68 citations · 107 across the 4 of their papers we have counts for
4 papers
Following Instructions by Imagining and Reaching Visual Goals
John Kanu, Eadom Dessalene, Xiaomin Lin +2
While traditional methods for instruction-following typically assume prior linguistic and perceptual knowledge, many recent works in reinforcement learning (RL) have proposed learn…
Multi-agent Inverse Reinforcement Learning for Certain General-sum Stochastic Games
Xiaomin Lin, Stephen C. Adams, Peter A. Beling
This paper addresses the problem of multi-agent inverse reinforcement learning (MIRL) in a two-player general-sum stochastic game framework. Five variants of MIRL are considered: u…
Comparison of Multi-agent and Single-agent Inverse Learning on a Simulated Soccer Example
Xiaomin Lin, Peter A. Beling, Randy Cogill
We compare the performance of Inverse Reinforcement Learning (IRL) with the relative new model of Multi-agent Inverse Reinforcement Learning (MIRL). Before comparing the methods, w…
Multi-agent Inverse Reinforcement Learning for Two-person Zero-sum Games
Xiaomin Lin, Peter A. Beling, Randy Cogill
The focus of this paper is a Bayesian framework for solving a class of problems termed multi-agent inverse reinforcement learning (MIRL). Compared to the well-known inverse reinfor…