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cs.LG2024
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations
Cevahir Koprulu, Po-han Li, Tianyu Qiu +5
Many continuous control problems can be formulated as sparse-reward reinforcement learning (RL) tasks. In principle, online RL methods can automatically explore the state space to…
cs.LG2023
Reward-Machine-Guided, Self-Paced Reinforcement Learning
Cevahir Koprulu, Ufuk Topcu
Self-paced reinforcement learning (RL) aims to improve the data efficiency of learning by automatically creating sequences, namely curricula, of probability distributions over cont…
cs.LG2022★ 2 cited
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics
Christos Verginis, Cevahir Koprulu, Sandeep Chinchali +1
We study the problem of reinforcement learning for a task encoded by a reward machine. The task is defined over a set of properties in the environment, called atomic propositions,…