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20182026
most citedEntropy Maximization for Markov Decision Processes Under Temporal Logic Constraints

28 citations · 67 across the 22 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.AI2023★ 7 cited

Formal Methods for Autonomous Systems

Tichakorn Wongpiromsarn, Mahsa Ghasemi, Murat Cubuktepe +6

Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main buil…

cs.GT2023

When Should a Leader Act Suboptimally? The Role of Inferability in Repeated Stackelberg Games

Mustafa O. Karabag, Sophia Smith, Negar Mehr +2

When interacting with other decision-making agents in non-adversarial scenarios, it is critical for an autonomous agent to have inferable behavior: The agent's actions must convey…

eess.SY2023

Simulator-Driven Deceptive Control via Path Integral Approach

Apurva Patil, Mustafa O. Karabag, Takashi Tanaka +1

We consider a setting where a supervisor delegates an agent to perform a certain control task, while the agent is incentivized to deviate from the given policy to achieve its own g…

eess.SY2023

Scenario-Game ADMM: A Parallelized Scenario-Based Solver for Stochastic Noncooperative Games

Jingqi Li, Chih-Yuan Chiu, Lasse Peters +6

Decision-making in multi-player games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochast…

cs.LG2023

On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples

Mustafa O. Karabag, Ufuk Topcu

Offline reinforcement learning (offline RL) considers problems where learning is performed using only previously collected samples and is helpful for the settings in which collecti…

cs.MA2023★ 3 cited

Differential Privacy in Cooperative Multiagent Planning

Bo Chen, Calvin Hawkins, Mustafa O. Karabag +3

Privacy-aware multiagent systems must protect agents' sensitive data while simultaneously ensuring that agents accomplish their shared objectives. Towards this goal, we propose a f…