Chapter 4: Global responses to the integration challenge

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Overview Explore 2 global responses to the integration challenge Model of intertheoretic reduction from philosophy of science Marr’s tri-level hypothesis Sketch out alternative approach mental architecture approach

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 The integration challenge The challenge of providing an unified account of cognition that draws upon and integrates the whole space Many regions within the “space” of cognitive science remain little studied The “space” is not organized by discipline

Cognitive Science  José Luis Bermúdez / Cambridge University Press approaches to IC Local integrations Examples of specific cases where cognitive scientists have built bridges across levels of explanation and between disciplines Global models of integration Blueprints for solving the integration challenge The mental architectures approach

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Models of global integration Two main candidates: Models of inter-theoretic reduction derived from philosophy of science – analogy with unity of science hypothesis in the physical sciences Marr’s tri-level hypothesis - explicitly proposed as a way of bridging different levels of explanation

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Intertheoretic reduction Relation between theories Model for showing how one theory can be understood in terms of another Standard examples are all in physics Two components Principles for connecting vocabularies Derivations of laws

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Applicability to cognitive science? Very few laws in the cognitive sciences The laws that there are function very differently from laws in physics predictive without being explanatory effects that themselves need to be explained Basic problem – knowledge in cognitive science is not organized in the right sort of way for intertheoretic reduction to be a good model

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 A Marrian model of unity The computational level is the privileged level of explanation The tri-level hypothesis gives two top-down relations between levels Algorithm at level n+1 computing information-processing problem at level n Implementation at level m+1 of algorithm running at level m

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Problems for the Marr approach It cannot work as a general model of cognition. Marr’s model is only applicable to modular systems It requires an information-processing task sufficiently circumscribed to be solvable algorithmically  domain-specificity Algorithms must be computationally tractable – there can only be a limited number of representational primitives and parameters (on pain of frame problem)  informational encapsulation

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Computational analysis and modularity Basic idea – modular systems are specialized for carrying out very specific information-processing tasks Two versions: Fodor modules Darwinian modules Differ over the extent to which the systems are informationally encapsulated

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Examples of modules Fodor modules: Marr’s early visual system Face recognition Syntactic parsing of heard utterances Detecting rhythmic structure of acoustic arrays Darwinian modules cheater detection mate selection social understanding

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Modularity and computational analysis Computational analysis can only work for systems performing functions that can be algorithmically solved Clear specification of what form the output needs to take E.g. Marr’s analysis of early visual system Fodor distinguishes central processing from modular processing Central processing can draw on any type of information Darwinian modules seem closer to central processing

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Mental architectures approach Starts off from the basic assumption that cognition is a form of information-processing Assumption governs all levels of organization (from neurons upwards) and almost all explanatory models/hypotheses within the individual cognitive sciences But there is relatively little discussion w/in those disciplines of how information and information-processing are to be understood

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Mental architecture A mental architecture is a model of how the mind is organized and how it works to process information 1)In what format does a cognitive system carry information? 2)How does that system transform and process information? 3)How is the mind as a whole organized into information- processing sub-systems?

Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Two models of information- processing The physical symbol system hypothesis e.g. Turing machine model of information- processing associated with classical, symbolic AI Connectionism/artificial neural networks neurally-inspired models of information-processing used to model cognitive/perceptual abilities that have posed problems for classical AI