6 citations · 15 across the 20 of their papers we have counts for
4 papers · 2 filters
Partially Observed Optimal Stochastic Control: Regularity, Optimality, Approximations, and Learning
Ali Devran Kara, Serdar Yuksel
In this review/tutorial article, we present recent progress on optimal control of partially observed Markov Decision Processes (POMDPs). We first present regularity and continuity…
Near Optimal Approximations and Finite Memory Policies for POMPDs with Continuous Spaces
Ali Devran Kara, Erhan Bayraktar, Serdar Yuksel
We study an approximation method for partially observed Markov decision processes (POMDPs) with continuous spaces. Belief MDP reduction, which has been the standard approach to stu…
Refined Bounds on Near Optimality Finite Window Policies in POMDPs and Their Reinforcement Learning
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
Finding optimal policies for Partially Observable Markov Decision Processes (POMDPs) is challenging due to their uncountable state spaces when transformed into fully observable Mar…
Learning with Linear Function Approximations in Mean-Field Control
Erhan Bayraktar, Ali D. Kara
The paper focuses on mean-field type multi-agent control problems with finite state and action spaces where the dynamics and cost structures are symmetric and homogeneous, and are…