Toward a Practice of Autonomous Systems --Proc. of the First European Conference on Artificial Life, edited by F. Varela and P. Bourgine, The MIT Press, 1992, ISBN 0 262 72019 1, 515 pp.

Statistical physics has proven to be a fruitful framework to describe phenomena outside the realm of traditional physics. Recent years have witnessed an attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. A wide list of topics are reviewed ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading. The connections between these problems and other, more traditional, topics of statistical physics are highlighted. Comparison of model results with empirical data from social systems are also emphasized.

Toward a Practice of Autonomous Systems

Statistical physics of social dynamics

I What Are the Ages of My Three Sons?.- 1 Why Are Some Problems Difficult to Solve?.- II How Important Is a Model?.- 2 Basic Concepts.- III What Are the Prices in 7-11?.- 3 Traditional Methods - Part 1.- IV What Are the Numbers?.- 4 Traditional Methods - Part 2.- V What's the Color of the Bear?.- 5 Escaping Local Optima.- VI How Good Is Your Intuition?.- 6 An Evolutionary Approach.- VII One of These Things Is Not Like the Others.- 7 Designing Evolutionary Algorithms.- VIII What Is the Shortest Way?.- 8 The Traveling Salesman Problem.- IX Who Owns the Zebra?.- 9 Constraint-Handling Techniques.- X Can You Tune to the Problem?.- 10 Tuning the Algorithm to the Problem.- XI Can You Mate in Two Moves?.- 11 Time-Varying Environments and Noise.- XII Day of the Week of January 1st.- 12 Neural Networks.- XIII What Was the Length of the Rope?.- 13 Fuzzy Systems.- XIV Everything Depends on Something Else.- 14 Coevolutionary Systems.- XV Who's Taller?.- 15 Multicriteria Decision-Making.- XVI Do You Like Simple Solutions?.- 16 Hybrid Systems.- 17 Summary.- Appendix A: Probability and Statistics.- A.1 Basic concepts of probability.- A.2 Random variables.- A.2.1 Discrete random variables.- A.2.2 Continuous random variables.- A.3 Descriptive statistics of random variables.- A.4 Limit theorems and inequalities.- A.5 Adding random variables.- A.6 Generating random numbers on a computer.- A.7 Estimation.- A.8 Statistical hypothesis testing.- A.9 Linear regression.- A.10 Summary.- Appendix B: Problems and Projects.- B.1 Trying some practical problems.- B.2 Reporting computational experiments with heuristic methods.- References.

/pdf/how-to-solve-it-modern-heuristics-1pu40hrf57.pdf

How to Solve It: Modern Heuristics

This paper describes a novel system for creating virtual creatures that move and behave in simulated three-dimensional physical worlds. The morphologies of creatures and the neural systems for controlling their muscle forces are both generated automatically using genetic algorithms. Different fitness evaluation functions are used to direct simulated evolutions towards specific behaviors such as swimming, walking, jumping, and following.A genetic language is presented that uses nodes and connections as its primitive elements to represent directed graphs, which are used to describe both the morphology and the neural circuitry of these creatures. This genetic language defines a hyperspace containing an indefinite number of possible creatures with behaviors, and when it is searched using optimization techniques, a variety of successful and interesting locomotion strategies emerge, some of which would be difficult to invent or built by design.

/pdf/evolving-virtual-creatures-4dl0f8717o.pdf

Evolving virtual creatures

Evolutionary Computation 1 : Basic Algorithms and Operator

From the Publisher:
Artificial life, a field that seeks to increase the role of synthesis in the study of biological phenomena, has great potential, both for unlocking the secrets of life and for raising a host of disturbing issues -- scientific and technical as well as philosophical and ethical. This book brings together a series of overview articles that appeared in the first three issues of the groundbreaking journal Artificial Life, along with a new introduction by Christopher Langton, Editor-in-Chief of Artificial Life, founder of the discipline, and Director of the Artificial Life Program at the Santa Fe Institute.

Toward a Practice of Autonomous Systems

Citations

Statistical physics of social dynamics

How to Solve It: Modern Heuristics

Evolving virtual creatures

Evolutionary Computation 1 : Basic Algorithms and Operator

Artificial Life: An Overview

Related Papers (5)

Adaptation in natural and artificial systems

Genetic algorithms in search, optimization and machine learning

Genetic Programming: On the Programming of Computers by Means of Natural Selection

Intelligence without representation

A robust layered control system for a mobile robot