28 citations · 31 across the 9 of their papers we have counts for
9 papers · 1 filter
Deceptive Planning for Resource Allocation
Shenghui Chen, Yagiz Savas, Mustafa O. Karabag +2
We consider a team of autonomous agents that navigate in an adversarial environment and aim to achieve a task by allocating their resources over a set of target locations. An adver…
On the Detection of Markov Decision Processes
Xiaoming Duan, Yagiz Savas, Rui Yan +2
We study the detection problem for a finite set of Markov decision processes (MDPs) where the MDPs have the same state and action spaces but possibly different probabilistic transi…
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…
Entropy Maximization for Markov Decision Processes Under Temporal Logic Constraints
Yagiz Savas, Melkior Ornik, Murat Cubuktepe +2
We study the problem of synthesizing a policy that maximizes the entropy of a Markov decision process (MDP) subject to a temporal logic constraint. Such a policy minimizes the pred…