Doina Precup
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The paper introduces the Markov decision contest, a new framework for reinforcement learning using pairwise preferences, and proves that stationary Markov policies are optimal and solvable efficiently.
The paper proposes a novel RL framework that naturally induces diverse agent behavior by reformulating the objective to treat the reward as a distribution over functions, making diversity a rational response to reward uncertainty.
This paper investigates whether adults' struggles with conjunctive causal rules persist when they have agency through active exploration.
Papers
Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?
Mandana Samiei, Eunice Yiu, Anthony GX-Chen, Dongyan Lin +4 more
This paper investigates whether adults' struggles with conjunctive causal rules persist when they have agency through active exploration.