Learning and selection

Are learning processes selection processes? This paper takes a slightly modified version of the account of selection presented in Hull et al. (Behav Brain Sci 24:511–527, 2001) and asks whether it applies to learning processes. The answer is that although some learning processes are selectional, many are not. This has consequences for teleological theories of mental content. According to these theories, mental states have content in virtue of having proper functions, and they have proper functions in virtue of being the products of selection processes. For some mental states, it is plausible that the relevant selection process is natural selection, but there are many for which it is not plausible. One response to this (due to David Papineau) is to suggest that the learning processes by which we acquire non-innate mental states are selection processes and can therefore confer proper functions on mental states. This paper considers two ways in which this response could be elaborated, and argues that neither of them succeed: the teleosemanticist cannot rely on the claim that learning processes are selection processes in order to justify the attribution of proper functions to beliefs

An Evolutionary Framework for Culture: Selectionism versus Communal Exchange

Dawkins' replicator-based conception of evolution has led to widespread mis-application selectionism across the social sciences because it does not address the paradox that inspired the theory of natural selection in the first place: how do organisms accumulate change when traits acquired over their lifetime are obliterated? This is addressed by von Neumann's concept of a self-replicating automaton (SRA). A SRA consists of a self-assembly code that is used in two distinct ways: (1) actively deciphered during development to construct a self-similar replicant, and (2) passively copied to the replicant to ensure that it can reproduce. Information that is acquired over a lifetime is not transmitted to offspring, whereas information that is inherited during copying is transmitted. In cultural evolution there is no mechanism for discarding acquired change. Acquired change can accumulate orders of magnitude faster than, and quickly overwhelm, inherited change due to differential replication of variants in response to selection. This prohibits a selectionist but not an evolutionary framework for culture. Recent work on the origin of life suggests that early life evolved through a non-Darwinian process referred to as communal exchange that does not involve a self-assembly code, and that natural selection emerged from this more haphazard, ancestral evolutionary process. It is proposed that communal exchange provides a more appropriate evolutionary framework for culture than selectionism. This is supported by a computational model of cultural evolution and a network-based program for documenting material cultural history, and it is consistent with high levels of human cooperation.Comment: 18 pages; 2 tables and 11 figures embedded in tex

A Causal Interpretation of Selection Theory

The following dissertation is an inferentialist account of classical population genetics. I present the theory as a definite body of interconnected inferential rules for generating mathematical models of population dynamics. To state those rules, I use the notion of causation as a primitive. First, I put forward a rule stating the circumstances of application of the theory, one that uses causal language to pick out the types of entities over which the theory may be deployed. Next, I offer a rule for grouping such entities into populations based on their competitive causal relationships. Then I offer a general algorithm for generating classical population genetics models for such populations on the basis of what causal influences operate within them.Dynamical models in population genetics are designed to demystify natural phenomena, chiefly to show how adaptation, altruism, and genetic polymorphism can be explained in terms of natural rather than supernatural processes. In order for the theory to serve this purpose, it must be possible to understand, in a principled fashion, when and how to deploy the theory. By presenting the theory as a system of ordered inferential rules that takes causal information as its critical input and yields dynamical models as its outputs, I show explicitly how classical population genetics functions as a non-circular theoretical apparatus for generating explanations. The generalization of the theory achieved by presenting it using causal vocabulary shows how the scope of the theory of natural selection extends beyond its traditional domain of systems distinguished by genetic variations

Rethinking naive realism

Perceptions are externally-directed - they present us with a mind-independent reality, and thus contribute to our abilities to think about this reality, and to know what is objectively the case. But perceptions are also internally-dependent - their phenomenal characters depend on the neuro-computational properties of the subject. A good theory of perception must account for both these facts. But Naive realism has been criticized for failing to accommodate the latter one. This paper evaluates and responds to this criticism. It first argues that a certain version of naive realism, often called “selectionism”, does indeed struggle with the internal-dependence of perceptions. It then develops an alternate version of naive realism which does not. This alternate version, inspired by an idea of Martin's, accommodates the internal-dependence of perceptions by recognizing the role that the subject's neuro-computational properties play in shaping perceptual phenomenology. At the same time, it retains the distinctive naive realist account of the external-directedness of perceptions

A Cognitive Science Based Machine Learning Architecture

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:\ud 1) perceptual learning, the learning of new objects, categories, relations, etc.,\ud 2) episodic learning of events, the what, where, and when,\ud 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence

Learning to Trust

Trust is full of puzzle and paradox.Trust is both rational and emotional. Trust can go beyond calculative self-interest, but has its limits.People may want to trust, while they may also feel threatened by it.If trust is not in place prior to a relationship, on the basis of institutions, prior experience, or reputation, it has to be built up, in specific relations.For that one needs to learn, in the sense of building empathy, and perhaps a certain degree of identification.In an attempt at a better understanding of the puzzles and processes of trust, this chapter applies the perspective of 'embodied cognition', and insights from mental 'framing' and decision heuristics from social psychology.learning;trust;institutions

Methodological Interactionism: Theory and Application to the Firm and to the Building of Trust

Recent insights from the ‘embodied cognition’ perspective in cognitive science, supported by neural research, provide a basis for a ‘methodological interactionism’ that transcends both the methodological individualism of economics and the methodological collectivism of (some) sociology, and is consistent with insights from social psychology. It connects with a Mengerian exchange perspective and Hayekian view of dispersed knowledge from Austrian economics. It provides a basis for a new, unified social science that integrates elements from economics, sociology, social psychology and cognitive science. This paper discusses the roots of this perspective, in theory of cognition and meaning, and illustrates its application in a summary of a social-cognitive theory of the firm and an analysis of processes by which trust is built up and broken down.methodology;philosophy of economics;theory of the firm;trust