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18th European Conference on Logics in Artificial Intelligence (JELIA)

作者： Yamada, Yuya Banbara, Mutsunori Inoue, Katsumi Schaub, Torsten Nagoya Univ Furo ChoChikusa Ku Nagoya 4648601 Japan Natl Inst Informat HitotsubashiChiyoda Ku Tokyo 1018430 Japan Univ Potsdam Bahn 2 D-14476 Potsdam Germany

ISBN: (纸本)9783031436185;9783031436192

We develop an approach called bounded combinatorial reconfiguration for solving combinatorial reconfiguration problems based on answer set programming. The general task is to study the solution spaces of source combinatorial problems and to decide whether or not there are sequences of feasible solutions that have special properties. The resulting recongo solver covers all metrics of the solver track in the most recent international competition on combinatorial reconfiguration (CoRe Challenge 2022). recongo ranked first in the shortest metric of the single-engine solvers track.

关键词： answer set programming Multi-shot ASP solving Combinatorial Reconfiguration Independent set Reconfiguration

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Declarative AI design in Unity using answer set programming

Declarative AI design in Unity using Answer Set Programming

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IEEE Conference on Games (CoG)

作者： Angilica, Denise Ianni, Giovambattista Pacenza, Francesco Univ Calabria DeMaCS Calabria Italy

ISBN: (数字)9781665459891

ISBN: (纸本)9781665459891

Declarative methods such as answer set programming show potential in cutting down development costs in commercial videogames and real-time applications in general. Many shortcomings, however, prevent their adoption, such as performance and integration gaps. In this work we illustrate our ThinkEngine, a framework in which a tight integration of declarative formalisms within the typical game development workflow is made possible in the context of the Unity game engine. ThinkEngine allows to wire declarative AI modules to the game logic and to move the computational load of reasoning tasks outside the main game loop using an hybrid deliberative/reactive architecture. In this paper, we illustrate the architecture of the ThinkEngine and its role both at design and run-time. Then we show how to program declarative modules in a proof-of-concept game, and report about performance and related work.

关键词： answer set programming Declarative Methods Game Design Knowledge Representation and Reasoning Unity

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User-Defined Smart Contracts Using answer set programming 34th

User-Defined Smart Contracts Using Answer Set Programming

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34th Australasian Joint Conference on Artificial Intelligence (AI)

作者： Purnell, Kevin Schwitter, Rolf Macquarie Univ Sydney NSW Australia

ISBN: (纸本)9783030975463;9783030975456

We present a novel approach to the creation of smart contracts that takes an existing legal document and allows it to be incrementally elaborated into a tested smart contract by domain experts. Smart contracts are currently built with compiled imperative languages, and suffer from lack of agility, elevated risks from errors and security flaws, and high development costs. This paper describes a smart editor that uses a declarative language (answer set programming (ASP)) to represent the business logic of legal documents. The document is incrementally elaborated in a fixed sequence of steps beginning with an ontology discovery step that identifies the explicit and implicit artefacts and applicable constraints. This information is used to generate ASP representations which provide the foundation required for modelling the legal logic. Furthermore, we have achieved the verbalisation of rules built during modelling, and have developed a method of representing artefacts visually which allows logic modelling, model validation and program verification to be visual. During these steps, the original legal document is enhanced with additional embedded information, which results in a tested executable ASP program which can then be used as a smart contract if modifications are made to the blockchain smart contract infrastructure.

关键词： answer set programming Legal Logic Model Validation Ontology Smart Contract Verbalisation Visualisation

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Deep Learning for the Generation of Heuristics in answer set programming: A Case Study of Graph Coloring 16th

Deep Learning for the Generation of Heuristics in Answer Set...

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16th International Conference on Logic programming and Non-Monotonic Reasoning (LPNMR)

作者： Dodaro, Carmine Ilardi, Davide Oneto, Luca Ricca, Francesco Univ Calabria DeMaCS Arcavacata Di Rende Italy Univ Genoa DIBRIS Genoa Italy

ISBN: (纸本)9783031157073;9783031157066

answer set programming (ASP) is a well-established declarative AI formalism for knowledge representation and reasoning. ASP systems were successfully applied to both industrial and academic problems. Nonetheless, their performance can be improved by embedding domain-specific heuristics into their solving process. However, the development of domain-specific heuristics often requires both a deep knowledge of the domain at hand and a good understanding of the fundamental working principles of the ASP solvers. In this paper, we investigate the use of deep learning techniques to automatically generate domain-specific heuristics for ASP solvers targeting the well-known graph coloring problem. Empirical results show that the idea is promising: the performance of the ASP solver WASP can be improved.

关键词： answer set programming deep learning heuristics graph coloring

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Modal Logic S5 in answer set programming with Lazy Creation of Worlds 16th

Modal Logic S5 in Answer Set Programming with Lazy Creation ...

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16th International Conference on Logic programming and Non-Monotonic Reasoning (LPNMR)

作者： Alviano, Mario Batsakis, Sotiris Baryannis, George Univ Calabria Arcavacata Di Rende Italy Tech Univ Crete Iraklion Greece Univ Huddersfield Sch Comp & Engn Huddersfield W Yorkshire England

ISBN: (纸本)9783031157073;9783031157066

Modal logic S5 is used extensively for representing knowledge that includes statements about necessity and possibility, owing to its simplicity in handling chained modal operators. Significant research effort has been devoted in developing efficient reasoning mechanisms over complex S5 formulas, resulting in various solvers taking advantage of the boolean satisfiability problem (SAT). Among them, the most performant solver implements a heuristic for identifying worlds that can be merged, hence reducing the size of SAT instances to be checked. Recently, answer set programming (ASP) has also been considered, and different ASP encodings were proposed and tested, reaching state-of-the-art performance. In particular, a heuristic for identifying the propositional atoms that are relevant in every world resulted in a performance gain in previous experiments. This work addresses the open question of whether the aforementioned two heuristics can be combined, as well as possibly enabling lazy instantiation of the resulting encodings, and what their potential impact is on the performance of the ASP-based solver. Experiments show that lazy creation of worlds provides some further performance gain to the ASP-based solver on the tested instances.

关键词： Modal Logic S5 answer set programming

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State Transition in Multi-agent Epistemic Domains Using answer set programming 16th

State Transition in Multi-agent Epistemic Domains Using Answ...

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16th International Conference on Logic programming and Non-Monotonic Reasoning (LPNMR)

作者： Izmirlioglu, Yusuf Pham, Loc Son, Tran Cao Pontelli, Enrico New Mexico State Univ Las Cruces NM 88003 USA

ISBN: (纸本)9783031157073;9783031157066

In this paper we develop a state transition function for partially observable multi-agent epistemic domains and implement it using answer set programming (ASP). The transition function computes the next state upon an occurrence of a single action. Thus it can be used as a module in epistemic planners. Our transition function incorporates ontic, sensing and announcement actions and allows for arbitrary nested belief formulae and general common knowledge. A novel feature of our model is that upon an action occurrence, an observing agent corrects his (possibly wrong) initial beliefs about action precondition and his observability. By examples, we show that this step is necessary for robust state transition. We establish some properties of our state transition function regarding its soundness in updating beliefs of agents consistent with their observability.

关键词： answer set programming Multi-agent systems Epistemic planning State transition

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Planning with Incomplete Information in Quantified answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2021年第5期21卷 663-679页

作者： Fandinno, Jorge Laferriere, Francois Romero, Javier Schaub, Torsten Son, Tran Cao Omaha State Univ Omaha NE 68182 USA Univ Potsdam Potsdam Germany New Mexico State Univ Las Cruces NM 88003 USA

We present a general approach to planning with incomplete information in answer set programming (ASP). More precisely, we consider the problems of conformant and conditional planning with sensing actions and assumptions. We represent planning problems using a simple formalism where logic programs describe the transition function between states, the initial states and the goal states. For solving planning problems, we use Quantified answer set programming (QASP), an extension of ASP with existential and universal quantifiers over atoms that is analogous to Quantified Boolean Formulas (QBFs). We define the language of quantified logic programs and use it to represent the solutions different variants of conformant and conditional planning. On the practical side, we present a translation-based QASP solver that converts quantified logic programs into QBFs and then executes a QBF solver, and we evaluate experimentally the approach on conformant and conditional planning benchmarks.

关键词： answer set programming planning quantified logics

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A Compact answer set programming Encoding of Multi-Agent Pathfinding

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IEEE ACCESS 2021年 9卷 26886-26901页

作者： Gomez, Rodrigo N. Hernandez, Carlos Baier, Jorge A. Pontificia Univ Catolica Chile Dept Ciencia Computac Santiago 7820244 Chile Univ Andres Bello Dept Ciencias Ingn Santiago 7500000 Chile Inst Milenio Fundamentos Ios Datos Santiago 7820244 Chile

Multi-agent pathfinding (MAPF) is the problem of finding k non-colliding paths connecting k given initial positions with k given goal positions on a given map. In its sum-of-costs variant, the total number of moves and wait actions performed by agents before they definitely reach the goal is minimized. Not surprisingly, since MAPF is combinatorial, a number of compilations to Boolean Satisfiability (SAT) and answer set programming (ASP) exist. In this article, we describe in detail the first family of compilations to ASP that solve sum-of-costs MAPF over 4-connected grids. Compared to existing ASP compilations, a distinguishing feature of our compilation is that the number of total clauses (after grounding) grow linearly with the number of agents, while existing compilations grow quadratically. In addition, the optimization objective is such that its size after grounding does not depend on the size of the grid. In our experimental evaluation, we show that our approach outperforms search-based sum-of-costs MAPF solvers when grids are congested with agents. We also show that our approach is competitive with a SAT-based approach when follow conflicts are taken into account. We also explore the potential of our solver when finding makespan-optimal solutions, in which makespan is minimized first and then cost is minimized. Our results show that makespan-optimal solutions are slightly suboptimal in most benchmarks. Moreover, our MAPF solver, when run in that mode, is faster and scales better.

关键词： answer set programming multi-agent pathfinding

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Towards Dynamic Consistency Checking in Goal-Directed Predicate answer set programming 24th

Towards Dynamic Consistency Checking in Goal-Directed Predi...

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24th International Conference on Practical Aspects of Declarative Languages, PADL 2022

作者： Arias, Joaquín Carro, Manuel Gupta, Gopal CETINIA Universidad Rey Juan Carlos Madrid Spain Universidad Politécnica de Madrid Madrid Spain IMDEA Software Institute Madrid Spain University of Texas at Dallas Richardson United States

ISBN: (纸本)9783030944780

Goal-directed evaluation of answer set Programs is gaining traction thanks to its amenability to create AI systems that can, due to the evaluation mechanism used, generate explanations and justifications. s(CASP) is one of these systems and has been already used to write reasoning systems in several fields. It provides enhanced expressiveness w.r.t. other ASP systems due to its ability to use constraints, data structures, and unbound variables natively. However, the performance of existing s(CASP) implementations is not on par with other ASP systems: model consistency is checked once models have been generated, in keeping with the generate-and-test paradigm. In this work, we present a variation of the top-down evaluation strategy, termed Dynamic Consistency Checking, which interleaves model generation and consistency checking. This makes it possible to determine when a literal is not compatible with the denials associated to the global constraints in the program, prune the current execution branch, and choose a different alternative. This strategy is specially (but not exclusively) relevant in problems with a high combinatorial component. We have experimentally observed speedups of up to 90 × w.r.t. the standard versions of s(CASP). © 2022, Springer Nature Switzerland AG.

关键词： answer set programming Constraints Dynamic consistency checking Goal-directed evaluation

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xASP: An Explanation Generation System for answer set programming 16th

xASP: An Explanation Generation System for Answer Set Progra...

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16th International Conference on Logic programming and Non-Monotonic Reasoning (LPNMR)

作者： Trieu, Ly Ly Son, Tran Cao Balduccini, Marcello New Mexico State Univ Las Cruces NM 88003 USA St Josephs Univ Philadelphia PA 19131 USA

ISBN: (纸本)9783031157073;9783031157066

In this paper, we present a system, called xASP, for generating explanations that explain why an atom belongs to (or does not belong to) an answer set of a given program. The system can generate all possible explanations for a query without the need to simplify the program before computing explanations, i.e., it works with non-ground programs. These properties distinguish xASP from existing systems such as xClingo, DiscASP, exp(ASP(c)), and s(CASP), which also generate explanations for queries to logic programs under the answer set semantics but simplify and ground the programs (the three systems xClingo, DiscASP, exp(ASP(c))) or do not always generate all possible explanations (the system s(CASP)). In addition, the output of xASP is insensitive to syntactic variations such as the order conditions and the order of rules, which is also different from the output of s(CASP).

关键词： Explainable AI Logic programming answer set programming

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