no code implementations • 2 Nov 2023 • Tichakorn Wongpiromsarn, Mahsa Ghasemi, Murat Cubuktepe, Georgios Bakirtzis, Steven Carr, Mustafa O. Karabag, Cyrus Neary, Parham Gohari, Ufuk Topcu

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

no code implementations • 9 Sep 2023 • Cyrus Neary, Aryaman Singh Samyal, Christos Verginis, Murat Cubuktepe, Ufuk Topcu

We propose a framework for verifiable and compositional reinforcement learning (RL) in which a collection of RL subsystems, each of which learns to accomplish a separate subtask, are composed to achieve an overall task.

1 code implementation • 30 Dec 2022 • Franck Djeumou, Christian Ellis, Murat Cubuktepe, Craig Lennon, Ufuk Topcu

First, they require an excessive amount of data due to the information asymmetry between the expert and the learner.

no code implementations • 22 Dec 2022 • Aleksandar Krnjaic, Raul D. Steleac, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Andrew Wing Keung To, Kuan-Ho Lao, Murat Cubuktepe, Matthew Haley, Peter Börsting, Stefano V. Albrecht

We envision a warehouse in which dozens of mobile robots and human pickers work together to collect and deliver items within the warehouse.

1 code implementation • 30 Jun 2021 • Murat Cubuktepe, Nils Jansen, Sebastian Junges, Joost-Pieter Katoen, Ufuk Topcu

The parameter synthesis problem is to compute an instantiation of these unspecified parameters such that the resulting MDP satisfies the temporal logic specification.

no code implementations • 29 Jun 2021 • Franck Djeumou, Zhe Xu, Murat Cubuktepe, Ufuk Topcu

Specifically, we study a setting in which the agents move along the nodes of a graph, and the high-level task specifications for the swarm are expressed in a recently-proposed language called graph temporal logic (GTL).

1 code implementation • 7 Jun 2021 • Cyrus Neary, Christos Verginis, Murat Cubuktepe, Ufuk Topcu

We propose a framework for verifiable and compositional reinforcement learning (RL) in which a collection of RL subsystems, each of which learns to accomplish a separate subtask, are composed to achieve an overall task.

no code implementations • 28 May 2021 • Franck Djeumou, Murat Cubuktepe, Craig Lennon, Ufuk Topcu

Nevertheless, the resulting formulation is still nonconvex due to the intrinsic nonconvexity of the so-called forward problem, i. e., computing an optimal policy given a reward function, in POMDPs.

no code implementations • 4 May 2021 • Murat Cubuktepe, František Blahoudek, Ufuk Topcu

We develop an algorithm that solves this graph problem in time that is \emph{polynomial} in the number of agents, target locations, and size of the consumption Markov decision process.

no code implementations • 24 Sep 2020 • Murat Cubuktepe, Nils Jansen, Sebastian Junges, Ahmadreza Marandi, Marnix Suilen, Ufuk Topcu

(3) We linearize this dual problem and (4) solve the resulting finite linear program to obtain locally optimal solutions to the original problem.

no code implementations • 15 May 2019 • Murat Cubuktepe, Nils Jansen, Mohammed Alsiekh, Ufuk Topcu

We design the autonomy protocol to ensure that the resulting robot behavior satisfies given safety and performance specifications in probabilistic temporal logic.

no code implementations • 25 Apr 2019 • Bo Wu, Murat Cubuktepe, Suda Bharadwaj, Ufuk Topcu

In this paper, we consider deceiving adversaries with bounded rationality and in terms of expected rewards.

no code implementations • 28 Sep 2018 • Mohamadreza Ahmadi, Murat Cubuktepe, Nils Jansen, Sebastian Junges, Joost-Pieter Katoen, Ufuk Topcu

Then, the deception problem is to compute a strategy for the deceiver that minimizes the expected cost of deception against all strategies of the infiltrator.

no code implementations • 9 Jul 2018 • Yagiz Savas, Melkior Ornik, Murat Cubuktepe, Mustafa O. Karabag, Ufuk Topcu

Such a policy minimizes the predictability of the paths it generates, or dually, maximizes the exploration of different paths in an MDP while ensuring the satisfaction of a temporal logic specification.

no code implementations • 5 Mar 2018 • Murat Cubuktepe, Nils Jansen, Sebastian Junges, Joost-Pieter Katoen, Ufuk Topcu

This paper considers parametric Markov decision processes (pMDPs) whose transitions are equipped with affine functions over a finite set of parameters.

no code implementations • 28 Feb 2018 • Murat Cubuktepe, Ufuk Topcu

We develop a method for computing policies in Markov decision processes with risk-sensitive measures subject to temporal logic constraints.

no code implementations • 26 Oct 2016 • Nils Jansen, Murat Cubuktepe, Ufuk Topcu

We formalize synthesis of shared control protocols with correctness guarantees for temporal logic specifications.

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