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Recruitment Learning
This book presents a fascinating and self-contained account of "recruitment learning", a model and theory of fast learning in the neocortex. In contrast to the more common attractor network paradigm for long- and short-term memory, recruitment learning focuses on one-shot learning or "chunking" of arbitrary feature conjunctions that co-occur in single presentations. The book starts with a comprehensive review of the historic background of recruitment learning, putting special emphasis on the ground-breaking work of D.O. Hebb, W.A.Wickelgren, J.A.Feldman, L.G.Valiant, and L. Shastri. Afterwards a thorough mathematical analysis of the model is presented which shows that recruitment is indeed a...
Handbook of Environmental and Ecological Modeling
With descriptions of hundreds of the most important environmental and ecological models, this handbook is a unique and practical reference source. The Handbook of Environmental and Ecological Modeling is ideal for those working in environmental modeling, including regulators and managers who wish to understand the models used to make assessments. Overviews of more than 360 models are easily accessed in this handbook, allowing readers to quickly locate information they need about models available in a given ecosystem. The material in the Handbook of Environmental and Ecological Modeling is logically arranged according to ecosystem. Each of the sixteen chapters of the handbook covers a particular ecosystem, and includes not only the descriptions of the models, but also an overview of the state-of-the-art in modeling for that particular ecosystem. A summary of the spectrum of available models is also provided in each chapter. The extensive table of contents and the easy-to-use index put materials immediately at your fingertips.
Uncertainty Theory
Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.
Intelligent Systems: From Theory to Practice
In the modern science and technology there are some research directions and ch- lenges which are at the forefront of world wide research activities because of their relevance. This relevance may be related to different aspects. First, from a point of view of researchers it can be implied by just an analytic or algorithmic difficulty in the solution of problems within an area. From a broader perspective, this re- vance can be related to how important problems and challenges in a particular area are to society, corporate or national competitiveness, etc. Needless to say that the latter, more global challenges are probably more decisive a driving force for s- ence seen from a global perspective. One of such “meta-challenges” in the present world is that of intelligent s- tems. For a long time it has been obvious that the complexity of our world and the speed of changes we face in virtually all processes that have impact on our life imply a need to automate many tasks and processes that have been so far limited to human beings because they require some sort of intelligence.
Intelligent Watermarking Techniques
Watermarking techniques involve the concealment of information withina text or images and the transmission of this information to thereceiver with minimum distortion. This is a very new area ofresearch. The techniques will have a significant effect on defence, business, copyright protection and other fields where informationneeds to be protected at all costs from attackers.This book presents the recent advances in the theory andimplementation of watermarking techniques. It brings together, for thefirst time, the successful applications of intelligent paradigms(including comparisons with conventional methods) in many areas. Theaccompanying CD-Rom provides readers with source codes and executablesto put into practice general topics in watermarking
Adaptive Representations for Reinforcement Learning
This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manually designed solution representations, agents that automatically adapt their own representations have the potential to dramatically improve performance. This book introduces two novel approaches for automatically discovering high-performing representations. The first approach synthesizes temporal difference methods, the traditional approach to reinforcement learning, with evolutionary methods, which can learn representations for a broad class of optimization problems. This synt...
Biometrics and ID Management
This book constitutes the thoroughly refereed proceedings of the COST 2101 International Workshop, BIOID 2011, held in Brandenburg (Havel), Germany, in March 2011. The 25 revised full papers presented were carefully reviewed and selected from numerous submissions and are completed by an introduction on COST. The papers are organized in topical main sections on theory and systems, handwriting authentication, speaker authentication, face recognition, multibiometric authentication, and on biometrics and forensics.
Natural Computing in Computational Finance
The chapters in this book illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. The eleven chapters were selected following a rigorous, peer-reviewed, selection process.
Computer Vision
Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University ...
