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Improved Multi-agent Reinforcement Learning for Path Planning based Crowd Simulation
2019
IEEE Access
The combination of multi-agent technology and reinforcement learning methods has been recognized as an effective way which is used in path planning-based crowd simulation. However, the existing solution is still not satisfactory due to the problem in the mutual influence of agents. Therefore, an improved multi-agent reinforcement learning method (IMARL algorithm) is introduced. In this method, the intersection of the pedestrian trajectory extracted from the real video is first used as the state
doi:10.1109/access.2019.2920913
fatcat:mei7jlheznbvtdo3jbkt3w4bca