Case-Based Reasoning Research and Development
Springer Berlin (Verlag)
978-3-642-02997-4 (ISBN)
The 17 revised full papers and 17 revised poster papers presented together with 2 invited talks were carefully reviewed and selected from 55 submissions. Covering a wide range of CBR topics of interest both to practitioners and researchers, the papers are devoted to theoretical/methodological as well as to applicative aspects of current CBR analysis.
Invited Talks.- We're Wiser Together.- Black Swans, Gray Cygnets and Other Rare Birds.- Theoretical/Methodological Research Papers.- Case Retrieval Reuse Net (CR2N): An Architecture for Reuse of Textual Solutions.- Case-Based Reasoning in Transfer Learning.- Toward Modeling and Teaching Legal Case-Based Adaptation with Expert Examples.- Opportunistic Adaptation Knowledge Discovery.- Improving Reinforcement Learning by Using Case Based Heuristics.- Dimensions of Case-Based Reasoner Quality Management.- Belief Merging-Based Case Combination.- Maintenance by a Committee of Experts: The MACE Approach to Case-Base Maintenance.- The Good, the Bad and the Incorrectly Classified: Profiling Cases for Case-Base Editing.- An Active Approach to Automatic Case Generation.- Four Heads Are Better than One: Combining Suggestions for Case Adaptation.- Adaptation versus Retrieval Trade-Off Revisited: An Analysis of Boundary Conditions.- Boosting CBR Agents with Genetic Algorithms.- Using Meta-reasoning to Improve the Performance of Case-Based Planning.- Multi-level Abstractions and Multi-dimensional Retrieval of Cases with Time Series Features.- On Similarity Measures Based on a Refinement Lattice.- An Overview of the Deterministic Dynamic Associative Memory (DDAM) Model for Case Representation and Retrieval.- Robust Measures of Complexity in TCBR.- S-Learning: A Model-Free, Case-Based Algorithm for Robot Learning and Control.- Quality Enhancement Based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender.- Abstraction in Knowledge-Rich Models for Case-Based Planning.- A Scalable Noise Reduction Technique for Large Case-Based Systems.- Conceptual Neighborhoods for Retrieval in Case-Based Reasoning.- CBR Supports Decision Analysis with Uncertainty.-Constraint-Based Case-Based Planning Using Weighted MAX-SAT.- Applied Research Papers.- A Value Supplementation Method for Case Bases with Incomplete Information.- Efficiently Implementing Episodic Memory.- Integration of a Methodology for Cluster-Based Retrieval in jColibri.- Case-Based Collective Inference for Maritime Object Classification.- Case-Based Reasoning for Situation-Aware Ambient Intelligence: A Hospital Ward Evaluation Study.- Spatial Event Prediction by Combining Value Function Approximation and Case-Based Reasoning.- Case-Based Support for Forestry Decisions: How to See the Wood from the Trees.- A Case-Based Perspective on Social Web Search.- Determining Root Causes of Drilling Problems by Combining Cases and General Knowledge.
| Erscheint lt. Verlag | 30.6.2009 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XIII, 526 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 825 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | ADA • Agents • algorithms • Ambient Intelligence • automatic case generation • Case-Based Planning • Case-Based Reasoning • case similarity • CBR agents • CBR quality management • CBR tools • Cluster • complexity measures • decision modeling • distributed CBR • Genetic algorithms • Hardcover, Softcover / Informatik, EDV/Informatik • Heuristics • hybrid AI systems • Information Retrieval • Instance-Based Learning • knowledge management • learning • machine learning • Multi-agent Systems • multi-dimensional indexing • Process-Oriented Reasoning • proving • real-time CBR • Recommender Systems • Reinforcement Learning • robot • self-organization maps • semantic web • Soft Computing • spatial prediction • temporal CBR • textual CBR |
| ISBN-10 | 3-642-02997-3 / 3642029973 |
| ISBN-13 | 978-3-642-02997-4 / 9783642029974 |
| Zustand | Neuware |
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