chapter 4: global responses to the integration challenge
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Chapter 4: Global responses to the integration challenge. 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. - PowerPoint PPT PresentationTRANSCRIPT
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 2010
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
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