Guillermo A. Perez

research

∙ 08/25/2023

Integer Programming with GCD Constraints

We study the non-linear extension of integer programming with greatest c...

0 Rémy Defossez, et al. ∙

research

∙ 08/15/2023

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

We study how to efficiently combine formal methods, Monte Carlo Tree Sea...

0 Debraj Chakraborty, et al. ∙

research

∙ 05/16/2023

Bi-Objective Lexicographic Optimization in Markov Decision Processes with Related Objectives

We consider lexicographic bi-objective problems on Markov Decision Proce...

0 Damien Busatto-Gaston, et al. ∙

research

∙ 05/09/2023

Graph-Based Reductions for Parametric and Weighted MDPs

We study the complexity of reductions for weighted reachability in param...

0 Kasper Engelen, et al. ∙

research

∙ 03/22/2023

Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees

Although deep reinforcement learning (DRL) has many success stories, the...

0 Florent Delgrange, et al. ∙

research

∙ 03/07/2023

The Temporal Logic Synthesis Format TLSF v1.2

We present an extension of the Temporal Logic Synthesis Format (TLSF). T...

0 Swen Jacobs, et al. ∙

research

∙ 03/06/2023

The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models

Partially Observable Markov Decision Processes (POMDPs) are useful tools...

0 Raphaël Avalos, et al. ∙

research

∙ 12/10/2022

Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking

Deep Reinforcement Learning (RL) agents are susceptible to adversarial n...

0 Dennis Gross, et al. ∙

research

∙ 10/03/2022

The Geometry of Reachability in Continuous Vector Addition Systems with States

We study the geometry of reachability sets of continuous vector addition...

0 Shaull Almagor, et al. ∙

research

∙ 09/15/2022

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

This paper presents COOL-MC, a tool that integrates state-of-the-art rei...

0 Dennis Gross, et al. ∙

research

∙ 06/01/2022

The Reactive Synthesis Competition (SYNTCOMP): 2018-2021

We report on the last four editions of the reactive synthesis competitio...

0 Swen Jacobs, et al. ∙

research

∙ 04/12/2022

Acacia-Bonsai: A Modern Implementation of Downset-Based LTL Realizability

We describe our implementation of downset-manipulating algorithms used t...

0 Michaël Cadilhac, et al. ∙

research

∙ 12/17/2021

Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report)

We consider the challenge of policy simplification and verification in t...

0 Florent Delgrange, et al. ∙

research

∙ 12/06/2021

Lecture Notes on Partially Known MDPs

In these notes we will tackle the problem of finding optimal policies fo...

0 Guillermo A. Perez, et al. ∙

research

∙ 04/23/2021

Active Learning of Sequential Transducers with Side Information about the Domain

Active learning is a setting in which a student queries a teacher, throu...

0 Raphaël Berthon, et al. ∙

research

∙ 01/28/2021

Continuous One-Counter Automata

We study the reachability problem for continuous one-counter automata, C...

0 Michael Blondin, et al. ∙

research

∙ 09/28/2020

The Complexity of Reachability in Parametric Markov Decision Processes

This article presents the complexity of reachability decision problems f...

0 Sebastian Junges, et al. ∙

research

∙ 05/19/2020

Safe Learning for Near Optimal Scheduling

In this paper, we investigate the combination of synthesis techniques an...

0 Gilles Geeraerts, et al. ∙

research

∙ 05/12/2020

Robustness Verification for Classifier Ensembles

We give a formal verification procedure that decides whether a classifie...

0 Dennis Gross, et al. ∙

research

∙ 05/03/2020

Revisiting Synthesis for One-Counter Automata

One-counter automata are obtained by extending classical finite-state au...

0 Guillermo A. Perez, et al. ∙

research

∙ 04/06/2020

Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework

In this paper we cast neural networks defined on graphs as message-passi...

0 Floris Geerts, et al. ∙

research

∙ 12/12/2019

The Extended HOA Format for Synthesis

We propose a small extension to the Hanoi Omega-Automata format to defin...

0 Guillermo A. Perez, et al. ∙

research

∙ 07/16/2019

Partial Solvers for Generalized Parity Games

Parity games have been broadly studied in recent years for their applica...

0 Véronique Bruyère, et al. ∙

research

∙ 04/02/2019

On the Complexity of Reachability in Parametric Markov Decision Processes

This paper studies parametric Markov decision processes (pMDPs), an exte...

0 Tobias Winkler, et al. ∙

research

∙ 02/18/2019

Coverability in 1-VASS with Disequality Tests

We show that the control-state reachability problem for one-dimensional ...

0 Shaull Almagor, et al. ∙

research

∙ 11/17/2018

The Impatient May Use Limited Optimism to Minimize Regret

Discounted-sum games provide a formal model for the study of reinforceme...

0 Michaël Cadilhac, et al. ∙

research

∙ 07/13/2018

On the Complexity of Value Iteration

Value iteration is a fundamental algorithm for solving Markov Decision P...

0 Nikhil Balaji, et al. ∙

research

∙ 07/13/2018

On the Complexity of Iterative Tropical Computation with Applications to Markov Decision Processes

We study the complexity of evaluating powered functions implemented by s...

0 Nikhil Balaji, et al. ∙

research

∙ 04/24/2018

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

We formalize the problem of maximizing the mean-payoff value with high p...

0 Jan Křetínský, et al. ∙

research

∙ 11/29/2017

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

We report on the fourth reactive synthesis competition (SYNTCOMP 2017). ...

0 Swen Jacobs, et al. ∙

research

∙ 10/22/2017

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

We study the never-worse relation (NWR) for Markov decision processes wi...

0 Stephane Le Roux, et al. ∙

research

∙ 11/26/2016

Optimizing Expectation with Guarantees in POMDPs (Technical Report)

A standard objective in partially-observable Markov decision processes (...

0 Krishnendu Chatterjee, et al. ∙

Guillermo A. Perez

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