102 citations · 255 across the 30 of their papers we have counts for
5 papers · 1 filter
Generalization in Text-based Games via Hierarchical Reinforcement Learning
Yunqiu Xu, Meng Fang, Ling Chen +2
Deep reinforcement learning provides a promising approach for text-based games in studying natural language communication between humans and artificial agents. However, the general…
Is Nash Equilibrium Approximator Learnable?
Zhijian Duan, Wenhan Huang, Dinghuai Zhang +4
In this paper, we investigate the learnability of the function approximator that approximates Nash equilibrium (NE) for games generated from a distribution. First, we offer a gener…
MHER: Model-based Hindsight Experience Replay
Rui Yang, Meng Fang, Lei Han +3
Solving multi-goal reinforcement learning (RL) problems with sparse rewards is generally challenging. Existing approaches have utilized goal relabeling on collected experiences to…
Ordering-Based Causal Discovery with Reinforcement Learning
Xiaoqiang Wang, Yali Du, Shengyu Zhu +4
It is a long-standing question to discover causal relations among a set of variables in many empirical sciences. Recently, Reinforcement Learning (RL) has achieved promising result…
Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du +6
Multi-agent reinforcement learning (MARL) has become effective in tackling discrete cooperative game scenarios. However, MARL has yet to penetrate settings beyond those modelled by…