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Machine Learning and Adaptive Computation

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Next Generation Challenges and Future Directions

Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recognition, databases, and high performance computing, data mining extracts useful information from the large data sets now available to industry and science. This collection surveys the most recent advances in the field and charts directions for future research.

Proceedings of the Eighth International Conference on the Simulation of Adaptive Behavior

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.

The Biology, Intelligence, and Technology of Self-Organizing Machines

Evolutionary robotics is a new technique for the automatic creation of autonomous robots. Inspired by the Darwinian principle of selective reproduction of the fittest, it views robots as autonomous artificial organisms that develop their own skills in close interaction with the environment and without human intervention. Drawing heavily on biology and ethology, it uses the tools of neural networks, genetic algorithms, dynamic systems, and biomorphic engineering.


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 Adaptive Suspension Vehicle

What is 16 feet long, 10 feet high, weighs 6,000 pounds, has six legs, and can sprint at 8 mph and step over a 4 foot wall? The Adaptive Suspension Vehicle (ASV) described in this book.

Interpreting and Responding to Questions in Context

Modeling and Simulation with Incomplete Knowledge

This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past fifteen years for building and simulating qualitative models of physical systems—bathtubs, tea kettles, automobiles, the physiology of the body, chemical processing plants, control systems, electrical systems—where knowledge of that system is incomplete. The primary tool for this work is the author's QSIM algorithm, which is discussed in detail.

Proceedings of the Seventh International Conference on Simulation of Adaptive 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.

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