research
∙
11/02/2022
Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement
Adaptive mesh refinement (AMR) is necessary for efficient finite element...
share
research
∙
12/20/2021
Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning
Critical sectors of human society are progressing toward the adoption of...
research
∙
05/18/2021
Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach
Multi-agent reinforcement learning (MARL) becomes more challenging in th...
research
∙
03/01/2021
Reinforcement Learning for Adaptive Mesh Refinement
Large-scale finite element simulations of complex physical systems gover...
research
∙
07/07/2020
GraphOpt: Learning Optimization Models of Graph Formation
Formation mechanisms are fundamental to the study of complex networks, b...
research
∙
06/10/2020
Learning to Incentivize Other Learning Agents
The challenge of developing powerful and general Reinforcement Learning ...
research
∙
12/07/2019
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery
Human players in professional team sports achieve high level coordinatio...
research
∙
10/17/2019
Single Episode Policy Transfer in Reinforcement Learning
Transfer and adaptation to new unknown environmental dynamics is a key c...
research
∙
09/23/2019
Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization
Traffic congestion in metropolitan areas is a world-wide problem that ca...
research
∙
09/13/2018
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
We propose CM3, a new deep reinforcement learning method for cooperative...
research
∙
11/08/2017
Learning Deep Mean Field Games for Modeling Large Population Behavior
We consider the problem of representing collective behavior of large pop...
research
∙
11/08/2017