"Collectives and Design of Complex Systems" lays the foundation for the study of collective intelligence and how these entities can be developed to yield optimal performance. Partone describes how some information-processing problems can only be solved by the joint actions of large communities of computers, each running their own complex, decentralized machine-learning algorithms. Part two offers general analysis on the dynamics and structures of collectives. Finally, part three addresses economic,
model-free, and control-theory approaches to designing these complex systems. The work assumes a modest understanding of basic statistics and calculus.
Using an approach that integrates key theoretical principles with applications in real-world scenarios, this unique monograph surveys the latest research on the dynamics of collectives, their A.I. aspects, and critical design issues pertaining to them. Computer scientists, computer engineers, and all practitioners, researchers, and graduate students with an interest in this new and growing field will find the book an authoritative introduction and resource.
Computer science researchers, professionals, practitioners
- Adaptive computation
- Algorithm analysis
- Artificial intelligence
- Complexity theory
- Distributed systems
A survey of collectives.- Theory of collective intelligence.- On learnable mechanism design.- Asynchronous learning in decentralized environments.- Competition between adaptive agents.- Managing catastrophic changes in a collective.- Effects of inter-agent communications on the collective.- Man and superman--human limitations, innovation, and emergence in resource competition.- Design principles for the distributed control of modular self-reconfigurable robots.- Two paradigms for the design of artificial collectives.- Efficiency and equity in collective systems of interacting heterogeneous agents.- Selection in coevolutionary algorithms and the inverse problem.- Dynamics of large autonomous computational systems.- Index.