Kalyanmoy Deb

Swagatam Das

Arnab Bhattacharya

Kay Chen Tan

Nirupam Chakraborti

Joydeep Dutta

Juergen Branke

Partha Chakroborty

Santosh K. Gupta

Ashu Jain

Varun Aggarwal

Sushil J. Louis

evolutionary - gorithms. Manindra Agrawal's talk on “PRIMES is in P” provided a mu- improved version of his celebrated and ground-breaking 2002 work on poly- mial time algorithm for testing prime numbers. The theoretical computation work presented in this keynote lecture should be motivating for the evolutionary optimization and machine learning community at large.

8th International Conference, SEAL 2010, Kanpur, India, December 1-4, 2010, Proceedings

Simulated Evolution and Learning

Yaochu Jin

Hisao Ishibuchi

Ke Tang

Peter Whigham

Yuhui Shi

Xiaodong Li

Mengjie Zhang

Lam Thu Bui

Will N. Browne

Pramod Singh

Grant Dick

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings

Tong Heng Lee

Eik Fun Khor

Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. Covers the authors’ recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.

Multiobjective Evolutionary Algorithms and Applications

Ying Tan

Qingfu Zhang

Martin Middendorf

This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.

11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings

Keshav Dahal

Peter I. Cowling

Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.

Evolutionary Scheduling

Dikai Liu

Lingfeng Wang

With the increasing applications of intelligent robotic systems in various ?elds, the - sign and control of these systems have increasingly attracted interest from researchers. This edited book entitled “Design and Control of Intelligent Robotic Systems” in the book series of “Studies in Computational Intelligence” is a collection of some advanced research on design and control of intelligent robots. The works presented range in scope from design methodologies to robot development. Various design approaches and al- rithms, such as evolutionary computation, neural networks, fuzzy logic, learning, etc. are included. We also would like to mention that most studies reported in this book have been implemented in physical systems. An overview on the applications of computational intelligence in bio-inspired robotics is given in Chapter 1 by M. Begum and F. Karray, with highlights of the recent progress in bio-inspired robotics research and a focus on the usage of computational intelligence tools to design human-like cognitive abilities in the robotic systems. In Chapter 2, Lisa L. Grant and Ganesh K. Venayagamoorthy present greedy search, particle swarm optimization and fuzzy logic based strategies for navigating a swarm of robots for target search in a hazardous environment, with potential applications in high-risk tasks such as disaster recovery and hazardous material detection.

Design and Control of Intelligent Robotic Systems

Yew-Soon Ong

Chi-Keong Goh

The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.

Multi-Objective Memetic Algorithms

Yew Soon Ong

Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.

Issues and Algorithms

Evolutionary Multi-objective Optimization in Uncertain Environments

Jian Pei

Longbing Cao

Vincent S. Tseng

Jiuyong Li

Can Wang

Bo Liu

This book constitutes the refereed proceedings at PAKDD Workshops 2013, affiliated with the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Gold Coast, Australia in April 2013. The 47 revised full papers presented were carefully reviewed and selected from 92 submissions. The workshops affiliated with PAKDD 2013 include: Data Mining Applications in Industry and Government (DMApps), Data Analytics for Targeted Healthcare (DANTH), Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE), Biologically Inspired Techniques for Data Mining (BDM), Constraint Discovery and Application (CDA), Cloud Service Discovery (CloudSD).

PAKDD 2013 Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Golden Coast, QLD, Australia, Revised Selected Papers

Trends and Applications in Knowledge Discovery and Data Mining

Hisashi Handa

This book contains a collection of the papers accepted in the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014), which was held in Singapore from 10-12th November 2014. The papers contained in this book demonstrate notable intelligent systems with good analytical and/or empirical results.

Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems

Kay Chen Tan

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