multiagent-particle-envs
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Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
def reward(self, agent, world): # squared distance from listener to landmark a = world.agents[0] dist2 = np.sum(np.square(a.goal_a.state.p_pos - a.goal_b.state.p_pos)) return -dist2 But world.agents[0] is the speaker
Traceback (most recent call last): File "D:/My_Research/MAS_code/Python/multiagent-particle-envs-master/bin/interactive.py", line 36, in env.render() File "D:\My_Research\MAS_code\Python\multiagent-particle-envs-master\bin\..\multiagent\environment.py", line 261, in render results.append(self.viewers[i].render(return_rgb_array = mode=='rgb_array')) File "D:\My_Research\MAS_code\Python\multiagent-particle-envs-master\bin\..\multiagent\rendering.py", line 110, in render self.window.flip() File "C:\Python27\lib\site-packages\pyglet\window\win32\__init__.py", line...
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