Importance Sampling-Guided Meta-Training for Intelligent Agents in Highly Interactive Environments
Mansur Arief, Mike Timmerman, David Isele, Mykel J. Kochenderfer
Training intelligent agents to navigate highly interactive environments presents significant challenges. While guided meta reinforcement learning (RL) approach that first trains a guiding policy to train the ego agent has proven effective in improving generalizability across scenarios with various levels of interaction, …
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IEEE Robotics and Automation Letters