This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are "multimodal" by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as "niching" methods, because of the nature-inspired "niching" effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

This book introduces readers to using the simple but effective Zhang-gradient (ZG) method to solve tracking-control problems concerning various nonlinear systems, while also highlighting the applications of the ZG method to tracking control for practical systems, e.g. an inverted-pendulum-on-a-cart (IPC) system and a two-wheeled mobile robot (showing its potential applications). In addition to detailed theoretical analyses of ZG controllers, the book presents a wealth of computer simulations to demonstrate the feasibility and efficacy of the controllers discussed (as well as the method itself). More importantly, the superiority of ZG controllers in overcoming the division-by-zero (DBZ) problem is also illustrated. Given its scope and format, the book is well suited for undergraduate and graduate students, as well as academic and industrial researchers in the fields of neural dynamics/neural networks, nonlinear control, computer mathematics, time-varying problem solving, modeling and simulation, analog hardware, and robotics.

This book constitutes the proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, AI 2018, held in Wellington, New Zealand, in December 2018. The 50 full and 26 short papers presented in this volume were carefully reviewed and selected from 125 submissions. The paper were organized in topical sections named: agents, games and robotics; AI applications and innovations; computer vision; constraints and search; evolutionary computation; knowledge representation and reasoning; machine learning and data mining; planning and scheduling; and text mining and NLP.

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.

We are pleased to present this LNCS volume, the Proceedings of the 22nd A- tralasianJointConferenceonArti?cialIntelligence(AI2009), heldinMelbourne, Australia, December 1-4,2009.This long established annual regionalconference is a forum both for the presentation of researchadvances in arti?cial intelligence and for scienti?c interchange amongst researchers and practitioners in the ?eld of arti?cial intelligence. Conference attendees were also able to enjoy AI 2009 being co-located with the Australasian Data Mining Conference (AusDM 2009) and the 4th Australian Conference on Arti?cial Life (ACAL 2009). This year AI 2009 received 174 submissions, from authors of 30 di?erent countries. After an extensive peer review process where each submitted paper was rigorously reviewed by at least 2 (and in most cases 3) independent revi- ers, the best 68 papers were selected by the senior Program Committee for oral presentation at the conference and included in this volume, resulting in an - ceptance rate of 39%. The papers included in this volume cover a wide range of topics in arti?cial intelligence: from machine learning to natural language s- tems, from knowledge representation to soft computing, from theoretical issues to real-world applications. AI 2009 also included 11 tutorials, available through the First Australian Computational Intelligence Summer School (ACISS 2009). These tutorials - some introductory, some advanced - covered a wide range of research topics within arti?cial intelligence, including data mining, games, evolutionary c- putation, swarm optimization, intelligent agents, Bayesian and belief networks

This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning, held December 7-10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world

This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006.

The 117 revised full papers presented were carefully reviewed and selected from 420 submissions. The papers are organized in topical sections on evolutionary learning, evolutionary optimisation, hybrid learning, adaptive systems, theoretical issues in evolutionary computation, and real-world applications of evolutionary computation techniques.

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are "multimodal" by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as "niching" methods, because of the nature-inspired "niching" effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

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.

This book constitutes the refereed proceedings of the 30th Australasian Joint Conference on Artificial Intelligence, AI 2017, held in Melbourne, VIC, Australia, in August 2017. The 29 full papers were carefully reviewed and selected from 58 submissions. This volume covers a wide spectrum of research streams in artificial intelligence ranging from machine learning, optimization to big data science and their practical applications.

This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 47 submissions. They were organized in topical sections named: artificial life and computational intelligence and optimization algorithms and applications.

This book constitutes the proceedings of the 10th International Conference on Swarm Intelligence, ANTS 2016, held in Brussels, Belgium, in September 2016. The 18 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 47 submissions. They are devoted to the field of swarm intelligence as a whole, without any bias towards specific research directions.

This book constitutes the proceedings of the Second Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2016, held in Canberra, ACT, Australia, in February 2016. The 30 full papers presented in this volume were carefully reviewed and selected from 41 submissions. They are organized in topical sections named: mathematical modeling and theory; learning and optimization; planning and scheduling; feature selection; and applications and games.

This book discusses phase selective and morphology controllable processing of titania (TiO2) nanocrystals and their enhanced functionality via doping for photo-catalytic, luminescent, and magnetic applications. Materials synthesis has been achieved by two "extreme" techniques: low temperature soft-chemical processing (typically <250 DegreesC) and high temperature RF (Radio frequency) thermal plasma processing (typically above 10,000 DegreesC). It is demonstrated that anatase, rutile and even the brookite polymorph of TiO2 can all be selectively synthesised in a phase-pure form via solution processing, sometimes even under near atmospheric conditions. Processing factors that govern phase structure and crystal morphology of the products are discussed. Detailed characterisations are given to the brookite phase with regard to its physio-chemical properties and its irreversible phase transition to rutile. It is also shown that quasi-equiaxed rutile nanocrystals, a morphological form rather difficult to make, can be obtained from Degussa P25 via a hydrothermal crystallisation/phase transformation process.

COVID-19 is a severe and complex epidemic ravaging many countries. Traditional Chinese medicine (TCM) has accumulated rich experience and achieved outstanding effects in its struggle against epidemics for thousands of years. As an essential intervention means for prevention and control of COVID-19, TCM boasts significant effects in relieving fever symptoms, slowing down disease progression, preventing disease transformation, reducing hormone dosage, and alleviating complications. Establishing and improving the emergency supply service mode of Chinese medicine in response to public health emergencies, and scientifically managing and allocating Chinese medicine medical resources are conducive to establishing a green channel for the emergency supply of Chinese medicine in response to major public health emergencies. This book focuses on the four oral Chinese patent medicines used in the clinical treatment period based on the Guidelines for the Diagnosis and Treatment of COVID-19 by the National Health Commission and National Administration of Traditional Chinese Medicine of China. This work is not only an important part of the theoretical system of TCM treatment based on syndrome differentiation but also an effective way to promote an even deeper integration of clinical pharmaceutical service and clinical medical practice.

This book introduces the current state of research on dark energy. It consists of three parts. The first part is for preliminary knowledge, including general relativity, modern cosmology, etc. The second part reviews major theoretical ideas and models of dark energy. The third part reviews some observational and numerical works. The aim of this book is to provide a sufficient level of understanding of dark energy problems, so that the reader can both get familiar with this area quickly and also be prepared to tackle the scientific literature on this subject. It will be useful for graduate students and researchers who are interested in dark energy.