Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations
Modeling of real-world biological multi-agents is a fundamental problem in various scientific
and engineering fields. Reinforcement learning (RL) is a powerful framework to generate …
and engineering fields. Reinforcement learning (RL) is a powerful framework to generate …
Bidirectional GaitNet: A Bidirectional Prediction Model of Human Gait and Anatomical Conditions
We present a novel generative model, called Bidirectional GaitNet, that learns the
relationship between human anatomy and its gait. The simulation model of human anatomy …
relationship between human anatomy and its gait. The simulation model of human anatomy …
Emergent Dominance Hierarchies in Reinforcement Learning Agents
Modern Reinforcement Learning (RL) algorithms are able to outperform humans in a wide
variety of tasks. Multi-agent reinforcement learning (MARL) settings present additional …
variety of tasks. Multi-agent reinforcement learning (MARL) settings present additional …