Logic Programming and Nonmonotonic Reasoning逻辑编程与非单调推理

出版时间：2004-2  出版社：北京燕山出版社  作者：Niemels, Ilkka 编  页数：364  

内容概要

This book constitutes the refereed proceedings of the 7th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2004, held in Fort Lauderdale, Florida, USA in January 2004.    The 24 revised full papers presented together with 8 system descriptions were carefully reviewed and selected for presentation. Among the topics addressed are declarative logic programming, nonmonotonic reasoning, knowledge representation, combinatorial search, answer set programming, constraint programming, deduction in ontologies, and planning.

书籍目录

Invited Papers  Constraints and Probabilistic Networks: A Look at the Interface  Toward a Universal Inference Engine  Towards Systematic Benchmarking in Answer Set Programming: The Dagstuhl Initiative  Regular Papers  Semantics for Dynamic Logic Programming: A Principle-Based Approach,  Probabilistic Reasoning with Answer Sets  Answer Sets: From Constraint Programming towards Qualitative Optimization  A Logic of Non-monotone Inductive Definitions and Its Modularity Properties  Reasoning about Actions and Change in Answer Set Programming  Almost Definite Causal Theories  Simplifying Logic Programs under Uniform and Strong Equivalence  Towards Automated Integration of Guess and Check Programs in Answer Set Programming  Definitions in Answer Set Programming  Graphs and Colorings for Answer Set Programming:Abridged Report  Nondefinite vs. Definite Causal Theories  Logic Programs with Monotone Cardinality Atoms  Set Constraints in Logic Programming  Verifying the Equivalence of Logic Programs in the Disjunctiw Case  Uniform Equivalence for Equilibrium Logic and Logic Programs  Partial Stable Models for Logic Programs with Aggregates  Improving the Model Generation/Checking Interplay to Enhance the Evaluation of Disjunctive Programs  Using Criticalities as a Heuristic for Answer Set Programming  Planning with Preferences Using Logic Programming  Planning with Sensing Actions and Incomplete Information Using Logic Programming  Deduction in Ontologies via ASP  Strong Equivalence for Causal Theories  Answer Set Programming with Clause Learning  Properties of Iterated Multiple Belief Revision  ……System Descriptions Author Index