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检索条件"主题词=Answer set Programming"

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People, Ideas, and the Path Ahead 24th

People, Ideas, and the Path Ahead

引用

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

作者： Balduccini, Marcello Saint Joseph’s University PhiladelphiaPA United States Elemental Cognition WiltonCT United States

ISBN: (纸本)9783030944780

While recent advances in machine learning have yielded impressive results, researchers, practitioners, and even companies are beginning to recognize that true artificial intelligence requires much more sophisticated reasoning capabilities. Knowledge representation and declarative programming are arguably in a premier position to aid in the achievement of such capabilities. In this paper, I reflect on people and ideas that have had a great influence on my view of knowledge representation and of declarative programming. Through these lenses, I will discuss what I consider to be some of the most important milestones in the evolution of the field over the past years. I will conclude my reflection with my take on what this may tell us about the path that lies ahead and about areas where research efforts may yield considerable benefits. © 2022, Springer Nature Switzerland AG.

关键词： answer set programming Declarative programming Knowledge representation Non-monotonic reasoning Practical applications

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Smart Devices and Large Scale Reasoning via ASP: Tools and Applications 24th

Smart Devices and Large Scale Reasoning via ASP: Tools and...

引用

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

作者： Reale, Kristian Calimeri, Francesco Leone, Nicola Ricca, Francesco Department of Mathematics and Computer Science University of Calabria Rende Italy DLVSystem L.T.D. Via della Resistenza 19/C Rende Italy

ISBN: (纸本)9783030944780

In the last few years, we have been witnessing the spread of computing devices getting smaller and smaller (e.g., Smartphones, Smart Devices, Raspberry, etc.), and the production and availability of data getting bigger and bigger. In this work we introduce DLV Large Scale (DLV-LS), a framework based on answer set programming (ASP) for performing declarative-based reasoning tasks over data-intensive applications, possibly on Smart Devices. The framework encompasses DLV Mobile Edition (DLV-ME), an ASP based solver for Android systems and Raspberry devices, and DLV Enterprise Edition (DLV-EE), an ASP-based platform, accessible by REST interfaces, for large-scale reasoning over Big Data, classical relational database systems, and NoSQL databases. DLV-LS enables Smart Devices to both locally perform reasoning over data generated by their own sensors and properly interact with DLV-EE when more computational power is needed for harder tasks, possibly over bigger centralized data. We present also a real-world application of DLV-LS;the use case consists of a tourist navigator that calculates the best routes and optimizes a tour of a tourist under custom-defined time constraints. © 2022, Springer Nature Switzerland AG.

关键词： answer set programming Large scale reasoning Smart devices

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ALPSolver: A Solver for Assumable Logic programming

ALPSolver: A Solver for Assumable Logic Programming

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Intelligent Computing and Human-Computer Interaction (ICHCI), International Conference on

作者： Zhizheng Zhang Jiayi Chen Huangdezhong Tian School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University) Ministry of Education China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

Assumable Logic programming (ALP), an extension of answer set programming (ASP), has been theoretically demonstrated to possess significant advantages in addressing problems involving incomplete information. Therefore, the development of ALP solvers is urgently needed to facilitate further research and applications. This paper proposes a solving algorithm named answer set Based View Search (ASBVS) and its optimization to compute the results of ALP programs. Based on this, the ALPSolver has been implemented and integrated into an online platform for public use. This paper experimentally validates the correctness of the solving algorithm and confirms the advantages of ALP in handling default information, indirect exception and abductive reasoning. Additionally, the experimental results demonstrate the effectiveness of the optimization algorithm, with a notable increase in efficiency as the problem scale increases.

关键词： Human computer interaction Logic programming Semantics Optimization methods answer set programming Syntactics Cognition Logic

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Handling Semantic Inconsistencies in Commonsense Knowledge for Autonomous Service Robots 14

Handling Semantic Inconsistencies in Commonsense Knowledge f...

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14th IEEE International Conference on Semantic Computing (ICSC)

作者： Jakob, Stefan Opfer, Stephan Jahl, Alexander Baraki, Harun Geihs, Kurt Univ Kassel Wilhelmshoher Allee 73 D-34121 Kassel Germany

ISBN: (纸本)9781728163321

The necessary amount of commonsense knowledge for autonomous domestic service robots is enormous and avoiding inconsistencies is consequently almost impossible. This is especially true for inconsistencies on a semantic level, that is, inconsistencies as interpreted by human beings where the properties of a concept may contradict each other. In contrast to Boolean algebra (A and A), these inconsistencies will not lead to a trivial solution like false, since they are not captured in a logic formalism. Instead, they will result in semantic contradictions when interpreting the solution. In order to tackle this problem, we propose a way to handle semantic inconsistencies, by utilising a commonsense knowledge database and implementing a dynamic knowledge base that is capable of resolving contradicting parts of knowledge. The applied non-monotonic reasoning mechanism is answer set programming, and ConceptNet5 is the commonsense knowledge database. Finally, we evaluate the performance of our approach and show its advantages in a complete household scenario.

关键词： answer set programming Cognitive robotics Commonsense reasoning Dynamic knowledge Semantic inconsistencies Service robots

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answer set Programs with Queries over Subprograms 14th

Answer Set Programs with Queries over Subprograms

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14th International Conference on Logic programming and Nonmonotonic Reasoning (LPNMR)

作者： Redl, Christoph Tech Univ Wien Inst Informat Syst Favoritenstr 9-11 A-1040 Vienna Austria

ISBN: (纸本)9783319616605;9783319616599

answer-set programming (ASP) is a declarative programming paradigm. In this paper we discuss two related restrictions and present a novel modeling technique to overcome them: (1) Meta-reasoning about the collection of answer sets of a program is in general only possible by external postprocessing, but not within the program. This prohibits the direct continuation of reasoning based on the answer to the query over a (sub) program's answer sets. (2) The saturation programming technique exploits the minimality criterion for answer sets of a disjunctive ASP program to solve co-NP-hard problems, which typically involve checking if a property holds for all objects in a certain domain. However, the technique is advanced and not easily applicable by average ASP users;moreover, the use of default-negation within saturation encodings is limited. In this paper, we present an approach which allows for brave and cautious query answering over normal subprograms within a disjunctive program in order to address restriction (1). The query answer is represented by a dedicated atom within each answer set of the overall program, which paves the way also for a more intuitive alternative to saturation encodings and allows also using default-negation within such encodings, which addresses restriction (2).

关键词： answer set programming Nonmonotonic reasoning FLP semantics Meta programming Saturation

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DYNAMIC MAGIC setS FOR DISJUNCTIVE DATALOG PROGRAMS

DYNAMIC MAGIC SETS FOR DISJUNCTIVE DATALOG PROGRAMS

引用

26th International Conference on Logic programming (ICLP)

作者： Alviano, Mario Univ Calabria Dept Math I-87036 Arcavacata Di Rende CS Italy

ISBN: (纸本)9783939897170

answer set programming (ASP) is a powerful formalism for knowledge representation and common sense reasoning that allows disjunction in rule heads and non monotonic negation in bodies. Magic sets are a technique for optimizing query answering over logic programs and have been originally defined for standard Datalog, that is, ASP without disjunction and negation. Essentially, the input program is rewritten in order to identify a subset of the program instantiation which is sufficient for answering the query. Dynamic Magic sets (DMS) are an extension of this technique to ASP. The optimization provided by DMS can be exploited also during the nondeterministic phase of ASP systems. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query (because of these assumptions). This allows for dynamic pruning of the search space, which may result in exponential performance gains. DMS has been implemented in the DLV system and experimental results confirm the effectiveness of the technique.

关键词： answer set programming decidability magic sets disjunctive logic programs

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External Computations and Interoperability in the New DLV Grounder 16th

External Computations and Interoperability in the New DLV Gr...

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16th International Conference of the Italian Association for Artificial Intelligence (AI*IA)

作者： Calimeri, Francesco Fusca, Davide Perri, Simona Zangari, Jessica Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy DLVSystem Srl Arcavacata Di Rende Italy

ISBN: (纸本)9783319701691;9783319701684

In this paper we focus on some of the most recent advancements in I-DLV, the new intelligent grounder of DLV;the system has been endowed with means aimed at easing the interoperability and integration with external systems and accommodating external source of computation and value invention within ASP programs. In particular, we describe here the support for external computations via explicit calls to Python scripts, and tools for the interoperability with both relational and graph databases.

关键词： Knowledge representation and reasoning answer set programming DLV Artificial Intelligence Deductive database systems Grounding Instantiation

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Decomposition-Based Job-Shop Scheduling with Constrained Clustering 24th

Decomposition-Based Job-Shop Scheduling with Constrained Cl...

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

作者： El-Kholany, Mohammed M. S. Schekotihin, Konstantin Gebser, Martin Alpen-Adria-Universität Klagenfurt Klagenfurt Austria Technische Universität Graz Graz Austria Cairo University Cairo Egypt

ISBN: (纸本)9783030944780

Scheduling is a crucial problem appearing in various domains, such as manufacturing, transportation, or healthcare, where the goal is to schedule given operations on available resources such that the operations are completed as soon as possible. Unfortunately, most scheduling problems cannot be solved efficiently, so that research on suitable approximation methods is of primary importance. This work introduces a novel approximation approach based on problem decomposition with data mining methodologies. We propose a constrained clustering algorithm to group operations into clusters, corresponding to time windows in which the operations must be scheduled. The decomposition process consists of two main phases. First, features are extracted, either from the problem itself or from solutions obtained by heuristic methods, to predict the execution sequence of operations on each resource. The second phase deploys our constrained clustering algorithm to assign each operation into a time window. We then schedule the operations by time windows using answer set programming. Evaluation results show that our proposed approach outperforms other heuristic schedulers in most cases, where incorporating features like Remaining Processing Time, Machine Load, and Earliest Starting Time significantly improves the solution quality. © 2022, Springer Nature Switzerland AG.

关键词： answer set programming Constrained clustering Job-shop Scheduling Problem Time windows

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Specification and execution of declarative policies for grid service selection

引用

European Conference on Web Services (ECOWS 2004)

作者： Marchi, M Mileo, A Provetti, A Univ Milan DSI I-20135 Milan Italy Univ Milan DICo I-20135 Milan Italy Univ Messina Dipartimento Fis I-98166 Messina Italy

ISBN: (纸本)3540232028

We describe a modified Grid architecture that allows to specify and enforce connection policies with preferences and integrity constraints. This is done by interposing a policy enforcement engine between a calling application and the relative client stubs. Such policies are conveniently expressed in the declarative policy specification language PPDL. In particular, PPDL allows expressing preferences on how to enforce constraints on action execution. PPDL policies are evaluated by translating them into a Logic Program with Ordered Disjunctions and calling the psmodels interpreter. We describe an experimental architecture that enforces connection policies by catching and filtering only service requests. The process is completely transparent to both client applications and Grid services. There are clear advantages in having the connection logic expressed declaratively and externally to applications.

关键词： grid services customization user preferences declarative policies answer set programming

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Multi-modal multi-agent path finding with optimal resource utilization 5th

Multi-modal multi-agent path finding with optimal resource u...

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5th International Conference on the Industry 4.0 Model for Advanced Manufacturing, AMP 2020

作者： Bogatarkan, Aysu Erdem, Esra Kleiner, Alexander Patoglu, Volkan Faculty of Engineering and Natural Sciences Sabancı University İstanbul Turkey Robert Bosch GmbH Corporate Research Stuttgart Germany

ISBN: (纸本)9783030462116

The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other. We study a general version of MAPF, called mMAPF, that involves further challenges, such as multi-modal transportation modes, a set of waypoints to visit for each agent, and consumption of different types of resources. We introduce a declarative method to solve mMAPF, using answer set programming that provides a flexible formal framework to address all these challenges while optimizing multiple objectives. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

关键词： answer set programming Autonomous warehouses Declarative problem solving Multi-agent Path Finding

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