Massively Multi-Agent Systems II

Name: Massively Multi-Agent Systems II | International Workshop, MMAS 2018, Stockholm, Sweden, July 14, 2018, Revised Selected Papers
Brand: Springer
Price: 53.49 EUR
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International Workshop, MMAS 2018, Stockholm, Sweden, July 14, 2018, Revised Selected Papers

Donghui Lin Toru Ishida Franco Zambonelli Itsuki Noda(Herausgeber*in)

Springer (Verlag)

Erschienen am 18. Mai 2019

X, 163 Seiten

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978-3-030-20937-7 (ISBN)

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Beschreibung

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Inhalt

Intro
Preface
Organization
Contents
Multi-agent Systems and Internet of Things
Distributed Speaking Objects: A Case for Massive Multiagent Systems
1 Introduction
2 Speaking Objects as Cognitive Goal-Oriented Agents
2.1 Data Collection vs. Cognitive Sensing
2.2 Actuating Commands vs. Achieving Goals
3 Distributed Coordination as a Conversation
3.1 From Coordination to Conversations
3.2 Types of Conversations
4 Enabling Technologies
4.1 Cognitive Reasoning
4.2 Machine Learning
4.3 Goal-Oriented Computing
4.4 Argumentation-Based Coordination
5 Integration Recipe: Open Challenges for Realizing the Vision
5.1 Massive Scale and Heterogeneity
5.2 Middleware
5.3 Humans-in-the-Loop
5.4 Harnessing Algocracy
5.5 Security
6 Conclusions
References
Injecting (Micro)Intelligence in the IoT: Logic-Based Approaches for (M)MAS
1 Introduction
2 Background and Related Work
2.1 (M)MAS, IoT and Intelligence
2.2 Engineering Intelligence in the IoT: Key Challenges
3 Logic-Based Approaches for (M)MAS and IoT
4 LPaaS & LVLP for Environment Intelligence
4.1 Vision
4.2 LPaaS in a Nutshell
4.3 LVLP in a Nutshell
4.4 LPaaS & LVLP in (M)MAS
5 ReSpecT and Logical Tuples for Social Intelligence
5.1 Vision
5.2 TuCSoN and ReSpecT in a Nutshell
6 Conclusion
References
Integrating Internet of Services and Internet of Things from a Multiagent Perspective
1 Introduction
2 Background of IoS and IoT
2.1 Internet of Services (IoS)
2.2 Internet of Things (IoT)
3 Issues for Integrating IoS and IoT
4 A Multiagent Perspective on Integrated IoS/IoT
4.1 Integration of IoS and IoT
4.2 The Multiagent-Based Architecture
4.3 Multiagent Methodologies for Service Design
5 An Example Application of Multilingual Environment Design
6 Conclusion
References
Architectures for Massively Multi-agent Systems
Two-Layer Architecture for Distributed Massively Multi-agent Systems
1 Introduction
2 Two-Layer Architecture
2.1 Overlay Networks
2.2 Overall Architecture
2.3 Macro Agents
2.4 Micro Agents
3 Meta Scenario
3.1 Scenario Description Language Q
3.2 Extension of Q for Meta-scenario
3.3 Example of Meta-scenario
4 Application
4.1 Driving Control Using Environment-Embedded Sensors
5 Conclusion
References
Multi-agent Social Simulation for Social Service Design
1 Introduction
2 Pedestrian Simulations
2.1 Efficiency/Complexity Trade-Off Analysis for Evacuation Guidance
2.2 Evacuation Scalability Analysis
3 Transportation Simulations for On-Demand Traffic Systems
4 OACIS: Exhaustive Simulation Framework
5 Concluding Remarks
References
Inverse Reinforcement Learning for Agents Behavior in a Crowd Simulator
1 Introduction
2 Related Work
3 Pedestrian Simulator
4 Agent Model
5 Preliminary Validation
6 Conclusions
References
FARM: Architecture for Distributed Agent-Based Social Simulations
1 Introduction
2 Related Work
3 FARM Distributed Simulation Architecture
4 Github Simulation and Experiment Setup
5 Results
6 Discussion
References
Applications of Massively Multi-agent Systems
Diversity in Massively Multi-agent Systems: Concepts, Implementations, and Normal Accidents
1 Introduction
2 The TaaS Spectrum of Coordination
2.1 Market Systems
2.2 Hierarchical Control Systems
3 Ensembles of Hierarchies
3.1 Research Challenges
3.2 General Framework
3.3 Hierarchical Adaptation
3.4 Collective Adaptation Engine
4 Resilience Engineering for Normal Accidents
References
CARAVAN: A Framework for Comprehensive Simulations on Massive Parallel Machines
1 Motivation and Significance
2 Software Description
2.1 Overall Architecture
2.2 Requirements for a Simulator
2.3 Preparation of a Search Engine
3 Implementation
4 Application to Multi-agent Simulation
4.1 Searching Trade-Off Relationships in Evacuation Planning
4.2 Multi-objective Optimization Algorithm
4.3 Evacuation Simulator
4.4 Results and Discussion
5 Conclusions and Future Work
References
BASIC: Towards a Blockchained Agent-Based SImulator for Cities
1 Introduction
2 Background
2.1 Car-Sharing Scenario
2.2 Agent-Based Simulation
2.3 Blockchain and Smart Contracts
3 The BASIC Architecture
3.1 Data and Simulation Layers
3.2 Blockchain Layer
3.3 Planner Layer
4 Experiment, Results and Analysis
5 Discussion and Future Work
References
Author Index

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