23 citations · 101 across the 30 of their papers we have counts for
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cs.RO2024
SuPLE: Robot Learning with Lyapunov Rewards
Phu Nguyen, Daniel Polani, Stas Tiomkin
The reward function is an essential component in robot learning. Reward directly affects the sample and computational complexity of learning, and the quality of a solution. The des…
cs.LG2024
Boosting Soft Q-Learning by Bounding
Jacob Adamczyk, Volodymyr Makarenko, Stas Tiomkin +1
An agent's ability to leverage past experience is critical for efficiently solving new tasks. Prior work has focused on using value function estimates to obtain zero-shot approxima…
cs.AI2024
Learning telic-controllable state representations
Nadav Amir, Stas Tiomkin
Computational models of purposeful behavior comprise both descriptive and prescriptive aspects, used respectively to ascertain and evaluate situations in the world. In reinforcemen…