The Abstraction and Reasoning Corpus (ARC) is a general artificial intelligence benchmark that is currently unsolvable by any Machine Learning method. It demands strong generalization and reasoning capabilit...
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Answer Set programming (ASP) is a well-known symbolic AI formalism developed in the area of knowledgerepresentation and reasoning. This paper reports on some blendings of ASP with neural approaches, that ca...
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This paper presents a novel approach combining inductive logicprogramming with reinforcement learning to improve training performance and explainability. We exploit inductive learning of answer set programs from...
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The proceedings contain 7 papers. The special focus in this conference is on Hybrid Models for Coupling Deductive and Inductive Reasoning. The topics include: Evaluating Inductive Reasoning Capabilities of Large ...
ISBN:
(纸本)9783031893650
The proceedings contain 7 papers. The special focus in this conference is on Hybrid Models for Coupling Deductive and Inductive Reasoning. The topics include: Evaluating Inductive Reasoning Capabilities of Large Language Models With The One Dimensional Abstract Reasoning Corpus;program Synthesis Using Inductive logicprogramming for the Abstraction and Reasoning Corpus;trustworthy Inductive knowledge for Tropical Cyclones Formation Detection;automatic Curriculum Cohesion Analysis Based on knowledge Graphs;online Inductive Learning from Answer Sets for Efficient Reinforcement Learning Exploration.
This paper discusses the role that background knowledge can play in building flexible multistrategy learning systems. We contend that a variety of learning strategies can be embodied in the background knowledge provid...
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This paper discusses the role that background knowledge can play in building flexible multistrategy learning systems. We contend that a variety of learning strategies can be embodied in the background knowledge provided to a general purpose learning algorithm. To be effective, the general purpose algorithm must have a mechanism for learning new concept descriptions that can refer to knowledge provided by the user or learned during some other task. The method of knowledgerepresentation is a central problem in designing such a system since it should be possible to specify background knowledge in such a way that the learner can apply its knowledge to new information.
This paper is concerned with the design of type systems for logicprogramming so as to satisfy the requirements of modern logicprogramming. The design of type systems is based on the language Godel which has a strong...
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ISBN:
(纸本)9781424421961
This paper is concerned with the design of type systems for logicprogramming so as to satisfy the requirements of modern logicprogramming. The design of type systems is based on the language Godel which has a strongly type system based on many-sorted logic with parametric polymorphism. The definitions of the basic logicprogramming concepts of terms, atoms, programs are given in the setting of polymorphic many-sorted logic. In particular, an unification algorithm for typed predicates is proposed for the compiler construction of Godel.
Open Answer Set programming (OASP) is a knowledgerepresentation paradigm that allows for a tight integration of logicprogramming rules and Description logic ontologies. Although several decidable fragments of OASP e...
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In this paper, we use autoepistemic reasoning semantics to classify various semantics for disjunctive logic programs with default negation. We have observed that two different types of negative introspection in autoep...
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ISBN:
(纸本)3540649581
In this paper, we use autoepistemic reasoning semantics to classify various semantics for disjunctive logic programs with default negation. We have observed that two different types of negative introspection in autoepistemic reasoning present two different interpretations of default negation: consistency-based and minimal-model-based. We also observed that all logic program semantics fall into three semantical points of view: the skeptical, stable, and partial-stable. Based on these two observations, we classify disjunctive logic program semantics into six different categories, and discuss the relationships among various semantics.
The proceedings contain 9 papers. The topics discussed include: knowledgerepresentation with logic programs;DATALOG with nested rules;partial evidential stable models for disjunctive deductive databases;disjunctive l...
ISBN:
(纸本)3540649581
The proceedings contain 9 papers. The topics discussed include: knowledgerepresentation with logic programs;DATALOG with nested rules;partial evidential stable models for disjunctive deductive databases;disjunctive logicprogramming and autoepistemic logic;a system for abductive learning of logic programs;refining action theories through abductive logicprogramming;abduction, argumentation and bi-disjunctive logic programs;reasoning with prioritized defaults;and generalizing updates: from models to programs.
This paper presents an extension of disjunctive dat slog (Datalog(V)) by nested rules. Nested rules are (disjunctive) rules where elements of the head may be also rules. Nested rules increase the knowledge representat...
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ISBN:
(纸本)3540649581
This paper presents an extension of disjunctive dat slog (Datalog(V)) by nested rules. Nested rules are (disjunctive) rules where elements of the head may be also rules. Nested rules increase the knowledgerepresentation power of Datalog(V) both from a theoretical and from a practical viewpoint. A number of examples show that nested rules allow to naturally model several real world situations that cannot be represented in Datalog(V). An in depth analysis of complexity and expressive power of the language shows that nested rules do increase the expressiveness of Datalog(V) without implying any increase in its computational complexity.
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