David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Biology and Philosophy 26 (2):223-250 (2011)
Markov models of evolution describe changes in the probability distribution of the trait values a population might exhibit. In consequence, they also describe how entropy and conditional entropy values evolve, and how the mutual information that characterizes the relation between an earlier and a later moment in a lineage’s history depends on how much time separates them. These models therefore provide an interesting perspective on questions that usually are considered in the foundations of physics—when and why does entropy increase and at what rates do changes in entropy take place? They also throw light on an important epistemological question: are there limits on what your observations of the present can tell you about the evolutionary past?
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References found in this work BETA
Elliott Sober (2008). Evidence and Evolution: The Logic Behind the Science. Cambridge University Press.
D. R. Brooks (1988). Evolution as Entropy: Toward a Unified Theory of Biology. University of Chicago Press.
Martin Barrett & Elliott Sober (1994). The Second Law of Probability Dynamics. British Journal for the Philosophy of Science 45 (4):941-953.
Bruce H. Weber, David J. Depew, James D. Smith & C. Dyke (1990). Entropy, Information and Evolution: New Perspectives on Physical and Biological Evolution. Behavior and Philosophy 18 (2):79-84.
Elliott Sober (1989). Independent Evidence About a Common Cause. Philosophy of Science 56 (2):275-287.
Citations of this work BETA
William Roche & Tomoji Shogenji (forthcoming). Information and Inaccuracy. British Journal for the Philosophy of Science:axw025.
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