Coevolutionary Computation and Its Applications (Natural Computing Series)

Yao, Xin/ Chong, Siang Yew

Springer Nature Switzerland AG（2025/04発売）

• 製本 Hardcover:ハードカバー版／ページ数 406 p.
• 言語 ENG
• 商品コード 9789819628407

Full Description

This book introduces the fundamentals of Coevolutionary Computation and presents new methodologies that are developed and then employed for modern real-world problem-solving in various applications across different domains. It is structured in three main parts to support the anticipated general and frequent usage of the book. In particular, the reader is able to obtain a quick and general introduction on the principles of coevolution in Part I, and then go over in detail the specifics how coevolutionary principles are exploited and applied to solve specific problems in the relevant chapters of Parts II and III. In this manner, Part I will introduce the fundamentals in Coevolutionary Computation with no assumption made on familiarity with Evolutionary Computation literature. These fundamentals include key concepts and operational principles of both evolutionary and coevolutionary processes that are modelled as iterative algorithms and systems implementable in computing machines. Parts II and III contain various applications of coevolution to problems that are framed in the context of optimization and learning, respectively. Detailed procedural implementations are provided for those methodologies as well as analysis that highlight the improvements they bring about over conventional techniques.  

Contents

Part I Coevolutionary Computation Fundamentals, Applications, and Challenges.- Chapter 1 Evolutionary Computation: An Overview.- Chapter 2 Introduction to Coevolutionary Computation.- Chapter 3  Principal Approaches of Coevolution: Competitive and Cooperative.- Chapter 4 Applications of Coevolution in Real World Problem Solving.- Chapter 5 Pathologies and Analysis in Coevolutionary Search.- Part II Coevolutionary Computation on Optimization Problems.- Chapter 6 Coevolutionary Construction of Parallel Algorithm Portfolio Optimization.- Chapter 7 Cooperative Coevolution for Large Scale Optimization.- Chapter 8 High Dimensional Optimization as Computationally Expensive Optimization.- Chapter 9 Design Space Exploration for Multimode Dataflow Mapping.- Chapter 10 Cooperative Coevolutionary Design Optimization in Concurrent Engineering.- Part III Coevolutionary Computation on Learning Problems.- Chapter 11 Coevolutionary Learning in Noncooperative Games.- Chapter 12 Generalization in Coevolutionary Learning.- Chapter 13 Impact of Problem Structures in Coevolution.