4 papers
Offline Reinforcement Learning via Inverse Optimization
Ioannis Dimanidis, Tolga Ok, Peyman Mohajerin Esfahani
Inspired by the recent successes of Inverse Optimization (IO) across various application domains, we propose a novel offline Reinforcement Learning (ORL) algorithm for continuous s…
Control and Reinforcement Learning through the Lens of Optimization: An Algorithmic Perspective
Tolga Ok, Arman Sharifi Kolarijani, Mohamad Amin Sharif Kolarijani +1
The connection between control algorithms for Markov decision processes and optimization algorithms has been implicitly and explicitly exploited since the introduction of dynamic p…
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani +1
In this paper, we provide a novel algorithm for solving planning and learning problems of Markov decision processes. The proposed algorithm follows a policy iteration-type update b…
Scalable Kernel Inverse Optimization
Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro +1
Inverse Optimization (IO) is a framework for learning the unknown objective function of an expert decision-maker from a past dataset. In this paper, we extend the hypothesis class…