f

content/uploads/2024/battleship-solvers/battleship_genetic2.py

@@ -20,6 +20,7 @@ MUTATION_MULTIPLIERS = {
     "parity_weight": 1.5,
     "hunt_mode_threshold": 1.0,
     "prob_grid_weight": 1.0,
+    "avoid_edges_weight": 1.0,  # Added for avoid_edges_weight
 }
 
 
@@ -30,6 +31,7 @@ class BattleshipStrategy:
     PARITY_WEIGHT_RANGE = (0, 10)
     HUNT_MODE_THRESHOLD_RANGE = (0.1, 1)
     PROB_GRID_WEIGHT_RANGE = (0, 1)
+    AVOID_EDGES_WEIGHT_RANGE = (0, 1)  # New weight range
 
     def __init__(self):
         self.adjacent_hit_weight = random.uniform(*self.ADJACENT_HIT_WEIGHT_RANGE)
@@ -37,6 +39,9 @@ class BattleshipStrategy:
         self.parity_weight = random.uniform(*self.PARITY_WEIGHT_RANGE)
         self.hunt_mode_threshold = random.uniform(*self.HUNT_MODE_THRESHOLD_RANGE)
         self.prob_grid_weight = random.uniform(*self.PROB_GRID_WEIGHT_RANGE)
+        self.avoid_edges_weight = random.uniform(
+            *self.AVOID_EDGES_WEIGHT_RANGE
+        )  # Initialize new weight
         self._probability_grid = None
 
     def serialize(self, include_grid=False):
@@ -46,6 +51,7 @@ class BattleshipStrategy:
             "parity_weight": self.parity_weight,
             "hunt_mode_threshold": self.hunt_mode_threshold,
             "prob_grid_weight": self.prob_grid_weight,
+            "avoid_edges_weight": self.avoid_edges_weight,  # Include in serialization
         }
         if include_grid:
             data["probability_grid"] = self.probability_grid
@@ -83,6 +89,12 @@ class BattleshipStrategy:
                 ):
                     self.probability_grid[ni][nj] *= self.adjacent_hit_weight
 
+        # Apply avoid_edges_weight
+        for i in range(GRID_SIZE):
+            for j in range(GRID_SIZE):
+                if i == 0 or i == GRID_SIZE - 1 or j == 0 or j == GRID_SIZE - 1:
+                    self.probability_grid[i][j] *= 1 - self.avoid_edges_weight
+
         max_prob = max(max(row) for row in self.probability_grid if max(row) > 0)
         if max_prob > 0:
             for i in range(GRID_SIZE):
@@ -220,6 +232,12 @@ def crossover(parent1, parent2):
     child.hunt_mode_threshold = random.choice(
         [parent1.hunt_mode_threshold, parent2.hunt_mode_threshold]
     )
+    child.prob_grid_weight = random.choice(
+        [parent1.prob_grid_weight, parent2.prob_grid_weight]
+    )
+    child.avoid_edges_weight = random.choice(
+        [parent1.avoid_edges_weight, parent2.avoid_edges_weight]
+    )
     return child
 
 
@@ -250,6 +268,13 @@ def mutate(individual):
         individual.prob_grid_weight = random.uniform(
             *BattleshipStrategy.PROB_GRID_WEIGHT_RANGE
         )
+    if (
+        random.random()
+        < BASE_MUTATION_RATE * MUTATION_MULTIPLIERS["avoid_edges_weight"]
+    ):
+        individual.avoid_edges_weight = random.uniform(
+            *BattleshipStrategy.AVOID_EDGES_WEIGHT_RANGE
+        )
     return individual
 
 
@@ -345,7 +370,7 @@ def genetic_algorithm(continue_training=False):
                 json.dump(
                     [strategy.serialize() for strategy in population], f, indent=4
                 )
-            #tqdm.write(f"Generation {generation + 1} saved successfully.")
+            # tqdm.write(f"Generation {generation + 1} saved successfully.")
         except Exception as e:
             tqdm.write(f"Error saving generation {generation + 1}: {e}")