ECAL 2013, the twelfth European Conference on Artificial Life, presents the current state of the art of a mature and autonomous discipline collocated at the intersection of a theoretical perspective (the scientific explanations of different levels of life organizations, e.g., molecules, compartments, cells, tissues, organs, organisms, societies, collective and social phenomena) and advanced technological applications (bio-inspired algorithms and techniques to building-up concrete solutions such as in robotics, data analysis, search engines, gaming).
These are the Proceedings of Artificial Life 13, the Thirteenth International Conference on the Simulation and Synthesis of Living Systems (http://alife13.org/), hosted by the BEACON Center for the Study of Evolution in Action (http://beacon-center.org/) at Michigan State University in East Lansing, Michigan, on July 19-22, 2012.
Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes. The young field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction.
The biannual International Conference on the Simulation of Adaptive Behavior brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, engineering, and related fields to advance the understanding of behaviors and underlying mechanisms that allow natural and synthetic agents (animats) to adapt and survive in uncertain environments.
There is increasing interest in genetic programming by both researchers and professional software developers. These twenty-two invited contributions show how a wide variety of problems across disciplines can be solved using this new paradigm.
The term "artificial life" describes research into synthetic systems that possess some of the essential properties of life. This interdisciplinary field includes biologists, computer scientists, physicists, chemists, geneticists, and others. Artificial life may be viewed as an attempt to understand high-level behavior from low-level rules—for example, how the simple interactions between ants and their environment lead to complex trail-following behavior.
The Simulation of Adaptive Behavior Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, computer science, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow adaptation and survival in uncertain environments.
The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots.
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments.
The Animals to Animats Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow natural and synthetic agents (animats) to adapt and survive in uncertain environments.
The term "artificial life" describes research into synthetic systems that possess some of the essential properties of life. This truly interdisciplinary field includes biologists, computer scientists, physicists, chemists, geneticists, and others. Artificial life may be viewed as an attempt to understand high-level behavior from low-level rules—for example, how the simple interactions between ants and their environment lead to complex trail-following behavior.
This study of learning in autonomous agents offers a bracing intellectual adventure. Chris Thornton makes the compelling claim that learning is not a passive discovery operation but an active process involving creativity on the part of the learner. Although theorists of machine learning tell us that all learning methods contribute some form of bias and thus involve a degree of creativity, Thornton carries the idea much further. He describes an incremental process, recursive relational learning, in which the results of one learning step serve as the basis for the next.
Can there be a science of consciousness? This issue has been the focus of three landmark conferences sponsored by the University of Arizona in Tucson. The first two conferences and books have become touchstones for the field. This volume presents a selection of invited papers from the third conference. It showcases recent progress in this maturing field by researchers from philosophy, neuroscience, cognitive psychology, phenomenology, and physics.
Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable time- and cost-effective applications. It does this by breeding programs over many generations, using the principles of natural selection, sexual recombination, and mutuation. This third volume of Advances in Genetic Programming highlights many of the recent technical advances in this increasingly popular field.
It is now clear that the brain is unlikely to be understood without recourse to computational theories. The theme of An Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently been extended in ways that make them useful for describing the brain's programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models.
The Animals to Animats Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow natural and synthetic agents (animats) to adapt and survive in uncertain environments.
The term "artificial life" describes research into synthetic systems that possess some of the essential properties of life. This truly interdisciplinary effort includes biologists, computer scientists, physicists, chemists, geneticists, and others. The field may be viewed as an attempt to understand high-level behavior from low-level rules—for example, how the simple interactions between ants and their environment lead to complex trail-following behavior.
The concept of fuzzy sets is one of the most fundamental and influential tools in computational intelligence. Fuzzy sets can provide solutions to a broad range of problems of control, pattern classification, reasoning, planning, and computer vision. This book bridges the gap that has developed between theory and practice. The authors explain what fuzzy sets are, why they work, when they should be used (and when they shouldn't), and how to design systems using them.
What is consciousness? Recent attempts to answer this question have motivated two interdisciplinary conferences sponsored by the University of Arizona in Tucson. The first volume of Toward a Science of Consciousness is now considered a resource book for the emerging field. This volume presents a selection of invited papers from the second conference, held in April 1996. The book's fifteen sections demonstrate the broad range of fields now focusing on consciousness.
Researchers in artificial life attempt to use the physical representation of lifelike phenomena to understand the organizational principles underlying the dynamics of living systems. The goal of the 1997 European Conference on Artificial Life is to provoke new understandings of the relationships between the natural and the artificial. Topics include self-organization, the origins of life, natural selection, evolutionary computation, neural networks, communication, artificial worlds, software agents, philosophical issues in artificial life, ethical problems, and learning and development.
Despite all the successes in computer engineering, adaptive computation, bottom-up AI, and robotics, Artificial Life must not become simply a one-way bridge, borrowing biological principles to enhance our engineering efforts in the construction of life-as-it-could-be. We must ensure that we give back to biology in kind, by developing tools and methods that will be of real value in the effort to understand life-as-it-is.
For the past twenty years Scott Kelso's research has focused on extending the physical concepts of self- organization and the mathematical tools of nonlinear dynamics to understand how human beings (and human brains) perceive, intend, learn, control, and coordinate complex behaviors. In this book Kelso proposes a new, general framework within which to connect brain, mind, and behavior.
