687 citations · 3k across the 109 of their papers we have counts for
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cs.AI2012
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Tobias Jung, Peter Stone
Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of the main cha…
cs.AI2012
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-like Exploration
Tobias Jung, Peter Stone
We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achieve low sa…
cs.AI2012★ 2 cited
Empowerment for Continuous Agent-Environment Systems
Tobias Jung, Daniel Polani, Peter Stone
This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the effic…