Abstraction, Reformulation, and Approximation

Inhaltsverzeichnis

• Invited Talks (Abstracts).
• State Abstraction in Real-Time Heuristic Search.
• Abstraction and Reformulation in the Generation of Constraint Models.
• A Framework for Integrating Optimization and Constraint Programming.
• Research Papers.
• DFS-Tree Based Heuristic Search.
• Partial Pattern Databases.
• CDB-PV: A Constraint Database-Based Program Verifier.
• Generating Implied Boolean Constraints Via Singleton Consistency.
• Reformulating Constraint Satisfaction Problems to Improve Scalability.
• Reformulating Global Constraints: The Slide and Regular Constraints.
• Relaxation of Qualitative Constraint Networks.
• Dynamic Domain Abstraction Through Meta-diagnosis.
• Channeling Abstraction.
• Approximate Model-Based Diagnosis Using Greedy Stochastic Search.
• Combining Perimeter Search and Pattern Database Abstractions.
• Solving Satisfiability in Ground Logic with Equality by Efficient Conversion to Propositional Logic.
• Tailoring Solver-Independent Constraint Models: A Case Study with Essence? and Minion.
• A Meta-CSP Model for Optimal Planning.
• Reformulation for Extensional Reasoning.
• An Abstract Theory and Ontology of Motion Based on the Regions Connection Calculus.
• Computing and Using Lower and Upper Bounds for Action Elimination in MDP Planning.
• Model-Based Exploration in Continuous State Spaces.
• Active Learning of Dynamic Bayesian Networks in Markov Decision Processes.
• Boosting MUS Extraction.
• Homogeneous Hierarchical Composition of Areas in Multi-robot Area Coverage.
• Formalizing the Abstraction Process in Model-Based Diagnosis.
• Boolean Approximation Revisited.
• An Analysis of Map-Based Abstraction and Refinement.
• Solving Difficult SAT Instances Using Greedy Clique Decomposition.
• Abstraction and Complexity Measures.
• Research Summaries.
• Abstraction, Emergence, andThought.
• What’s Your Problem? The Problem of Problem Definition.
• A Reformulation-Based Approach to Explanation in Constraint Satisfaction.
• Integration of Constraint Programming and Metaheuristics.
• Rule-Based Reasoning Via Abstraction.
• Extensional Reasoning.
• Reformulating Constraint Models Using Input Data.
• Using Analogy Discovery to Create Abstractions.
• Distributed CSPs: Why It Is Assumed a Variable per Agent?.
• Decomposition of Games for Efficient Reasoning.
• Generalized Constraint Acquisition.
• Using Infeasibility to Improve Abstraction-Based Heuristics.
• Leveraging Graph Locality Via Abstraction.