Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation


In this paper, the calibration of a framework based in Multiagent Reinforcement Learning (RL) for generating motion simulations of pedestrian groups is presented. The framework sets a group of autonomous embodied agents that learn to control individually its instant velocity vector in scenarios with collisions and friction forces. The result of the process… (More)
DOI: 10.1007/978-3-642-34710-8_28


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