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Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Classifier systems are an intriguing approach to a broad range of machine learning problems, based on automated generation and evaluation of condi tion/action rules. Inreinforcement learning tasks they simultaneously address the two major problems of learning a policy and generalising over it (and re lated objects, such as value functions). Despite over 20 years of research, however, classifier systems have met with mixed success, for reasons which were often unclear. Finally, in 1995 Stewart Wilson claimed a long-awaited breakthrough with his XCS system, which differs from earlier classifier sys tems in a number of respects, the most significant of which is the way in which it calculates th...
From Animals to Animats 4
From Animals to Animats 4 brings together the latest research at the frontier of an exciting new approach to understanding intelligence.
Paleobotany and the Evolution of Plants
This 1993 textbook describes and explains the origin and evolution of plants as revealed by the fossil record.
Aircraft of WWII
A comprehensive directory of the aircraft that saw service during World War II with over 300 entries covering the fighters, bombers, aircraft, transport built in some 15 nations around the world.
An Introduction to Natural Computation
This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. 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 brains programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It stresses the broad spectrum of learning ...
Applications of Learning Classifier Systems
The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments? In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together? John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw a...
From Animals to Animats 5
The Animals to Animats Conference brings together researchers fromethology, psychology, ecology, artificial intelligence, artificiallife, robotics, engineering, and related fields to furtherunderstanding of the behaviors and underlying mechanisms that allownatural and synthetic agents (animats) to adapt and survive inuncertain environments 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 work presented focuses on well-defined models--robotic, computer-simulation, and mathematical--that help to characterize and compare various organizational principles or architectures underlying adaptive behavior in both natural animals and animats.
Learning Classifier Systems
Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.
Foundations of Learning Classifier Systems
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Spitfire
A dynamic look at one of the most famous fighters of WWII through a chronological history detailing the Supermarine Spitfire's career in a unique diary form. Supported by specially produced color artwork and extensive, easy-to-reference specification, performance and data tables. Traces the Spitfire's history from conception to phasing out of service, covering all versions of the Spitfire and Seafire. Softbound, 8 1/2" x 11", 184 pages, b&w and color ill.
