Advances in Artificial Intelligence

19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Quebec City, Quebec, Canada, June 7-9, Proceedings

Häftad, Engelska, 2006

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This book constitutes the refereed proceedings of the 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, held in Quebec City, Canada in June 2006. The book presents 47 carefully reviewed, revised full papers. These are organized in topical sections on agents, bioinformatics, constraint satisfaction and distributed search, knowledge representation and reasoning, natural language, reinforcement learning and, supervised and unsupervised learning.

Produktinformation

Utgivningsdatum2006-06-06
Mått155 x 235 x undefined mm
SpråkEngelska
SerieLecture Notes in Artificial Intelligence
Antal sidor566
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
EAN9783540346289

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Artificiell intelligens inom Data och it

Agents.- Integrating Information Gathering Interaction into Transfer of Control Strategies in Adjustable Autonomy Multiagent Systems.- A Pruning-Based Algorithm for Computing Optimal Coalition Structures in Linear Production Domains.- A Smart Home Agent for Plan Recognition.- Using Multiagent Systems to Improve Real-Time Map Generation.- An Efficient Resource Allocation Approach in Real-Time Stochastic Environment.- Satisfaction Equilibrium: Achieving Cooperation in Incomplete Information Games.- How Artificial Intelligent Agents Do Shopping in a Virtual Mall: A ‘Believable’ and ‘Usable’ Multiagent-Based Simulation of Customers’ Shopping Behavior in a Mall.- Bioinformatics.- A New Profile Alignment Method for Clustering Gene Expression Data.- A Classification-Based Glioma Diffusion Model Using MRI Data.- Bayesian Learning for Feed-Forward Neural Network with Application to Proteomic Data: The Glycosylation Sites Detection of the Epidermal Growth Factor-Like Proteins Associated with Cancer as a Case Study.- Constraint Satisfaction and Search.- Relaxation of Soft Constraints Via a Unified Semiring.- Intelligent Information Personalization Leveraging Constraint Satisfaction and Association Rule Methods.- On the Quality and Quantity of Random Decisions in Stochastic Local Search for SAT.- Simple Support-Based Distributed Search.- Knowledge Representation and Reasoning.- Modeling Causal Reinforcement and Undermining with Noisy-AND Trees.- An Improved LAZY-AR Approach to Bayesian Network Inference.- Four-Valued Semantics for Default Logic.- Exploiting Dynamic Independence in a Static Conditioning Graph.- Probabilistic Melodic Harmonization.- Learning Bayesian Networks in Semi-deterministic Systems.- Progressive Defeat Paths in Abstract Argumentation Frameworks.-Natural Language.- Parsing Korean Honorification Phenomena in a Typed Feature Structure Grammar.- Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity.- Unsupervised Labeling of Noun Clusters.- Language Patterns in the Learning of Strategies from Negotiation Texts.- Using Natural Language Processing to Assist the Visually Handicapped in Writing Compositions.- Text Compression by Syntactic Pruning.- Beyond the Bag of Words: A Text Representation for Sentence Selection.- Sentiment Tagging of Adjectives at the Meaning Level.- Reinforcement Learning.- Adaptive Fraud Detection Using Benford’s Law.- Partial Local FriendQ Multiagent Learning: Application to Team Automobile Coordination Problem.- Trace Equivalence Characterization Through Reinforcement Learning.- Belief Selection in Point-Based Planning Algorithms for POMDPs.- Supervised and Unsupervised Learning.- Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization.- Adaptive Clustering Algorithms.- Classification Based on Logical Concept Analysis.- Machine Learning in a Quantum World.- A New Attempt to Silhouette-Based Gait Recognition for Human Identification.- Learning Naïve Bayes Tree for Conditional Probability Estimation.- On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques.- Discriminative vs. Generative Classifiers for Cost Sensitive Learning.- The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization.- Learning Naive Bayes for Probability Estimation by Feature Selection.- Lazy Averaged One-Dependence Estimators.- Probabilistic Inference Trees for Classification and Ranking.- Parameter Estimation of One-Class SVM on Imbalance Text Classification.- UserModeling.- MITS: A Mixed-Initiative Intelligent Tutoring System for Sudoku.