AI 2005: Advances in Artificial IntelligenceAI 2005：人工智能进展/会议录
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内容提要：
The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, 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 of application fields. The type of material published traditionally 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) 目录：
Invited Talks
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining Providing Semantics for the WEB Using Fuzzy Set Methods Little Models, Big Results PART I: AI Foundations and Technologies Logic and Reasoning Model Updating CTL Systems Model Checking for PRS-Like Agents A Fibred Belief Logic for Multi-agent Systems Inconsistency-Based Strategy for Clarifying Vague Software Requirements Conditioning Graphs: Practical Structures for Inference in Bayesian Networks Reasoning with the Outcomes of Plan Execution in Intentional Agents Tie Breaking in Clause Weighting Local Search for SAT Syntactic and Semantic Disambiguation of Numeral Strings Using an N-Gram Method Machine Learning Locating Regions of Interest in CBIR with Multi-instance Learning Techniques Ensemble Selection for SuperParent-One-Dependence Estimators Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning Any-Cost Discovery: Learning Optimal Classification Rules Preprocessing Time Series Data for Classification with Application to CRM Combining Contents and Citations for Scientific Document Classification Machine Learning Approach to Realtime Intrusion Detection System Structural Abstraction Experiments in Reinforcement Learning A Hybrid Adaptive Multi-objective Memetic Algorithm for 0/1 Knapsack Problem Game Theory Probability Estimation in Error Correcting Output Coding Framework Using Game Theory …… PART II:Computational Intelligence PART Ⅲ:AI in Specialized Domains PART Ⅳ:Short Papers Author Index |