Recently forms of abstraction have been proposed for bothlogic programs (LPs) under the answer set semantics (ASP) and for the related formalism of assumption-based argumentation (ABA), e.g., via clustering of atoms ...
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ISBN:
(纸本)9783031742088;9783031742095
Recently forms of abstraction have been proposed for bothlogic programs (LPs) under the answer set semantics (ASP) and for the related formalism of assumption-based argumentation (ABA), e.g., via clustering of atoms or assumptions, in order to simplify a given LP or ABA framework. In both approaches after clustering the original answer sets and assumption sets are over-approximated, withthe aim of avoiding spuriousness. In contrast, in ASP a given LP is syntactically modified to achieve over-approximation, while on ABA the framework is minimally modified and the semantics is abstracted. In this work we follow the latter approach and provide a novel semantical abstraction for LPs and for ABA frameworks corresponding to LPs.
Traditionally, in the argumentation theory literature structured arguments are constructed from rules interpretations aiming to build well-supported deductive evidence. Different from other approaches, we emphasize th...
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ISBN:
(纸本)9783031742088;9783031742095
Traditionally, in the argumentation theory literature structured arguments are constructed from rules interpretations aiming to build well-supported deductive evidence. Different from other approaches, we emphasize the role of investigating general frameworks that can also provide a consistent and well-defined justification for a conclusion that cannot be inferred and there is certainty about it, which we call here NAF-arguments, which have been less explored in the formal argumentation theory, despite its potential use in practical applications for building nuanced well-structured explanations and justifications. this article introduces the so-called semantic argumentation guaranteeing well-known principles for quality in structured argumentation, and withthe ability to generate two types of arguments, those where the conclusion atoms are semantically interpreted as true, and those where the conclusion is assumed to be false, we call them here semantic and NAF-arguments respectively. this framework is defined on the set of all logic programs in terms of rewriting systems based on a confluent set of transformation rules, the so-called Confluent logicprogramming Systems, making this approach a general framework. Additionally, we introduce a method for building such arguments using the program's strata through partial interpretations. We implement our framework named semantic argumentation solver available open source.
We develop a computational approach to Metric Answer Set programming (ASP) to allow for expressing quantitative temporal constrains, like durations and deadlines. A central challenge is to maintain scalability when de...
ISBN:
(纸本)9783031742088;9783031742095
We develop a computational approach to Metric Answer Set programming (ASP) to allow for expressing quantitative temporal constrains, like durations and deadlines. A central challenge is to maintain scalability when dealing with fine-grained timing constraints, which can significantly exacerbate ASP's grounding bottleneck. To address this issue, we leverage extensions of ASP with difference constraints, a simplified form of linear constraints, to handle time-related aspects externally. Our approach effectively decouples metric ASP from the granularity of time, resulting in a solution that is unaffected by time precision.
Weather forecasting is important for saving lives, protecting property, and supporting economic activities. It provides timely warnings for severe weather, improves agricultural planning, and aids in disaster manageme...
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ISBN:
(纸本)9783031742088;9783031742095
Weather forecasting is important for saving lives, protecting property, and supporting economic activities. It provides timely warnings for severe weather, improves agricultural planning, and aids in disaster management. Neural networks and deep learning methods can achieve impressive accuracy in weather prediction, but their black-box nature lacks in explainability. To address this limitation, we investigated the potential of FastLAS, an Inductive logicprogramming (ILP) framework, to produce reliable and, more important, explainable weather predictions. FastLAS learns ASP programs whose syntax and structural semantics resemble natural human language, making them easily understandable and interpretable by humans. the supportedness of stable models allows a clear explanation of the predictions. Our empirical evaluation on data from an Italian weather forecasting center shows that our approach is capable of learning predictive models from small dataset (a few samples instead of the thousands needed by neural networks) achieving an accuracy higher than statistical machine learning base lines.
Supply chains exhibit complex dynamics and intricate dependencies among their components, whose understanding is crucial for addressing the challenges highlighted by recent global disruptions. this paper presents a no...
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ISBN:
(纸本)9783031742088;9783031742095
Supply chains exhibit complex dynamics and intricate dependencies among their components, whose understanding is crucial for addressing the challenges highlighted by recent global disruptions. this paper presents a novel multi-agent system designed to simulate supply chains, linking reasoning about dynamic domains and multi-agent systems to reasoning about the high-level primitives of the NIST CPS Framework. Our approach synthesizes existing research on supply chain formalization and integrates these insights with multi-agent techniques, employing a declarative approach to model interactions and dependencies. the simulation framework models a set of autonomous agents within a partially observable environment, and whose interactions are dictated by contracts. the system dynamically reconciles agents' actions, assessing their feasibility and consequences. Based on the state of the domain, the simulation framework also draws conclusions about the high-level notions of requirements and concerns of the NIST CPS Framework, which provide a uniform and domain-agnostic vocabulary for the understanding of such complex systems as supply chains.
the proceedings contain 25 papers. the special focus in this conference is on logicprogramming and nonmonotonicreasoning. the topics include: Founded World Views with Autoepistemic Equilibrium logic;towards Dynamic ...
ISBN:
(纸本)9783030205270
the proceedings contain 25 papers. the special focus in this conference is on logicprogramming and nonmonotonicreasoning. the topics include: Founded World Views with Autoepistemic Equilibrium logic;towards Dynamic Answer Set programming over Finite Traces;a Sequent-Type Calculus for three-Valued Default logic, Or: Tweety Meets Quartum Non Datur;diagnosing Data Pipeline Failures Using Action Languages;repair-Based Degrees of Database Inconsistency;elect: An Inconsistency Handling Approach for Partially Preordered Lightweight Ontologies;Elaboration Tolerant Representation of Markov Decision Process via Decision-theoretic Extension of Probabilistic Action Language pBC+;Evaluation of Disjunctive Programs in WASP;telingo = ASP + Time;Telco Network Inventory Validation with NoHR;verifying Strong Equivalence of Programs in the Input Language of gringo;the Return of xorro;Degrees of Laziness in Grounding: Effects of Lazy-Grounding Strategies on ASP Solving;Enhancing DLV for Large-Scale reasoning;Pruning External Minimality Checking for ASP Using Semantic Dependencies;declarative Local Search for Predicate logic;An ASP-Based Framework for the Manipulation of Articulated Objects Using Dual-Arm Robots;C-ASP: Continuous ASP-Based reasoning over RDF Streams;internet Routing and Non-monotonic reasoning;assessing Arguments with Schemes and Fallacies;simple Contrapositive Assumption-Based Frameworks;Argumentation-Based Explanations for Answer Sets Using ADF;treewidth and Counting Projected Answer Sets.
We develop an approach to solve curriculum-based course timetabling (CB-CTT) problems with Large Neighborhood Prioritized Search (LNPS) based on Answer Set programming (ASP). LNPS is a metaheuristic that starts with a...
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ISBN:
(纸本)9783031742088;9783031742095
We develop an approach to solve curriculum-based course timetabling (CB-CTT) problems with Large Neighborhood Prioritized Search (LNPS) based on Answer Set programming (ASP). LNPS is a metaheuristic that starts with an initial solution and then iteratively tries to obtain improved solutions by alternately destroying and prioritized searching for a current solution. Our approach relies on high-level domain-specific LNPS configurations for efficient CB-CTT solving, and boththe grounding and solving tasks are delegated to a heuristically-driven answer set optimizer implementing the LNPS algorithm. the resulting system teaspoon-lnps demonstrates that LNPS can significantly enhance the solving performance of ASP for CB-CTT solving. Furthermore, we show the competitiveness of our declarative approach by empirically contrasting it to the best known bounds obtained by more dedicated algorithms.
the analysis of properties of consequence operators has been a very active field in the formative years of non-monotonic reasoning. One possible approach to do this is to start with a model-theoretic semantics and the...
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ISBN:
(纸本)9783031742088;9783031742095
the analysis of properties of consequence operators has been a very active field in the formative years of non-monotonic reasoning. One possible approach to do this is to start with a model-theoretic semantics and then to study the logical consequence relation induced by that semantics. In this paper we follow that approach and analyse resulting consequence operators of so-called characterization logics. Roughly speaking, a characterization logic characterizes, via its own notion of ordinary equivalence, another logic's notion of strong equivalence. For example, the logic of here and there is a characterization logic for answer set programs, because strong equivalence of the latter is characterized by ordinary equivalence of the former. In previous work, we showed that the consideration of finite knowledge bases only - a common assumption in the field of knowledge representation - guarantees the existence (and uniqueness) of characterization logics. In this paper, we apply this existence result to the field of abstract argumentation. We show that the associated consequence operator outputs a so-called reverse kernel, a useful construct that received comparably little attention in the literature so far. As an aside, we clarify that for several well-known logics, their canonical characterization consequence operators are well-behaved.
Large Language Models (LLMs) lack the ability for commonsense reasoning and learning from text. In this work, we present a system, called LLM2LAS, for learning commonsense knowledge from story-based question and answe...
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ISBN:
(纸本)9783031742088;9783031742095
Large Language Models (LLMs) lack the ability for commonsense reasoning and learning from text. In this work, we present a system, called LLM2LAS, for learning commonsense knowledge from story-based question and answering expressed in natural language. LLM2LAS combines the semantic parsing capability of LLMs with ILASP for learning commonsense knowledge expressed as answer set programs. LLM2LAS requires only few examples of questions and answers to learn general commonsense knowledge and correctly answer unseen questions. An empirical evaluation demonstrates the viability of our approach.
In the fast-growing area of Artificial Intelligence (AI), the ability of autonomous agents to engage in complex debates is crucial for consensus building on beliefs, actions, or goals and forms the basis for applicati...
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ISBN:
(纸本)9783031742088;9783031742095
In the fast-growing area of Artificial Intelligence (AI), the ability of autonomous agents to engage in complex debates is crucial for consensus building on beliefs, actions, or goals and forms the basis for applications in decision-making, planning, opinion polling, and negotiation. In this paper, we leverage the Timed Concurrent Language for Argumentation, a modelling language derived from concurrent programming paradigms and Argumentation theory, to introduce well-known high-level propositions (claim, counter, why, argue, concede, and retract) to model various debate forms, making it a powerful tool for agent interaction. the obtained constructs, specifically designed for multi-agent reasoning and the facilitation of argumentation, define the dialogue language DICLA (DIalogic Concurrent Language for Argumentation) that enables domain experts to employ advanced computational argumentation tools without needing programming skills, bridging the gap between theoretical argumentation models and practical, real-world applications.
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