2 citations · 2 across the 12 of their papers we have counts for
4 papers · 1 filter
Action-Dependent Optimality-Preserving Reward Shaping
Grant C. Forbes, Jianxun Wang, Leonardo Villalobos-Arias +2
Recent RL research has utilized reward shaping--particularly complex shaping rewards such as intrinsic motivation (IM)--to encourage agent exploration in sparse-reward environments…
Potential-Based Intrinsic Motivation: Preserving Optimality With Complex, Non-Markovian Shaping Rewards
Grant C. Forbes, Leonardo Villalobos-Arias, Jianxun Wang +2
Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertentl…
Potential-Based Reward Shaping For Intrinsic Motivation
Grant C. Forbes, Nitish Gupta, Leonardo Villalobos-Arias +3
Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertentl…
Modeling Risk in Reinforcement Learning: A Literature Mapping
Leonardo Villalobos-Arias, Derek Martin, Abhijeet Krishnan +3
Safe reinforcement learning deals with mitigating or avoiding unsafe situations by reinforcement learning (RL) agents. Safe RL approaches are based on specific risk representations…