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examples/multiagent.py

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+"""Example: multi-agent self-play with BlokusMultiAgentEnv."""
+import numpy as np
+
+from blokus_gym import BlokusMultiAgentEnv, GreedyBot, RandomBot
+
+
+def main():
+    env = BlokusMultiAgentEnv(num_players=2, board_size=7)
+
+    # Create bots for each player
+    bots = {
+        "player_0": RandomBot(player_idx=0, seed=42),
+        "player_1": GreedyBot(player_idx=1),
+    }
+
+    obs, info = env.reset(seed=42)
+    print("=== Multi-Agent Game ===")
+    print(f"Agents: {env.agents}")
+
+    steps = 0
+    while True:
+        for agent in env.agents:
+            obs, info = env.last() if hasattr(env, "last") else (obs.get(agent, {}), {})
+            mask = env.get_action_mask(agent)
+            valid_actions = np.where(mask)[0]
+
+            if len(valid_actions) > 0:
+                bot = bots[agent]
+                action = bot.select_action(env.game, mask)
+                if action is not None:
+                    obs, rewards, terminations, truncations, infos = env.step(action)
+                    steps += 1
+
+                    if terminations[agent]:
+                        print(f"Game over after {steps} steps")
+                        scores = env.game.get_scores()
+                        for i, score in enumerate(scores):
+                            print(f"  Player {i}: {score}")
+                        env.close()
+                        return
+
+    env.close()
+
+
+if __name__ == "__main__":
+    main()