2 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
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…
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,…
Act to Reason: A Dynamic Game Theoretical Model of Driving
Cevahir Köprülü, Yıldıray Yıldız
The focus of this paper is to propose a driver model that incorporates human reasoning levels as actions during interactions with other drivers. Different from earlier work using g…