1 citations · 1 across the 5 of their papers we have counts for
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Entropy Maximization for Partially Observable Markov Decision Processes
Yagiz Savas, Michael Hibbard, Bo Wu +2
We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process (POMDP) subject to a constraint on the expected total…
On Minimizing Total Discounted Cost in MDPs Subject to Reachability Constraints
Yagiz Savas, Christos K. Verginis, Michael Hibbard +1
We study the synthesis of a policy in a Markov decision process (MDP) following which an agent reaches a target state in the MDP while minimizing its total discounted cost. The pro…
On the Complexity of Sequential Incentive Design
Yagiz Savas, Vijay Gupta, Ufuk Topcu
In many scenarios, a principal dynamically interacts with an agent and offers a sequence of incentives to align the agent's behavior with a desired objective. This paper focuses on…
Entropy-Regularized Stochastic Games
Yagiz Savas, Mohamadreza Ahmadi, Takashi Tanaka +1
In two-player zero-sum stochastic games, where two competing players make decisions under uncertainty, a pair of optimal strategies is traditionally described by Nash equilibrium a…
Incentive Design for Temporal Logic Objectives
Yagiz Savas, Vijay Gupta, Melkior Ornik +2
We study the problem of designing an optimal sequence of incentives that a principal should offer to an agent so that the agent's optimal behavior under the incentives realizes the…
Unpredictable Planning Under Partial Observability
Michael Hibbard, Yagiz Savas, Bo Wu +2
We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process (POMDP) subject to a constraint on the expected total…