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Explains how to build useful tools for searching collections of text and other media.
A Symbolic and Connectionist Approach To Legal Information Retrieval
Many existing information retrieval (IR) systems are surprisingly ineffective at finding documents relevant to particular topics. Traditional systems are extremely brittle, failing to retrieve relevant documents unless the user's exact search string is found. They support only the most primitive trial-and-error interaction with their users and are also static. Even systems with so-called "relevance feedback" are incapable of learning from experience with users. SCALIR (a Symbolic and Connectionist Approach to Legal Information Retrieval) -- a system for assisting research on copyright law -- has been designed to address these problems. By using a hybrid of symbolic and connectionist artifici...
Philosophy and Simulation
In this groundbreaking book, Manuel DeLanda analyzes different genres of simulation, from cellular automata and generic algorithms to neural nets and multi-agent systems, as a means to conceptualize the space of possibilities associated with casual and other capacities. This remarkably clear philosophical discussion of a rapidly growing field, from a thinker at the forefront of research at the interface of science and the humanities, is a must-read for anyone interested in the philosophies of technology, emergence and science at all levels.
The Garden in the Machine
What is life? Is it just the biologically familiar--birds, trees, snails, people--or is it an infinitely complex set of patterns that a computer could simulate? What role does intelligence play in separating the organic from the inorganic, the living from the inert? Does life evolve along a predestined path, or does it suddenly emerge from what appeared lifeless and programmatic? In this easily accessible and wide-ranging survey, Claus Emmeche outlines many of the challenges and controversies involved in the dynamic and curious science of artificial life. Emmeche describes the work being done by an international network of biologists, computer scientists, and physicists who are using compute...
Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence
This book constitutes, together with its companion, LNCS 2085, the refereed proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, held in Granada, Spain, in June 2001. The 200 revised papers presented were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in sections on foundations of connectionism, biophysical models of neurons, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, artificial intelligence and congnitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.
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.
Artificial War: Multiagent-based Simulation Of Combat
Military conflicts, particularly land combat, possess the characteristics of complex adaptive systems: combat forces are composed of a large number of nonlinearly interacting parts and are organized in a dynamic command-and-control network; local action, which often appears disordered, self-organizes into long-range order; military conflicts, by their nature, proceed far from equilibrium; military forces adapt to a changing combat environment; and there is no master “voice” that dictates the actions of every soldier (i.e., battlefield action is decentralized). Nonetheless, most modern “state of the art” military simulations ignore the self-organizing properties of combat.This book su...
Imitation in Animals and Artifacts
An interdisciplinary overview of current research on imitation in animals and artifacts.
Truth from Trash
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. 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...
The Simple Genetic Algorithm
Content Description #"A Bradford book."#Includes bibliographical references (p.) and index.
