Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From this, an (...) information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

We argue against some of Reichenbach's claims about causal forks are incorrect. We do not see why the Second Law of Thermodynamics rules out the existence of conjunctive forks open to the past. In addition, we argue that a common effect rarely forms a conjunctive fork with its joint causes, but it sometimes does. Nevertheless, we think there is something to be said for Reichenbach's idea that forks of various kinds are relevant to explaining why we know more about the (...) past than about the future. And entropy turns out to play a role in the explanation, though not the determining role that Reichenbach envisions. (shrink)

The idea that the changing entropy of a system is relevant to explaining why we know more about the system's past than about its future has been criticized on several fronts. This paper assesses the criticisms and clarifies the epistemology of the inference problem. It deploys a Markov process model to investigate the relationship between entropy and temporally asymmetric inference.

It is well known that informational theories of representation have trouble accounting for error. Informational semantics is a family of theories attempting a naturalistic, unashamedly reductive explanation of the semantic and intentional properties of thought and language. Most simply, the informational approach explains truth-conditional content in terms of causal, nomic, or simply regular correlation between a representation and a state of affairs. The central work is Dretske, and the theory was largely developed at the University of Wisconsin by Fred Dretske, (...) Dennis Stampe, and Berent Enc. Recently, informational semantics has roamed far beyond its Wisconsin home, and built a sizeable collection of followers. Converts include Jerry Fodor, Robert Stalnaker and, less faithfully, Paul and Patricia Churchland and Hartry Field. But for some years informational semantics has been hounded by a problem with error – the classic presentation is Fodor – and no other problem has hounded the theory so persistently. (shrink)

A model of a Markov process is presented in which observing the present state of a system is asymmetrically related to inferring the system's future and inferring its past. A likelihood inference about the system's past state, based on observing its present state, is justified no matter what the parameter values in the model happen to be. In contrast, a probability inference of the system's future state, based on observing its present state, requires further information about the parameter values.

Information about the environment is captured in human biological systems on a variety of interacting levels – in distributions of genes, linguistic particulars, concepts, methods, theories, preferences, and overt behaviors. I investigate some of the basic principles which govern such a hierarchy by constructing a comparatively simple three-level selection model of bee foraging preferences and behaviors. The information-theoretic notion of ''''mutual information'''' is employed as a measure of efficiency in tracking a changing environment, and its appropriateness in epistemological applications is (...) discussed at some length. In particular, information accumulated in mid-level preference distributions exhibits suggestive properties for the purposes of naturalistic epistemology. It also appears that the novelty of scientific objects and representations and the rapidity of scientific change relative to genetic change need present no obstacle to the use of such models in explanations of scientific progress and the reliability of scientific judgement. (shrink)