38 citations · 121 across the 7 of their papers we have counts for
3 papers · 1 filter
Inverse Reinforcement Learning for Strategy Identification
Mark Rucker, Stephen Adams, Roy Hayes +1
In adversarial environments, one side could gain an advantage by identifying the opponent's strategy. For example, in combat games, if an opponents strategy is identified as overly…
Empirically Measuring Transfer Distance for System Design and Operation
Tyler Cody, Stephen Adams, Peter A. Beling
Classical machine learning approaches are sensitive to non-stationarity. Transfer learning can address non-stationarity by sharing knowledge from one system to another, however, in…
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…