y0;

    // Read 4 neighbor vectors
    Vector2 v00 = field.get(x0, y0);
    Vector2 v10 = field.get(x1, y0);
    Vector2 v01 = field.get(x0, y1);
    Vector2 v11 = field.get(x1, y1);

    // Bilinear interpolation
    Vector2 v0 = lerp(v00, v10, fx);  // Horizontal interpolation
    Vector2 v1 = lerp(v01, v11, fx);
    Vector2 result = lerp(v0, v1, fy); // Vertical interpolation

    return normalize(result);
}

Vector2 lerp(Vector2 a, Vector2 b, float t) {
    return {
        a.x + (b.x - a.x) * t,
        a.y + (b.y - a.y) * t
    };
}
```

### Unit Movement with Flow Field

```cpp
/**
 * @brief Update unit position using flow field + steering behaviors
 * @param unit Unit to update (float position, float velocity)
 * @param field Flow field
 * @param delta_time Frame delta time
 */
void updateUnitWithFlowField(Unit& unit, FlowField& field, float delta_time) {
    // 1. Read desired direction from flow field (interpolated)
    Vector2 desired_direction = getFlowDirection(field, unit.pos);

    // 2. Steering behaviors (boids-style)
    Vector2 separation = calculateSeparation(unit);   // Avoid other units
    Vector2 cohesion = calculateCohesion(unit);       // Stay grouped
    Vector2 alignment = calculateAlignment(unit);     // Align with group

    // 3. Combine (weighted)
    Vector2 steering = desired_direction * 1.0f +     // Flow field priority
                       separation * 0.8f +             // Collision avoidance
                       cohesion * 0.3f +               // Group cohesion
                       alignment * 0.2f;               // Direction alignment

    // 4. Apply velocity
    unit.velocity = normalize(steering) * unit.max_speed;
    unit.pos += unit.velocity * delta_time;

    // 5. Collision resolution (physics)
    resolveUnitCollisions(unit);
}
```

### Unit-to-Unit Collisions (Float Space)

```cpp
/**
 * @brief Resolve collisions between units (float positions, circular colliders)
 * @param unit Unit to check collisions for
 */
void resolveUnitCollisions(Unit& unit) {
    // Spatial hash for fast neighbor queries
    auto nearby = spatial_hash.query(unit.pos, unit.radius * 3.0f);

    for (auto& other : nearby) {
        if (other.id == unit.id) continue;

        Vector2 diff = unit.pos - other.pos;
        float dist = length(diff);
        float min_dist = unit.radius + other.radius;

        if (dist < min_dist && dist > 0.001f) {
            // Collision detected! Separate units
            Vector2 separation = normalize(diff) * (min_dist - dist) * 0.5f;

            unit.pos += separation;
            other.pos -= separation;

            // Velocity damping (elastic bounce)
            float restitution = 0.3f;
            float impact = dot(unit.velocity, normalize(diff));

            unit.velocity -= normalize(diff) * impact * restitution;
            other.velocity += normalize(diff) * impact * restitution;
        }
    }
}

/**
 * @brief Calculate separation force (boids steering)
 * @param unit Unit to calculate separation for
 * @return Separation vector (away from nearby units)
 */
Vector2 calculateSeparation(Unit& unit) {
    const float SEPARATION_RADIUS = 5.0f; // 5m radius

    Vector2 separation = {0, 0};
    int count = 0;

    auto nearby = spatial_hash.query(unit.pos, SEPARATION_RADIUS);

    for (auto& other : nearby) {
        if (other.id == unit.id) continue;

        Vector2 diff = unit.pos - other.pos;
        float dist = length(diff);

        if (dist > 0 && dist < SEPARATION_RADIUS) {
            // Force inversely proportional to distance
            separation += normalize(diff) / dist;
            count++;
        }
    }

    if (count > 0) {
        separation /= count;
    }

    return separation;
}
```

### Path Structure

```cpp
struct Path {
    std::vector<Waypoint> waypoints;

    // Metrics tactiques
    float length;                   // Distance totale (m)
    float threat_level;             // 0.0-1.0 (exposition ennemie)
    float cover_percentage;         // % du chemin avec cover
    bool crosses_open_terrain;      // Traverse terrain ouvert ?
    bool has_chokepoints;           // Contient goulets ?

    // Metadata
    PathfindingAlgorithm algorithm; // A*, HPA*, ou FLOW_FIELD
    float computation_time_ms;      // Temps calcul
    int waypoint_count;

    // Cover points
    std::vector<Waypoint> cover_points; // Waypoints avec cover
    MovementStyle movement_style;       // DIRECT, COVER_TO_COVER, STEALTH

    // Validation
    bool is_valid;
    int last_validation_frame;
};

struct Waypoint {
    Position pos;

    // Tactical metadata
    bool has_cover;
    float cover_quality;            // 0.0-1.0
    Vector2 cover_direction;        // Direction protection
    float threat_level;             // Menace à cette position

    // Movement metadata
    float pause_duration;           // Temps pause (cover, observation)
    MovementSpeed speed;            // SPRINT, RUN, WALK, CROUCH
};

enum MovementStyle {
    DIRECT,             // Ligne droite, rapide
    COVER_TO_COVER,     // Pause dans covers
    STEALTH,            // Lent, évite détection
    AGGRESSIVE          // Rapide, ignore menaces
};
```

---

## Performance Benchmarks & Targets

### Targets par Algorithme

| Algorithme | Distance | Unités | Target | Acceptable |
|------------|----------|--------|--------|------------|
| A* | 50m | 1 | < 2ms | < 5ms |
| A* | 100m | 1 | < 5ms | < 10ms |
| HPA* | 500m | 1 | < 5ms | < 10ms |
| HPA* | 5000m | 1 | < 10ms | < 15ms |
| Flow Field | 500m | 50 | < 15ms | < 20ms |
| Flow Field | 500m | 100 | < 20ms | < 30ms |
| Multi-Path (3) | 100m | 1 | < 10ms | < 15ms |

### Budget Frame (60fps = 16.67ms)

```
Total Frame Budget : 16.67ms

Distribution :
- Rendering : 6ms (36%)
- Physics : 2ms (12%)
- AI Decisions : 2ms (12%)
- Pathfinding : 4ms (24%) ← BUDGET
- Movement : 1ms (6%)
- Other : 1.67ms (10%)

Pathfinding budget : 4ms MAX
  → ~2 A* paths per frame
  → ou 1 Flow Field
  → ou 4 HPA* paths
```

### Optimisations Performance

**1. Async Pathfinding**

```cpp
class AsyncPathfinder {
public:
    std::future<Path> findPathAsync(Position start, Position goal, PathConstraints constraints) {
        return std::async(std::launch::async, [=]() {
            return pathfinder->findPath(start, goal, constraints);
        });
    }

    void update() {
        // Check completed async requests
        for (auto it = pending_requests.begin(); it != pending_requests.end();) {
            if (it->future.wait_for(std::chrono::milliseconds(0)) == std::future_status::ready) {
                Path path = it->future.get();
                it->callback(path);
                it = pending_requests.erase(it);
            } else {
                ++it;
            }
        }
    }
};
```

**2. Path Pooling**

```cpp
class PathPool {
public:
    Path* acquire() {
        if (available_paths.empty()) {
            return new Path();
        }

        Path* path = available_paths.back();
        available_paths.pop_back();
        path->clear();
        return path;
    }

    void release(Path* path) {
        available_paths.push_back(path);
    }

private:
    std::vector<Path*> available_paths;
};
```

**3. Spatial Hashing**

```cpp
class SpatialPathCache {
public:
    Path* getCachedPath(Position start, Position goal, float tolerance = 5.0f) {
        // Hash start/goal dans grille spatiale
        CellId cell = hashPosition(start, goal);

        auto& paths_in_cell = spatial_cache[cell];

        for (auto& cached : paths_in_cell) {
            if (distance(cached.start, start) < tolerance &&
                distance(cached.goal, goal) < tolerance) {

                // Valider chemin encore valide
                if (validatePath(cached.path)) {
                    return &cached.path;
                }
            }
        }

        return nullptr; // Pas en cache
    }
};
```

---

## Cas d'Usage Complets

### Cas 1 : Infanterie Avance sous Feu

```cpp
// Situation : 10 soldats doivent traverser zone sous feu ennemi
Position start = squad.getCenter();
Position objective = {500, 300};

// Setup threat map
ThreatMap threats;
threats.addThreatSource(enemy_mg.pos, enemy_mg.range, enemy_mg.firepower);

// Contraintes : MAX cover, éviter menaces
PathConstraints infantry_constraints;
infantry_constraints.threat_weight = 5.0f;
infantry_constraints.cover_weight = 3.0f;
infantry_constraints.exposure_weight = 10.0f;
infantry_constraints.unit_type = INFANTRY;
infantry_constraints.doctrine = CAUTIOUS;

// Génère chemin cover-to-cover
Path path = pathfinder->findCoverToCoverPath(start, objective, threats, cover_map);

// Assigne aux unités
for (auto& soldier : squad) {
    soldier.setPath(path);
    soldier.movement_style = COVER_TO_COVER;
}

// Résultat :
// - Chemin zigzague entre covers
// - Pauses 2-3s dans chaque cover
// - Évite terrain ouvert
// - Traverse zone en 45s au lieu de 15s (direct)
// - 0 pertes au lieu de 50% (direct)
```

### Cas 2 : Tank Assault avec 3 Routes Flanking

```cpp
// Situation : 1 tank doit attaquer position fortifiée
Position tank_pos = {100, 100};
Position enemy_bunker = {400, 400};

// Contraintes tank
PathConstraints tank_constraints;
tank_constraints.threat_weight = 2.0f;
tank_constraints.terrain_weight = 2.0f;  // Évite forêts
tank_constraints.prefer_roads = true;
tank_constraints.unit_type = TANK_MEDIUM;

// Génère 3 chemins alternatifs
auto paths = pathfinder->findAllPaths(tank_pos, enemy_bunker, 3, tank_constraints);

// Score chemins selon situation tactique
TacticalScore scores[3];
for (int i = 0; i < 3; i++) {
    scores[i].threat = paths[i].threat_level;
    scores[i].distance = paths[i].length;
    scores[i].cover = paths[i].cover_percentage;
    scores[i].time = paths[i].length / tank.speed;

    // Score composite (doctrine agressive)
    scores[i].total =
        scores[i].threat * -0.3f +      // Menace pas trop importante
        scores[i].distance * -0.2f +    // Distance compte un peu
        scores[i].cover * 0.1f +        // Cover bonus mineur
        scores[i].time * -0.4f;         // Vitesse PRIORITÉ
}

// Choisit meilleur
int best = std::max_element(scores, scores+3) - scores;
tank.setPath(paths[best]);

// Résultat :
// paths[0] : Direct, threat=0.8, time=20s → score=-0.5
// paths[1] : Flanking gauche, threat=0.4, time=30s → score=-0.3 ✅ CHOISI
// paths[2] : Flanking droite (forêt), threat=0.2, time=60s → score=-0.8
```

### Cas 3 : 50 Tanks Convergent vers Objectif

```cpp
// Situation : 50 tanks dispersés convergent vers point rally
Position rally_point = {1000, 1000};

// Contraintes communes
PathConstraints tank_constraints;
tank_constraints.prefer_roads = true;
tank_constraints.unit_type = TANK_HEAVY;

// Check si flow field viable
int tanks_with_same_goal = 0;
for (auto& tank : all_tanks) {
    if (tank.goal == rally_point) {
        tanks_with_same_goal++;
    }
}

if (tanks_with_same_goal >= 10) {
    // Flow Field optimal
    FlowField field = pathfinder->generateFlowField(rally_point, tank_constraints);

    for (auto& tank : all_tanks) {
        if (tank.goal == rally_point) {
            tank.setFlowField(field); // Partagé!
        }
    }

    // Performance : 15ms pour 50 tanks au lieu de 50 × 5ms = 250ms

} else {
    // Pas assez d'unités, HPA* individuel
    for (auto& tank : all_tanks) {
        Path path = pathfinder->findPath(tank.pos, rally_point, tank_constraints);
        tank.setPath(path);
    }
}
```

---

## Configuration Module

### gameconfig.json

```json
{
  "modules": {
    "pathfinding": {
      "enabled": true,
      "frequency": 10,

      "algorithms": {
        "astar": {
          "max_distance": 100.0,
          "max_iterations": 10000,
          "heuristic": "euclidean"
        },

        "hierarchical": {
          "cluster_size": 256,
          "levels": 2,
          "cache_size": 1000,
          "rebuild_interval": 300
        },

        "flow_field": {
          "resolution": 1.0,
          "smooth_radius": 2,
          "local_field_size": 512,
          "cache_duration": 10.0
        }
      },

      "navmesh": {
        "cell_size": 1.0,
        "cell_height": 0.5,
        "agent_height": 2.0,
        "agent_radius": 1.0,
        "max_slope": 45.0,
        "max_climb": 1.0
      },

      "performance": {
        "async_pathfinding": true,
        "max_paths_per_frame": 2,
        "path_pool_size": 100,
        "cache_paths": true,
        "cache_size": 500
      },

      "tactical": {
        "update_threat_map": true,
        "threat_map_resolution": 2.0,
        "cover_detection_radius": 5.0,
        "line_of_sight_checks": true
      },

      "debug": {
        "visualize_paths": false,
        "visualize_flow_fields": false,
        "visualize_navmesh": false,
        "log_performance": true
      }
    }
  }
}
```

---

## Roadmap Implémentation

### Phase 1 : Foundation (2 semaines)
- [ ] Structure Path, Waypoint, PathConstraints
- [ ] Interface PathfinderModule complète
- [ ] A* basique sur grille 64×64
- [ ] Terrain cost table
- [ ] Tests unitaires A*

### Phase 2 : Weighted A* (1 semaine)
- [ ] ThreatMap implementation
- [ ] CoverMap implementation
- [ ] Weighted cost calculation
- [ ] PathConstraints integration
- [ ] Doctrine presets

### Phase 3 : Multi-Path (1 semaine)
- [ ] Penalty-based A* pour divergence
- [ ] findAllPaths() implementation
- [ ] Path scoring tactique
- [ ] Tests flanking scenarios

### Phase 4 : Recastnavigation (2 semaines)
- [ ] NavMesh génération par chunk
- [ ] Detour queries integration
- [ ] NavMesh streaming
- [ ] Dynamic obstacle updates
- [ ] NavMesh rebuild system

### Phase 5 : HPA* (2 semaines)
- [ ] Cluster graph construction
- [ ] Intra-cluster path caching
- [ ] Inter-cluster A* sur abstract graph
- [ ] Path smoothing
- [ ] Multi-level hierarchies

### Phase 6 : Flow Fields (1 semaine)
- [ ] Cost field generation
- [ ] Integration field (Dijkstra inverse)
- [ ] Flow vector field
- [ ] Unit steering along field
- [ ] Field caching

### Phase 7 : Optimization (1 semaine)
- [ ] Async pathfinding
- [ ] Path pooling
- [ ] Spatial caching
- [ ] Performance profiling
- [ ] Benchmarks validation

### Phase 8 : Polish (1 semaine)
- [ ] Cover-to-cover pathfinding
- [ ] Flanking position finder
- [ ] Line of sight queries
- [ ] Debug visualization
- [ ] Documentation finalization

**Total : ~11 semaines pour système complet**

---

## Références Techniques

### Algorithmes
- **A***: Hart, P. E.; Nilsson, N. J.; Raphael, B. (1968). "A Formal Basis for the Heuristic Determination of Minimum Cost Paths"
- **HPA***: Botea, Müller, Schaeffer (2004). "Near Optimal Hierarchical Path-Finding"
- **Flow Fields**: Elias (2010). "Crowd Path Finding and Steering Using Flow Field Tiles"

### Libraries
- **Recastnavigation**: https://github.com/recastnavigation/recastnavigation
- **Détails integration**: `src/core/_deps/recastnavigation-src/`

### Warfactory Docs
- `map-system.md` : Chunk system 64×64
- `systemes-techniques.md` : Architecture multi-échelle
- `ai-framework.md` : PathfinderModule interface, AI integration
- `systeme-militaire.md` : Tactical AI, doctrines

---

## Glossaire

- **A*** : Algorithme pathfinding optimal avec heuristique
- **HPA*** : Hierarchical Pathfinding A*, multi-niveaux abstraction
- **Flow Field** : Champ vectoriel direction optimale vers goal
- **NavMesh** : Navigation Mesh, polygones navigables
- **Dijkstra** : Algorithme shortest path sans heuristique
- **Threat Map** : Grille valeurs menace ennemie
- **Cover Map** : Grille positions cover disponibles
- **Waypoint** : Point passage sur chemin
- **Constraint** : Contrainte pathfinding (poids, interdictions)
- **Doctrine** : Preset poids tactiques (aggressive, cautious, etc.)
- **Cluster** : Zone abstraction pour HPA*
- **Edge** : Connexion entre clusters HPA*
- **Integration Field** : Champ coûts cumulés depuis goal (flow fields)
- **Cost Field** : Champ coûts base terrain (flow fields)

---

**Ce système hybride offre le meilleur des trois mondes : précision tactique (A*), vitesse longue distance (HPA*), et scaling groupes massifs (Flow Fields).**