Call for Book Chapters

COLLECTIVE INTELLIGENCE: The Rise of Swarm Systems and their Impact on Society

Editors:

• Prof. Dr. Uwe Seebacher (University of Applied Sciences Munich, uwe.seebacher@hm.edu)
• Dr.-Ing. Christoph Legat (Augsburg Technical University of Applied Sciences, christoph.legat@hs-augsburg.de)

Theme

The book delves into cutting-edge concepts of swarm intelligence and its versatile applications across industries, with a special focus on the realm of artificial intelligence. It transcends the conventional view of swarm intelligence as a mechanism for coordinating group behavior, instead showcasing its potential to craft more efficient, sustainable systems in the modern age. Notably, the book presents an exclusive exploration of swarm intelligence's role in shaping the trajectory of autonomous systems, leveraging recent breakthroughs in multi-agent systems, artificial intelligence, and predictive intelligence research. By orchestrating predictive collaboration and emergent behavior, swarm intelligence enhances autonomous system performance across domains, as exemplified through real-world instances in various industrial sectors. By seeking a diverse array of contributions, we want to create a well-rounded and insightful book that covers a wide spectrum of topics related to collective intelligence and its far-reaching implications.

Potential topics are (but not limited to)

• Fundamentals of Swarm Intelligence
  • Definition, origins, and principles of swarm intelligence.
  • Comparison of swarm intelligence with other AI and collective behavior paradigms.
  • Biological inspiration: Studying how natural swarms function and collaborate.
• Advanced Swarm Algorithms:
  • Exploration of different types of swarm algorithms (particle swarm optimization, ant colony optimization, etc.).
  • Evolution of swarm algorithms: From basic to advanced techniques.
  • Adaptive swarm algorithms that learn and adapt to changing environments.
• (Industry-specific) Applications and Implementations in Autonomous Systems:
  • Role of swarm intelligence in autonomous systems in different industries like autonomous vehicles, drones, robotics, etc.
  • Swarm-based decision-making and navigation in complex environments.
  • Achieving swarm-based coordination in Internet of Things (IoT) ecosystems.
  • Swarm intelligence in manufacturing and supply chain optimization.
  • Smart agriculture: Using swarms for precision farming and crop monitoring.
  • Swarm algorithms for energy grid optimization and smart cities.
  • In-depth analysis of successful swarm intelligence deployments across industries.
  • Real-world examples of companies harnessing swarm intelligence for competitive advantage incl. lessons learned, challenges faced, and achieved outcomes
• Predictive Intelligence and Data Analytics:
  • Utilizing swarm intelligence for predictive modeling and data-driven insights.
  • Swarm-based data clustering and classification in diverse datasets.
  • Forecasting trends and patterns through swarm-driven predictive analytics.
• Industrial Disruption, Innovation and Digital Transformation:
  • Case studies on industry life cycle evaluations using swarm intelligence.
  • Identifying disruptive opportunities and potential paradigm shifts.
• Human-Swarm Interaction and Collaboration:
  • Human-guided swarms: Enhancing human-machine collaboration.
  • Swarm-based problem-solving platforms for crowdsourcing and collective intelligence.
  • Ethical considerations and challenges in human-swarm interaction.
• Emergent Behavior and Complexity:
  • Understanding emergent behavior in swarm systems and its implications.
  • Modeling complex phenomena through swarm simulations and experiments.
  • Swarm-driven innovation in fields like art, design, and architecture.
• Future Frontiers and Ethical Dimensions:
  • Emerging trends in swarm intelligence research and potential breakthroughs.
  • Ethical considerations in swarm algorithms and decision-making processes.
  • The role of swarm intelligence in shaping AI ethics and responsible technology.

Target audience

1. Researchers and academics in the fields of computer science, business informatics, engineering, and artificial intelligence who are interested in the latest developments.
2. Professionals in various industries, such as manufacturing, transportation, healthcare, and agriculture, who are looking to improve their systems and processes through the application of swarm intelligence.
3. Entrepreneurs and innovators who are interested in using swarm intelligence to develop new technologies, products, and services.
4. Students and educators who are studying topics related to artificial intelligence, machine learning, and autonomous systems.
5. Policy makers and government officials who are interested in the potential of swarm intelligence to address social and environmental challenges.
6. General readers who are interested in learning more about the latest advancements in technology and how they are shaping the world around us.

Deadlines

Sep 30th, 2023        Submission of abstracts (500 words)

Oct 31st, 2023         Submission of initial version 

Nov 21st, 2023        Notification of acceptance incl. review comments

Dec 12th, 2023        Submission of revised final versions

Page length and formatting

Contributions are expected to typically 15 to 20 pages in length (excluding references) when applying the CRC Press formatting instructions. Contributions should be original and not be submitted elsewhere. 

Submission

Abstract and chapters (Microsoft Word) should be submitted via easyChair. No publication fees or hidden costs.

Publication

The book is planned to be published by CRC Press, Taylor & Francis Group, LLC.