activity
20182022
most citedNo-Regret Learning in Dynamic Stackelberg Games

1 citations · 1 across the 5 of their papers we have counts for

collaborators

11 papers

cs.GT20221 cited

No-Regret Learning in Dynamic Stackelberg Games

Niklas Lauffer, Mahsa Ghasemi, Abolfazl Hashemi +2

In a Stackelberg game, a leader commits to a randomized strategy, and a follower chooses their best strategy in response. We consider an extension of a standard Stackelberg game, c…

cs.AI2021

Deceptive Decision-Making Under Uncertainty

Yagiz Savas, Christos K. Verginis, Ufuk Topcu

We study the design of autonomous agents that are capable of deceiving outside observers about their intentions while carrying out tasks in stochastic, complex environments. By mod…

math.OC2021

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…

math.OC2021

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…

eess.SP2021

Physical-Layer Security via Distributed Beamforming in the Presence of Adversaries with Unknown Locations

Yagiz Savas, Abolfazl Hashemi, Abraham P. Vinod +2

We study the problem of securely communicating a sequence of information bits with a client in the presence of multiple adversaries at unknown locations in the environment. We assu…

math.OC2020

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…