Call for Chapters

Book Title: Agent-Based Evolutionary Search

Publisher: Springer


Over the last two decades, there has been an increase in the acceptance of Evolutionary Computation (EC) as a tool for solving complex real life decision making problems. EC does not require any pre-knowledge of the search space, and the use of EC can eliminate the need to satisfy necessary mathematical properties of functions and variables as required to apply conventional search processes. EC can be designed for parallel processing which is crucial to solve large problems within an affordable computational time.

A multi-agent system (MAS) is a paradigm of solving complex problems in which multiple interacting agents equipped with intelligent capabilities collectively solve the problem. Recently, multi-agent systems are increasingly being used for solving intractable problems. Agents of MAS have some of the basic properties such as autonomy, local view, sociability (communications), learning and adaptive ability.

The performances of EA’s have been enhanced by integrating features of MAS as evident in the literature. The agents can bring many interesting features in EAs which are beyond the scope of traditional evolutionary process and learning.

The aim of this volume is to reflect recent advances in the field, and increase the awareness of the computing community on the effectiveness of this technology. In particular, we endeavour to demonstrate the current state-of-the-art in the theory and practice of Agent based Evolutionary Search (AES). Topics of interest include (but are not limited to):

Chapter Submission

The chapters must be submitted to one of the editors. Chapters submitted for this book will be peer-reviewed. The chapter format is available in the Springer website. After the final decision is made, authors will receive a notification letter accompanied with the reports of the reviewers.

 
Editors

 Contact Emails: r.sarker@adfa.edu.au; t.ray@adfa.edu.au

 
Important Dates