Saved in:
| Other Authors: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2013
|
| Series: | Studies in computational intelligence
456 |
| Subjects: | |
| Links: | https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 https://doi.org/10.1007/978-3-642-34097-0 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025935634&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025935634&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Summary: | <p>This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the <i>agent-based optimization</i>. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving. </p> |
| Item Description: | Machine Learning and Multiagent Systems as Interrelated Technologies -- Ant Colony Optimization for the Multi-criteria Vehicle Navigation Problem -- Solving Instances of the Capacitated Vehicle Routing Problem Using Multi-Agent Non-Distributed and Distributed Environment -- Structure vs. Efficiency of the Cross-Entropy Based Population Learning Algorithm for Discrete-Continuous Scheduling with Continuous Resource Discretisation -- Triple-Action Agents Solving the MRCPSP/max Problem -- Team of A-Teams - a Study of the Cooperation Between Program Agents Solving Difficult Optimization Problems -- Distributed Bregman-Distance Algorithms for Min-Max Optimization -- A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure |
| Physical Description: | 1 Online-Ressource (X, 203 p. 38 illus) |
| ISBN: | 9783642340970 |
| DOI: | 10.1007/978-3-642-34097-0 |
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Record in the Search Index
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| adam_text | AGENT-BASED OPTIMIZATION
/
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
MACHINE LEARNING AND MULTIAGENT SYSTEMS AS INTERRELATED TECHNOLOGIES
ANT COLONY OPTIMIZATION FOR THE MULTI-CRITERIA VEHICLE NAVIGATION
PROBLEM
SOLVING INSTANCES OF THE CAPACITATED VEHICLE ROUTING PROBLEM USING
MULTI-AGENT NON-DISTRIBUTED AND DISTRIBUTED ENVIRONMENT
STRUCTURE VS. EFFICIENCY OF THE CROSS-ENTROPY BASED POPULATION LEARNING
ALGORITHM FOR DISCRETE-CONTINUOUS SCHEDULING WITH CONTINUOUS RESOURCE
DISCRETISATION
TRIPLE-ACTION AGENTS SOLVING THE MRCPSP/MAX PROBLEM
TEAM OF A-TEAMS - A STUDY OF THE COOPERATION BETWEEN PROGRAM AGENTS
SOLVING DIFFICULT OPTIMIZATION PROBLEMS
DISTRIBUTED BREGMAN-DISTANCE ALGORITHMS FOR MIN-MAX OPTIMIZATION
A PROBABILITY COLLECTIVES APPROACH FOR MULTI-AGENT DISTRIBUTED AND
COOPERATIVE OPTIMIZATION WITH TOLERANCE FOR AGENT FAILURE
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
AGENT-BASED OPTIMIZATION
/
: 2013
ABSTRACT / INHALTSTEXT
THIS VOLUME PRESENTS A COLLECTION OF ORIGINAL RESEARCH WORKS BY LEADING
SPECIALISTS FOCUSING ON NOVEL AND PROMISING APPROACHES IN WHICH THE
MULTI-AGENT SYSTEM PARADIGM IS USED TO SUPPORT, ENHANCE OR REPLACE
TRADITIONAL APPROACHES TO SOLVING DIFFICULT OPTIMIZATION PROBLEMS. THE
EDITORS HAVE INVITED SEVERAL WELL-KNOWN SPECIALISTS TO PRESENT THEIR
SOLUTIONS, TOOLS, AND MODELS FALLING UNDER THE COMMON DENOMINATOR OF THE
AGENT-BASED OPTIMIZATION. THE BOOK CONSISTS OF EIGHT CHAPTERS COVERING
EXAMPLES OF APPLICATION OF THE MULTI-AGENT PARADIGM AND RESPECTIVE
CUSTOMIZED TOOLS TO SOLVE DIFFICULT OPTIMIZATION PROBLEMS ARISING IN
DIFFERENT AREAS SUCH AS MACHINE LEARNING, SCHEDULING, TRANSPORTATION
AND, MORE GENERALLY, DISTRIBUTED AND COOPERATIVE PROBLEM SOLVING
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| dewey-full | 006.3 |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-642-34097-0 |
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| id | DE-604.BV040957204 |
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| indexdate | 2024-12-20T16:28:03Z |
| institution | BVB |
| isbn | 9783642340970 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025935634 |
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| physical | 1 Online-Ressource (X, 203 p. 38 illus) |
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| publishDate | 2013 |
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| publisher | Springer |
| record_format | marc |
| series | Studies in computational intelligence |
| series2 | Studies in computational intelligence |
| spellingShingle | Agent-based optimization Studies in computational intelligence Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Mehragentensystem (DE-588)4389058-1 gnd Optimierung (DE-588)4043664-0 gnd |
| subject_GND | (DE-588)4389058-1 (DE-588)4043664-0 (DE-588)4143413-4 |
| title | Agent-based optimization |
| title_auth | Agent-based optimization |
| title_exact_search | Agent-based optimization |
| title_full | Agent-based optimization Ireneusz Czarnowski ... (eds.) |
| title_fullStr | Agent-based optimization Ireneusz Czarnowski ... (eds.) |
| title_full_unstemmed | Agent-based optimization Ireneusz Czarnowski ... (eds.) |
| title_short | Agent-based optimization |
| title_sort | agent based optimization |
| topic | Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Mehragentensystem (DE-588)4389058-1 gnd Optimierung (DE-588)4043664-0 gnd |
| topic_facet | Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Mehragentensystem Optimierung Aufsatzsammlung |
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