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Advances in artificial transportation systems and simulation /
The Intelligent Systems Series encompasses theoretical studies, design methods, and real-world implementations and applications. It publishes titles in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. Titles focus on professional and...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
San Diego, California :
Elsevier/Academic Press,
[2015]
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| Colección: | Intelligent systems series.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title Page; Copyright Page; Table of Contents; List of contributors; Preface; Chapter 1
- ITSUMO: An Agent-Based Simulator for Intelligent Transportation Systems; 1.1
- Introduction and Motivation; 1.2
- Description of the Simulator; 1.2.1
- Microscopic Simulation Model and Simulation Kernel; 1.2.2
- Database Module; 1.2.3
- Output Module: Statistics and Visualization; 1.3
- Control: Traffic Light Agent Module; 1.3.1
- Greedy Traffic Light Agent; 1.3.2
- Reinforcement Learning-Based Methods; 1.3.3
- Swarm-Intelligence Inspired Signal Plan Choice; 1.4
- Demand.
- 1.4.1
- Routing of the Demand1.4.2
- Deadlock Handling; 1.4.3
- Driver Definition; 1.4.4
- Drivers and En-Route Replanning; 1.5
- Case-Study: Aggregating Intelligence to Traffic Simulation; 1.6
- Conclusion; Acknowledgment; References; Chapter 2
- A Pattern-Based Framework for Building Self-Organizing Multi-Agent Systems; 2.1
- Introduction; 2.2
- JASOF; 2.2.1
- Main Idea; 2.2.2
- JASOF Structure; 2.2.2.1
- Environment; 2.2.2.2
- Agent location; 2.2.2.3
- Diffusion pattern; 2.2.2.4
- Evaporation pattern; 2.2.2.5
- Aggregation pattern; 2.2.2.6
- Replication pattern; 2.2.3
- JASOF Hotspots.
- 2.3
- Case Study: A Self-Organized Automatic Guided Vehicle2.3.1
- Main Idea; 2.3.2
- Destination Agent; 2.3.3
- Warehouse Agent; 2.3.4
- Transporter Agent; 2.3.5
- Location Agent; 2.3.6
- Execution; 2.3.7
- System Composition; 2.4
- Related Work; 2.5
- Conclusions and Future Work; Acknowledgment; References; Chapter 3
- An Agent Methodology for Processes, the Environment, and Services; 3.1
- Introduction; 3.2
- Background; 3.3
- Analysis and Design for MAS; 3.3.1
- Scenario Description and Early Requirements Analysis; 3.3.2
- Analysis Phase; 3.3.3
- Architectural Design.
- 3.3.4
- Detailed Design3.4
- Discussion and Future Work; Acknowledgment; References; Chapter 4
- A Role-Based Method for Analyzing Supply Chain Models; 4.1
- Introduction; 4.2
- Related Work; 4.3
- A Framework of Supply Chain Roles, Responsibilities and Interactions; 4.3.1 Roles; 4.3.2
- Responsibilities; 4.3.3
- Interaction; 4.3.4
- An Illustrating Example; 4.4
- A Method for Analyzing Supply Chain Simulation Models; 4.5
- Applicability and Validity of the Framework and Analysis Method; 4.5.1
- Analysis of the TAPAS Simulation Model.
- 4.5.2
- Analysis of a Supply Chain Model by Strader et al. (1998)4.5.3
- Analysis of a Supply Chain Model by Gjerdrum et al. (2001); 4.5.4
- Discrete Event Simulation of a Food Supply Chain; 4.5.5
- Dynamic Simulation of a Short Life Cycle Product Supply Chain; 4.6
- Concluding Remarks and Future Work; References; Chapter 5
- Applying Delegate MAS Patterns in Designing Solutions for Dynamic Pickup and Delivery Problems; 5.1
- Introduction; 5.2
- Related Work; 5.2.1
- Combinatorial Optimization-Based Approaches for Solving PDP; 5.2.2
- MAS-Based Approaches for Solving PDP.
- 5.2.3
- Patterns for MAS.