PRICAI 2004: Trends in Artificial Intelligence PRICAI 2004：人工智能趋势/会议录

The LNAI series reports state-of-the-art results in artificial intelligence re-search, devetopmenh and educatiOn, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available.
The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety ofapplication fields. The type of material published tradition ally includes
proceedings (published in time for the respective conference)
post-proceedings (consisting of thoroughly revised final full papers)
research monographs (which may be based on PhD work)

Invited Talks
Biomedical Artificial Intelligence
Electronics Institutions: Methodology of Multi-agent Systems Development
The Happy Searcher: Challenges in Web Information Retrieval
PART 1: AI Foundations
Logic and Reasoning
On the Intended Interpretations of Actions
Temporal Linear Logic for Symbolic Agent Negotiation
Dealing with Inconsistent Secure Messages
Answer Set Computation Based on a Minimal Model Generation Theorem Prover
Knowledge Representation and Search
What Is a Qualitative Calculus? A General Framework
Qualitative Direction Calculi with Arbitrary Granularity
Power of Brute-Force Search in Strongly-Typed Inductive Functional Programming Automation
Ontology
Ontology Services-Based Information Integration in Mining Telecom Business Intelligence
Planning
Indexing Approach for Delivery Demands with Time Constraints
An Hierarchical Terrain Representation for Approximately Shortest Paths
MSIP: Agents Embodying a Category-Based Learning Process for the ITS Tutor to Self-improve Its Instructional Plans
Constraint Satisfaction
Circuit Consistencies
Solving Over-Constrained Temporal Reasoning Problems
Using Local Search
Methods of Automatic Algorithm Generation ...
A Novel Heuristic to Solve IA Network by Convex Approximation and Weights
Applying An Improved Heuristic Based Optimiser to Solve a Set of Challengin University Timetabling Problems:An Experience Report
Extending Unit Propagation Look-Ahead of DPLL Procedure
Machine Learning
Extended Nearest Feature Line Classifier
Sifting the Margin - An Iterative Empirical Classification Scheme
PART2:Computational Intelligence
PART3:AI Methodologies and Systems
PART4:AI SPecific Application Areas
Author Indes