Richard A. Watson

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One common characterization of how simple hill climbing optimization methods can fail is that they become trapped in local op tima a state where no small modi cation of the current best solution will produce a solution that is better This measure of better depends on the performance of the solution with respect to the single objective be ing optimized In(More)
Epistasis for fitness means that the selective effect of a mutation is conditional on the genetic background in which it appears. Although epistasis is widely observed in nature, our understanding of its consequences for evolution by natural selection remains incomplete. In particular, much attention focuses only on its influence on the instantaneous rate(More)
We introduce Embodied Evolution (EE) as a new methodology for evolutionary robotics (ER). EE uses a population of physical robots that autonomously reproduce with one another while situated in their task environment. This constitutes a fully distributed evolutionary algorithm embodied in physical robots. Several issues identified by researchers in the(More)
vi List of Figures xiii List of Equations xvi List of Tables xvi Chapter 1 Accretive and compositional change in natural and artificial evolution 1 1.1 Exchange between evolutionary biology and evolutionary computation 2 1.1.1 Gradualism and the probability of large adaptive changes 2 1.1.2 Evolutionary adaptation and artificial optimisation methods 3 1.2(More)
Recombination in the Genetic Algorithm (GA) is supposed to enable the component characteristics from two parents to be extracted and then reassembled in different combinations – hopefully producing an offspring that has the good characteristics of both parents. However, this can only work if it is possible to identify which parts of each parent should be(More)
In contrast to terrestrial animals that function under hypoxic conditions but display the typical exercise response of increasing ventilation and cardiac output, marine mammals exercise under a different form of hypoxic stress. They function for the duration of a dive under progressive asphyxia, which is the combination of increasing hypoxia, hypercapnia(More)
One of the most controversial yet enduring hypotheses about what genetic algorithms (GAs) are good for concerns the idea that GAs process building-blocks. More specifically, it has been suggested that crossover in GAs can assemble short low-order schemata of above average fitness (building blocks) to create higher-order higher-fitness schemata. However,(More)