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Details
Table of Contents
Intro
Preface
Organization
Contents
Part I
Contents
Part II
Swarm Intelligence and Nature-Inspired Computing
Swarm Unit Digital Control System Simulation
1 Introduction
2 Features of Von Neumann Computer Control
3 Semi-Markov Model of DC Operation
4 Example of Control System Analysis
5 Conclusion
References
Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams
1 Introduction
2 Related Work
2.1 Multi-agent Reinforcement Learning
2.2 Multi-agent Environments
3 Method
3.1 Modeling Observation of Opponents
3.2 Modeling Interactions with Teammates
3.3 Policy
3.4 Scalability and Real World Applicability
3.5 Training
4 Environment
4.1 Observation Space
4.2 Action Space
4.3 Reward Structure
5 Results
5.1 Evolution of Strategies
5.2 Being Attentive
5.3 Ensemble Strategies
6 Conclusions
References
Analysis of Security Problems in Groups of Intelligent Sensors
1 Introduction
2 Analysis of Information Security Problems of the Internet of Things as a Group with Swarm Intelligence
3 Exploitation Vulnerabilities
4 Internet of Things and Lightweight Cryptography
5 The Tiny Encryption Algorithm Cipher Description
6 Speck Cipher Description
7 Experimental Research of Encryption Algorithms
8 Conclusion
References
Optimization of a High-Lift Mechanism Motion Generation Synthesis Using MHS
1 Introduction
2 High-Lift Mechanism
3 Optimization Problem and Constraint Handling
4 The Design Results
5 Conclusion and Discussion
References
Liminal Tones: Swarm Aesthetics and Materiality in Sound Art
1 Introduction
2 Methods
2.1 Concept
2.2 Model
3 Results
4 Discussion and Future Works
4.1 Order and Chaos
Sound as Emergence
4.2 Future Works
References
Study on the Random Factor of Firefly Algorithm
1 Introduction
2 Review of FA
2.1 Algorithm Idea
2.2 Model Analysis of FA
3 Research on the Random Factor Control Method of FA
3.1 Problem Analysis
3.2 New Control Method for the Random Factor
4 Experimental Results
4.1 Experiment Design
4.2 Results Analysis
4.3 Comparison with Other Decreasing Control Methods
4.4 Performance Comparison with Other Swarm Intelligence Algorithms
5 Conclusion
Preface
Organization
Contents
Part I
Contents
Part II
Swarm Intelligence and Nature-Inspired Computing
Swarm Unit Digital Control System Simulation
1 Introduction
2 Features of Von Neumann Computer Control
3 Semi-Markov Model of DC Operation
4 Example of Control System Analysis
5 Conclusion
References
Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams
1 Introduction
2 Related Work
2.1 Multi-agent Reinforcement Learning
2.2 Multi-agent Environments
3 Method
3.1 Modeling Observation of Opponents
3.2 Modeling Interactions with Teammates
3.3 Policy
3.4 Scalability and Real World Applicability
3.5 Training
4 Environment
4.1 Observation Space
4.2 Action Space
4.3 Reward Structure
5 Results
5.1 Evolution of Strategies
5.2 Being Attentive
5.3 Ensemble Strategies
6 Conclusions
References
Analysis of Security Problems in Groups of Intelligent Sensors
1 Introduction
2 Analysis of Information Security Problems of the Internet of Things as a Group with Swarm Intelligence
3 Exploitation Vulnerabilities
4 Internet of Things and Lightweight Cryptography
5 The Tiny Encryption Algorithm Cipher Description
6 Speck Cipher Description
7 Experimental Research of Encryption Algorithms
8 Conclusion
References
Optimization of a High-Lift Mechanism Motion Generation Synthesis Using MHS
1 Introduction
2 High-Lift Mechanism
3 Optimization Problem and Constraint Handling
4 The Design Results
5 Conclusion and Discussion
References
Liminal Tones: Swarm Aesthetics and Materiality in Sound Art
1 Introduction
2 Methods
2.1 Concept
2.2 Model
3 Results
4 Discussion and Future Works
4.1 Order and Chaos
Sound as Emergence
4.2 Future Works
References
Study on the Random Factor of Firefly Algorithm
1 Introduction
2 Review of FA
2.1 Algorithm Idea
2.2 Model Analysis of FA
3 Research on the Random Factor Control Method of FA
3.1 Problem Analysis
3.2 New Control Method for the Random Factor
4 Experimental Results
4.1 Experiment Design
4.2 Results Analysis
4.3 Comparison with Other Decreasing Control Methods
4.4 Performance Comparison with Other Swarm Intelligence Algorithms
5 Conclusion