Chapter 4: Global responses to the integration challenge

1. Chapter 4:Global responses to the integration challenge

2. 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

3. 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 2010

4. 3 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

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

15. 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 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010