arXiv subjects

Pablo F. Castro

Publications and source records attributed to Pablo F. Castro.

10 recordsLinked to original sources

arXiv2026

Satisfiability for Knowing How over Linear Plans is NP-complete

We study the satisfiability problem for a modal logic expressing knowing-how assertions, which captures an agent's ability to achieve a given goal under the standard semantics based on linear plans. Our main result shows that satisfiability of knowing-how formulas is NP-complete, improving previously known complexity bounds. The proof proceeds via a translation into modal logic S5, an instrumental tool for addressing a variety of problems in knowledge representation.

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arXiv2026

Solving Fuzzy Satisfiability via Mixed-Integer Non-Linear Programming

This paper introduces SATFuL, a SAT solver for fuzzy logics. In contrast to the Boolean case, for which numerous SAT solvers exist, the SAT problem for fuzzy logics has attracted less attention, even though these tools have interesting applications. Unlike existing SAT solvers for fuzzy logics, SATFuL uses MINLP (Mixed Integer Non-Linear Programming) solvers to check the satisfiability of fuzzy formulas. This approach offers certain benefits; for instance, our tool can handle all major variations of fuzzy propositional logic, whereas other fuzzy solvers are usually tailored to specific versions of fuzzy logic. We conduct some experiments and demonstrate that the performance of our tool is comparable with state-of-the-art fuzzy solvers for Lukasiewicz logic, and outperforms available solvers for Product logic. The approach is sound and complete and can be easily extended to accommodate new fuzzy operators.

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arXiv2025

Polytopal Stochastic Games

In this paper we introduce polytopal stochastic games, an extension of two-player, zero-sum, turn-based stochastic games, in which we may have uncertainty over the transition probabilities. In these games the uncertainty over the probabilities distributions is captured via linear (in)equalities whose space of solutions forms a polytope. We give a formal definition of these games and prove their basic properties: determinacy and existence of optimal memoryless and deterministic strategies. We do this for reachability and different types of reward objectives and show that the solution exists in a finite representation of the game. We also state that the corresponding decision problems are in the intersection of NP and coNP. We motivate the use of polytopal stochastic games via a simple example. Finally, we report some experiments we performed with a prototype tool.

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arXiv2025

Bounded Synthesis of Synchronized Distributed Models from Lightweight Specifications

We present an approach to automatically synthesize synchronized models from lightweight formal specifications. Our approach takes as input a specification of a distributed system along with a global linear time constraint, which must be fulfilled by the interaction of the system's components. It produces executable models for the component specifications (in the style of Promela language) whose concurrent execution satisfies the global constraint. The component specifications consist of a collection of actions described by means of pre and post conditions together with first-order relational formulas prescribing their behavior. We use the Alloy Analyzer to encode the component specifications and enumerate their potential implementations up to some bound, whose concurrent composition is model checked against the global property. Even though this approach is sound and complete up to the selected bound, it is impractical as the number of candidate implementations grows exponentially. To address this, we propose an algorithm that uses batches of counterexamples to prune the solution space, it has two main phases: exploration, the algorithm collects a batch of counterexamples, and exploitation, where this knowledge is used to speed up the search. The approach is sound, while its completeness depends on the batches used. We present a prototype tool, describe some experiments, and compare it with related approaches.

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arXiv2023

Quantifying Masking Fault-Tolerance via Fair Stochastic Games

We introduce a formal notion of masking fault-tolerance between probabilistic transition systems using stochastic games. These games are inspired in bisimulation games, but they also take into account the possible faulty behavior of systems. When no faults are present, these games boil down to probabilistic bisimulation games. Since these games could be infinite, we propose a symbolic way of representing them so that they can be solved in polynomial time. In particular, we use this notion of masking to quantify the level of masking fault-tolerance exhibited by almost-sure failing systems, i.e., those systems that eventually fail with probability 1. The level of masking fault-tolerance of almost-sure failing systems can be calculated by solving a collection of functional equations. We produce this metric in a setting in which one of the player behaves in a strong fair way (mimicking the idea of fair environments).

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arXiv2022

A Stochastic Game Approach to Masking Fault-Tolerance: Bisimulation and Quantification

We introduce a formal notion of masking fault-tolerance between probabilistic transition systems based on a variant of probabilistic bisimulation (named masking simulation). We also provide the corresponding probabilistic game characterization. Even though these games could be infinite, we propose a symbolic way of representing them, such that it can be decided in polynomial time if there is a masking simulation between two probabilistic transition systems. We use this notion of masking to quantify the level of masking fault-tolerance exhibited by almost-sure failing systems, i.e., those systems that eventually fail with probability 1. The level of masking fault-tolerance of almost-sure failing systems can be calculated by solving a collection of functional equations. We produce this metric in a setting in which the minimizing player behaves in a strong fair way (mimicking the idea of fair environments), and limit our study to memoryless strategies due to the infinite nature of the game. We implemented these ideas in a prototype tool, and performed an experimental evaluation.

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arXiv2022

Playing Against Fair Adversaries in Stochastic Games with Total Rewards

We investigate zero-sum turn-based two-player stochastic games in which the objective of one player is to maximize the amount of rewards obtained during a play, while the other aims at minimizing it. We focus on games in which the minimizer plays in a fair way. We believe that these kinds of games enjoy interesting applications in software verification, where the maximizer plays the role of a system intending to maximize the number of "milestones" achieved, and the minimizer represents the behavior of some uncooperative but yet fair environment. Normally, to study total reward properties, games are requested to be stopping (i.e., they reach a terminal state with probability 1). We relax the property to request that the game is stopping only under a fair minimizing player. We prove that these games are determined, i.e., each state of the game has a value defined. Furthermore, we show that both players have memoryless and deterministic optimal strategies, and the game value can be computed by approximating the greatest-fixed point of a set of functional equations. We implemented our approach in a prototype tool, and evaluated it on an illustrating example and an Unmanned Aerial Vehicle case study.

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arXiv2019

An Algebraic Approach for Action Based Default Reasoning

Often, we assume that an action is permitted simply because it is not explicitly forbidden; or, similarly, that an action is forbidden simply because it is not explicitly permitted. This kind of assumptions appear, e.g., in autonomous computing systems where decisions must be taken in the presence of an incomplete set of norms regulating a particular scenario. Combining default and deontic reasoning over actions allows us to formally reason about such assumptions. With this in mind, we propose a logical formalism for default reasoning over a deontic action logic. The novelty of our approach is twofold. First, our formalism for default reasoning deals with actions and action operators, and it is based on the deontic action logic originally proposed by Segerberg. Second, inspired by Segerberg's approach, we use tools coming from the theory of Boolean Algebra. These tools allow us to extend Segerberg's algebraic completeness result to the setting of Default Logics.

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arXiv2018

Measuring Masking Fault-Tolerance

In this paper we introduce a notion of fault-tolerance distance between labeled transition systems. Intuitively, this notion of distance measures the degree of fault-tolerance exhibited by a candidate system. In practice, there are different kinds of fault-tolerance, here we restrict ourselves to the analysis of masking fault-tolerance because it is often a highly desirable goal for critical systems. Roughly speaking, a system is masking fault-tolerant when it is able to completely mask the faults, not allowing these faults to have any observable consequences for the users. We capture masking fault-tolerance via a simulation relation, which is accompanied by a corresponding game characterization. We enrich the resulting games with quantitative objectives to define the notion of masking fault-tolerance distance. Furthermore, we investigate the basic properties of this notion of masking distance, and we prove that it is a directed pseudo metric. We have implemented our approach in a prototype tool that automatically compute the masking distance between a nominal system and a fault-tolerant version of it. We have used this tool to measure the masking tolerance of multiple instances of several case studies

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arXiv2014

Automated Reasoning over Deontic Action Logics with Finite Vocabularies

In this paper we investigate further the tableaux system for a deontic action logic we presented in previous work. This tableaux system uses atoms (of a given boolean algebra of action terms) as labels of formulae, this allows us to embrace parallel execution of actions and action complement, two action operators that may present difficulties in their treatment. One of the restrictions of this logic is that it uses vocabularies with a finite number of actions. In this article we prove that this restriction does not affect the coherence of the deduction system; in other words, we prove that the system is complete with respect to language extension. We also study the computational complexity of this extended deductive framework and we prove that the complexity of this system is in PSPACE, which is an improvement with respect to related systems.

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