Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving
High communication efforts and poor problem solving results due to restricted overview are two central issues in collaborative problem solving. This work addresses these issues by introducing the processes of agent melting and agent splitting that enable individual problem solving agents to continually and autonomously reconfigure and adapt themselves to the particular problem to be solved.

The author provides a sound theoretical foundation of collaborative problem solving itself and introduces various new design concepts and techniques to improve its quality and efficiency, such as the multi-phase agreement finding prool for external problem solving, the composable belief-desire-intention agent architecture, and the distribution-aware constraint specification architecture for internal problem solving.

The practical relevance and applicability of the concepts and techniques provided are demonstrated by using medical appointment scheduling as a case study.

1113636509
Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving
High communication efforts and poor problem solving results due to restricted overview are two central issues in collaborative problem solving. This work addresses these issues by introducing the processes of agent melting and agent splitting that enable individual problem solving agents to continually and autonomously reconfigure and adapt themselves to the particular problem to be solved.

The author provides a sound theoretical foundation of collaborative problem solving itself and introduces various new design concepts and techniques to improve its quality and efficiency, such as the multi-phase agreement finding prool for external problem solving, the composable belief-desire-intention agent architecture, and the distribution-aware constraint specification architecture for internal problem solving.

The practical relevance and applicability of the concepts and techniques provided are demonstrated by using medical appointment scheduling as a case study.

54.99 In Stock
Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving

Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving

by Markus Hannebauer
Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving

Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving

by Markus Hannebauer

Paperback(2002)

$54.99 
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Overview

High communication efforts and poor problem solving results due to restricted overview are two central issues in collaborative problem solving. This work addresses these issues by introducing the processes of agent melting and agent splitting that enable individual problem solving agents to continually and autonomously reconfigure and adapt themselves to the particular problem to be solved.

The author provides a sound theoretical foundation of collaborative problem solving itself and introduces various new design concepts and techniques to improve its quality and efficiency, such as the multi-phase agreement finding prool for external problem solving, the composable belief-desire-intention agent architecture, and the distribution-aware constraint specification architecture for internal problem solving.

The practical relevance and applicability of the concepts and techniques provided are demonstrated by using medical appointment scheduling as a case study.


Product Details

ISBN-13: 9783540443124
Publisher: Springer Berlin Heidelberg
Publication date: 12/16/2002
Series: Lecture Notes in Computer Science , #2427
Edition description: 2002
Pages: 290
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

1.Overview.- 2. Basics of Collaborative Problem Solving.- Theoretical Foundations.- 3. Distributed Constraint Problems — A Model for Collaborative Problem Solving.- 4. Autonomous Dynamic Reconfiguration — Improving Collaborative Problem Solving.- Practical Concepts.- 5. Multi-agent System Infrastructure.- 6. External Constraint Problem Solving.- 7. Composable BDI Agents.- 8. Internal Constraint Problem Solving.- 9. Controlling Agent Melting and Agent Splitting.- Assessment.- 10. Evaluation.- 11. Conclusion and Future Work.- A. Symbols and Abbreviations.- B. An XML-Encoded Request Message.- C. SICStus Prolog Code for Internal Constraint Problem Solving.- D. Initialization of the Hospital Scenario Generator.
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