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Mark Bedau

Reed College
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  •  Publications
    63
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 More details
  • Reed College
    Department of Philosophy
    Retired faculty
Areas of Specialization
Science, Logic, and Mathematics
Metaphysics and Epistemology
Areas of Interest
Science, Logic, and Mathematics
Metaphysics and Epistemology
  • All publications (63)
  •  86
    1 Arti cial life's working hypothesis
    Arti cial life studies computer models of the processes characteristic of complex adaptive systems|processes like self-organization, self-reproduction, adaptation, and evolution. Complex adaptive systems take many forms, each of which di ers from the others in myriad ways. By abstracting away from the diverse details, arti cial life hopes to reveal fundamental principles governing broad classes of complex adaptive systems. This hope rests on arti cial life's working hypoth-.
    Artificial LifeComplexity in Biology
  •  52
    The Evolution of Complexity
    In Barberousse Anouk, M. Morange & T. Pradeau (eds.), Mapping the Future of Biology. Boston Studies in the Philosophy of Science, vol 266, Springer. 2009.
    Complexity in BiologyComplexity
  •  598
    Effect of Environmental Structure on Evolutionary Adaptation
    with Jeffrey A. Fletcher and Martin Zwick
    In Jeffrey A. Fletcher, Mark A. Bedau & Martin Zwick (eds.), Effect of Environmental Structure on Evolutionary Adaptation, . pp. 189-198. 1998.
    This paper investigates how environmental structure, given the innate properties of a population, affects the degree to which this population can adapt to the environment. The model we explore involves simple agents in a 2-d world which can sense a local food distribution and, as specified by their genomes, move to a new location and ingest the food there. Adaptation in this model consists of improving the genomic sensorimotor mapping so as to maximally exploit the environmental resources. We va…Read more
    This paper investigates how environmental structure, given the innate properties of a population, affects the degree to which this population can adapt to the environment. The model we explore involves simple agents in a 2-d world which can sense a local food distribution and, as specified by their genomes, move to a new location and ingest the food there. Adaptation in this model consists of improving the genomic sensorimotor mapping so as to maximally exploit the environmental resources. We vary environmental structure to see its specific effect on adaptive success. In our investigation, two properties of environmental structure, conditioned by the sensorimotor capacities of the agents, have emerged as significant factors in determining adaptive success: (1) the information content of the environment which quantifies the diversity of conditions sensed, and (2) the expected utility for optimal action. These correspond to the syntactic and pragmatic aspects of environmental information, respectively. We find that the ratio of expected utility to information content predicts adaptive success measured by population gain and information content alone predicts the fraction of ideal utility achieved. These quantitative methods and specific conclusions should aid in understanding the effects of environmental structure on evolutionary adaptation in a wide range of evolving systems, both artificial and natural.
    Evolutionary BiologyArtificial LifeNatural SciencesGeneral Philosophy of ScienceSocial SciencesPhilo…Read more
    Evolutionary BiologyArtificial LifeNatural SciencesGeneral Philosophy of ScienceSocial SciencesPhilosophy of Computing and InformationPhilosophy of Social ScienceValue Theory, MiscellaneousSocial and Political PhilosophyPhilosophy of Action, Misc
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