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Genetic Programming

by John R. Koza , 1997
"... Introduction Genetic programming is a domain-independent problem-solving approach in which computer programs are evolved to solve, or approximately solve, problems. Genetic programming is based on the Darwinian principle of reproduction and survival of the fittest and analogs of naturally occurring ..."
Abstract - Cited by 1056 (12 self) - Add to MetaCart
genetic operations such as crossover (sexual recombination) and mutation. John Holland's pioneering Adaptation in Natural and Artificial Systems (1975) described how an analog of the evolutionary process can be applied to solving mathematical problems and engineering optimization problems using what

The Advantages of Evolutionary Computation

by David B. Fogel , 1997
"... Evolutionary computation is becoming common in the solution of difficult, realworld problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific ..."
Abstract - Cited by 541 (6 self) - Add to MetaCart
advantages include the flexibility of the procedures, as well as the ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine. 1 Introduction Darwinian evolution is intrinsically a robust search

The role of deliberate practice in the acquisition of expert performance

by K. Anders Ericsson, Ralf Th. Krampe, Clemens Tesch-romer - Psychological Review , 1993
"... The theoretical framework presented in this article explains expert performance as the end result of individuals ' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of ef ..."
Abstract - Cited by 690 (15 self) - Add to MetaCart
for a minimum of 10 years. Analysis of expert performance provides unique evidence on the potential and limits of extreme environmental adaptation and learning. Our civilization has always recognized exceptional individuals, whose performance in sports, the arts, and science is vastly superior

Formalising trust as a computational concept

by Stephen Paul Marsh , 1994
"... Trust is a judgement of unquestionable utility — as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say “I trust you, ” but what does that mean? T ..."
Abstract - Cited by 529 (6 self) - Add to MetaCart
Artificial Intelligence (DAI) is raised. The thesis presents a testbed populated by simple trusting agents which substantiates the utility of the formalism. The formalism provides a step in the direction of a proper understanding and definition of human trust. A contribution of the thesis is its detailed

Illusion and well-being: A social psychological perspective on mental health.

by Shelley E Taylor , Jonathon D Brown , Nancy Cantor , Edward Emery , Susan Fiske , Tony Green-Wald , Connie Hammen , Darrin Lehman , Chuck Mcclintock , Dick Nisbett , Lee Ross , Bill Swann , Joanne - Psychological Bulletin, , 1988
"... Many prominent theorists have argued that accurate perceptions of the self, the world, and the future are essential for mental health. Yet considerable research evidence suggests that overly positive selfevaluations, exaggerated perceptions of control or mastery, and unrealistic optimism are charac ..."
Abstract - Cited by 988 (20 self) - Add to MetaCart
receives negative feedback or is otherwise threatened and may be especially adaptive under these circumstances. Decades of psychological wisdom have established contact with reality as a hallmark of mental health. In this view, the well-adjusted person is thought to engage in accurate reality testing

Deleterious passengers in adapting populations

by Benjamin H. Good, Michael M. Desai
"... Most new mutations are deleterious and are eventually eliminated by natural selection. But in an adapting population, the rapid amplification of beneficial mutations can hinder the removal of deleterious variants in nearby regions of the genome, altering the patterns of sequence evolution. Here, we ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Most new mutations are deleterious and are eventually eliminated by natural selection. But in an adapting population, the rapid amplification of beneficial mutations can hinder the removal of deleterious variants in nearby regions of the genome, altering the patterns of sequence evolution. Here, we

Evolving 3D morphology and behavior by competition

by Karl Sims - Proceedings of Artificial Life IV , 1994
"... This paper describes a system for the evolution and co-evolution of virtual creatures that compete in physically simulated three-dimensional worlds. Pairs of individuals enter one-on-one contests in which they contend to gain control of a common resource. The winners receive higher relative fitness ..."
Abstract - Cited by 439 (0 self) - Add to MetaCart
, and the morphology and behavior can adapt to each other as they evolve simultaneously. The genotypes are structured as directed graphs of nodes and connections, and they can efficiently but flexibly describe instructions for the development of creatures ’ bodies and control systems with repeating or recursive

Adapting Populations of Agents

by Philippe De Wilde, Maria Chli, L. Correia, R. Ribeiro, P. Mariano, V. Abramov, J. Goossenaerts - LECTURE NOTES IN ARTIFICIAL INTELLIGENCE , 2003
"... We control a population of interacting software agents. The agents have a strategy, and receive a payoff for executing that strategy. Unsuccessful agents ..."
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We control a population of interacting software agents. The agents have a strategy, and receive a payoff for executing that strategy. Unsuccessful agents

AN ADAPTIVE POPULATION IMPORTANCE SAMPLER

by unknown authors
"... Monte Carlo (MC) methods are widely used in signal pro-cessing, machine learning and communications for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we ..."
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Monte Carlo (MC) methods are widely used in signal pro-cessing, machine learning and communications for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we

Cascades of Dynamical Transitions in an Adaptive Population

by H. M. Yang, Y. S. Ting, K. Y. Michael Wong , 2006
"... In an adaptive population that models financial markets and distributed control, we consider how the dynamics depends on the diversity of the agents ’ initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. This change in the environment ..."
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In an adaptive population that models financial markets and distributed control, we consider how the dynamics depends on the diversity of the agents ’ initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. This change in the environment
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