activity
20132023
most citedThe First Reactive Synthesis Competition (SYNTCOMP 2014)

34 citations · 174 across the 26 of their papers we have counts for

collaborators

38 papers

cs.LO2023

Integer Programming with GCD Constraints

Rémy Defossez, Christoph Haase, Alessio Mansutti +1

We study the non-linear extension of integer programming with greatest common divisor constraints of the form , where and are linear polynomials, is a…

cs.AI2023

Formally-Sharp DAgger for MCTS: Lower-Latency Monte Carlo Tree Search using Data Aggregation with Formal Methods

Debraj Chakraborty, Damien Busatto-Gaston, Jean-François Raskin +1

We study how to efficiently combine formal methods, Monte Carlo Tree Search (MCTS), and deep learning in order to produce high-quality receding horizon policies in large Markov Dec…

cs.LG2022★ 1 cited

Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking

Dennis Gross, Thiago D. Simao, Nils Jansen +1

Deep Reinforcement Learning (RL) agents are susceptible to adversarial noise in their observations that can mislead their policies and decrease their performance. However, an adver…

cs.LO2022

The Geometry of Reachability in Continuous Vector Addition Systems with States

Shaull Almagor, Arka Ghosh, Tim Leys +1

We study the geometry of reachability sets of continuous vector addition systems with states (VASS). In particular we establish that they are almost Minkowski sums of convex cones…

cs.LG2022★ 3 cited

COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checking

Dennis Gross, Nils Jansen, Sebastian Junges +1

This paper presents COOL-MC, a tool that integrates state-of-the-art reinforcement learning (RL) and model checking. Specifically, the tool builds upon the OpenAI gym and the proba…

cs.LO2022★ 19 cited

The Reactive Synthesis Competition (SYNTCOMP): 2018-2021

Swen Jacobs, Guillermo A. Perez, Remco Abraham +22

We report on the last four editions of the reactive synthesis competition (SYNTCOMP 2018-2021). We briefly describe the evaluation scheme and the experimental setup of SYNTCOMP. Th…

cs.AI2021

Lecture Notes on Partially Known MDPs

Guillermo A. Perez

In these notes we will tackle the problem of finding optimal policies for Markov decision processes (MDPs) which are not fully known to us. Our intention is to slowly transition fr…

cs.FL2021

Active Learning of Sequential Transducers with Side Information about the Domain

Raphaël Berthon, Adrien Boiret, Guillermo A. Perez +1

Active learning is a setting in which a student queries a teacher, through membership and equivalence queries, in order to learn a language. Performance on these algorithms is ofte…

cs.FL2021

Continuous One-Counter Automata

Michael Blondin, Tim Leys, Filip Mazowiecki +2

We study the reachability problem for continuous one-counter automata, COCA for short. In such automata, transitions are guarded by upper and lower bound tests against the counter…

cs.LO2020★ 10 cited

The Complexity of Reachability in Parametric Markov Decision Processes

Sebastian Junges, Joost-Pieter Katoen, Guillermo A. Pérez +1

This article presents the complexity of reachability decision problems for parametric Markov decision processes (pMDPs), an extension to Markov decision processes (MDPs) where tran…

cs.LO2020

Revisiting Parameter Synthesis for One-Counter Automata

Guillermo A. Pérez, Ritam Raha

We study the (parameter) synthesis problem for one-counter automata with parameters. One-counter automata are obtained by extending classical finite-state automata with a counter w…

cs.LO2019★ 2 cited

The Extended HOA Format for Synthesis

Guillermo A. Perez

We propose a small extension to the Hanoi Omega-Automata format to define reactive-synthesis problems. Namely, we add a "controllable-AP" header item specifying the subset of atomi…

cs.GT2019

Partial Solvers for Generalized Parity Games

Véronique Bruyère, Guillermo A. Pérez, Jean-François Raskin +1

Parity games have been broadly studied in recent years for their applications to controller synthesis and verification. In practice, partial solvers for parity games that execute i…

cs.LO2019★ 7 cited

On the Complexity of Reachability in Parametric Markov Decision Processes

Tobias Winkler, Sebastian Junges, Guillermo A. Pérez +1

This paper studies parametric Markov decision processes (pMDPs), an extension to Markov decision processes (MDPs) where transitions probabilities are described by polynomials over…

cs.FL2019★ 4 cited

Alternating Weak Automata from Universal Trees

Laure Daviaud, Marcin Jurdziński, Karoliina Lehtinen

An improved translation from alternating parity automata on infinite words to alternating weak automata is given. The blow-up of the number of states is related to the size of the…

cs.LO2019

Coverability in 1-VASS with Disequality Tests

Shaull Almagor, Nathann Cohen, Guillermo A. Pérez +2

We study a class of reachability problems in weighted graphs with constraints on the accumulated weight of paths. The problems we study can equivalently be formulated in the model…

cs.GT2018

The Impatient May Use Limited Optimism to Minimize Regret

Michaël Cadilhac, Guillermo A. Pérez, Marie van den Bogaard

Discounted-sum games provide a formal model for the study of reinforcement learning, where the agent is enticed to get rewards early since later rewards are discounted. When the ag…

cs.FL2018

On the Complexity of Value Iteration

Nikhil Balaji, Stefan Kiefer, Petr Novotný +2

Value iteration is a fundamental algorithm for solving Markov Decision Processes (MDPs). It computes the maximal -step payoff by iterating times a recurrence equation which…

cs.FL2018

Weak Cost Register Automata are Still Powerful

Shaull Almagor, Michaël Cadilhac, Filip Mazowiecki +1

We consider one of the weakest variants of cost register automata over a tropical semiring, namely copyless cost register automata over with updates using and i…

cs.FL2018

When is Containment Decidable for Probabilistic Automata?

Laure Daviaud, Marcin Jurdziński, Ranko Lazić +3

The emptiness and containment problems for probabilistic automata are natural quantitative generalisations of the classical language emptiness and inclusion problems for Boolean au…

cs.AI2018

Learning-Based Mean-Payoff Optimization in an Unknown MDP under Omega-Regular Constraints

Jan Křetínský, Guillermo A. Pérez, Jean-François Raskin

We formalize the problem of maximizing the mean-payoff value with high probability while satisfying a parity objective in a Markov decision process (MDP) with unknown probabilistic…

cs.LO2017★ 30 cited

The 4th Reactive Synthesis Competition (SYNTCOMP 2017): Benchmarks, Participants & Results

Swen Jacobs, Nicolas Basset, Roderick Bloem +11

We report on the fourth reactive synthesis competition (SYNTCOMP 2017). We introduce two new benchmark classes that have been added to the SYNTCOMP library, and briefly describe th…

cs.LO2017

The Complexity of Graph-Based Reductions for Reachability in Markov Decision Processes

Stephane Le Roux, Guillermo A. Perez

We study the never-worse relation (NWR) for Markov decision processes with an infinite-horizon reachability objective. A state q is never worse than a state p if the maximal probab…

cs.FL2017

On Delay and Regret Determinization of Max-Plus Automata

Emmanuel Filiot, Ismaël Jecker, Nathan Lhote +2

Decidability of the determinization problem for weighted automata over the semiring , WA for short, is a long-standing open question. We propo…