Computationalism Flashcards
Eliminativism
A strong form of anti-realism about intentionality (Quine)
Intentional realism
Realism regarding representation
Hold that representational properties are genuine aspects of mentality
Levels of analysis
Marr had 3 levels: Computational theory, representation and algorithm, and hardware implementation
Computational theory
Psychology
Premise/goal
What is the goal of the computation, why is it appropriate, and what is the logic of the strategy by which it can be carried out?
Representation and algorithm
Computer science
Procedure
How can this computational theory be implemented? In particular, what is the representation for the input and output, and what is the algorithm for the transformation?
Hardware implementation
Neuroscience
How can the representation and algorithm be realized physically?
3 tenets of computationalism
Systematically interpretable
Implementation independence
Symbol manipulation
Systematically interpretable
Symbols are interpreted the same way
Implementation independence
Since C = C it can be implemented everywhere
Symbol manipulation
Symbols can be manipulated so they mean new things
C = C
Cognition = computation
Turing indistinguishability
Can the machine and human being be separated, do they look/act the same?
Turing machine
An abstract model of an idealized computing device with unlimited time and storage space at its disposal. The device manipulates symbols
Input: symbols
Operations: formal
Output: processed symbols
Turing test
Test to see if a computer can “think”
Deterministic
Believing that everything that happens must happen as it does and could not have happened any other way, or relating to this belief
Representation (Marr)
A formal system for making explicit certain entities or types of information, together with a specification of how the system does this
Description (Marr)
The result of using a representation to describe a given entity
Formal scheme (Marr)
A set of symbols with rules for putting them together
Process
Very broad term: “I want to restrict our attention to the meanings associated with machines that are carrying out information-processing tasks”
The purpose of vision
Vision, in short, is used in such a bewildering variety of ways that the visual systems of different animals must differ significantly from one another.
The main job of vision [is] to derive a representation of shape
Algorithm
An explicit, step-by-step procedure for answering some question or solving some problem
Symbols
Primitive symbols are drawn from a finite alphabet.
Something is a symbol only if it has semantic or representational properties
Turing model
Mathematical model of computation describing an abstract machine that manipulates symbols on a strip of tape according to a table of rules
Universal Turing machine (UTM)
Can mimic any other Turing machine
A programmable general purpose computer
Has unlimited memory
AI
Aims to construct “thinking machinery”
Aims to construct computing machines that execute core mental tasks such as reasoning, decision-making, problem solving and so on
Classical computational theory of the mind (CCTM )
The mind is a computational system similar in important respect to a Turing machine, and core mental processes (e.g., reasoning, decisionmaking, and problem solving) are computations similar in important respects to computations executed by a Turing machine.
Core mental processes are computations similar to important respects to computations executed by a Turing machine.
Claims that mental activity is “Turing-style computation”, allowing these and other departures from Turing’s own formalism
Functionalism
A system has a mind when the system has a suitable functional organization
Mental states are functional states (Marr’s second level)
Machine functionalist
Emphasizes probabilistic automata, which are similar to Turing machines except that transitions between computational states are stochastic
Mentalese
Thinking occurs in a language of thought
The representational theory (RTM)
The meaning of a complex Mentalese expression is a function of the meanings of its parts and the way those parts are combined
The representational theory of the mind
A combination of CCTM and RTM
Implementationist
Allows for Turing-style models and neural networks
Turing-style model is higher-level
Neural network is lower-level
Computational neuroscience
Describes the nervous system through computational models
Truth-conditions
Beliefs are the sort of things that can be true or false
Accuracy-conditions
Perceptual states are the sorts of things that can be accurate or inaccurate
Fulfillment-conditions
Desires are the sorts of things that can fulfilled or thwarted
Intentional descriptions
Descriptions that identify mental states through their representational properties
Structuralist conception of computation
A computational model describes an abstract causal structure, without taking into account particular physical states that instantiate the structure
This perspective views computation as an abstract causal structure, focusing on the pattern of causal interactions among system parts rather than specific physical states.
Combinatorial-state automaton (CSA)
Subsumes most familiar models of computation (including Turing machines and neural networks). A CSA provides an abstract description of a physical system’s causal topology: the pattern of causal interaction among the system’s parts, independent of the nature of those parts or the causal mechanisms through which they interact. Computational description specifies a causal topology.
Systematicity
There seem to be systematic relations between mental states. A good theory should reflect those systematic relations.
Productivity
CCTM explains the productivity of mental computation by positing a central processor that stores and retrieves symbols in addressable read/write memory. When needed, the central processor can retrieve arbitrary, unpredicted combinations of symbols from memory.
Formal-syntactic conception of computation (FSC).
Computation manipulates symbols in virtue of their formal syntactic properties rather than their semantic properties.
Arguments against computationalism
Triviality argument
Gödel’s incompleteness theorem
Limits of computational modelling
Temporal arguments
Embodied cognition
Triviality argument
We can describe almost any physical system as executing computations. Searle (1990) claims that a wall implements any computer program, since we can discern some pattern of molecular movements in the wall that is isomorphic to the formal structure of the program.
Gödel’s incompleteness theorem
Gödel’s incompleteness theorems show that human mathematical capacities outstrip the capacities of any Turing machine
Limits of computational modelling
(1) Turing-style computation is sensitive only to “local” properties of a mental representation, which are exhausted by the identity and arrangement of the representation’s constituents.
(2) Many mental processes, paradigmatically abduction, are sensitive to “nonlocal” properties such as relevance, simplicity, and conservatism.
(3) Hence, we may have to abandon Turing-style modeling of the relevant processes.
(4) Unfortunately, we have currently have no idea what alternative theory might serve as a suitable replacement.
Temporal arguments
Mental activity unfolds in time. Moreover, the mind accomplishes sophisticated tasks (e.g., perceptual estimation) very quickly. Many critics worry that computationalism, especially classical computationalism, does not adequately accommodate temporal aspects of cognition.
Intentional realism
Realism regarding representation. At a minimum, this position holds that representational properties are genuine aspects of mentality. Usually, it is also taken to hold that scientific psychology should freely employ intentional descriptions when appropriate
Interpretation
Distractor task interferes with internal memory processes
Mental representations
Symbolic representations
Lessons from early computer technology
1) Computation is logic – and logic is purely formal
Purely formal processes can be run mechanically
2) The logic matters, not the architecture – Implementation independence:
Humans, Mechanics, Electronics
3) Three things needed for computation:
Some input-output mechanisms (sensation)
A big internal store (memory)
Processes (programs) to do the logic
Visual illusions
Especially revealing. The computer model should “suffer” from the same bistability
Church-Turing thesis
The Church-Turing thesis is a fundamental principle in the theory of computation and computer science, formulated independently by Alonzo Church and Alan Turing in the 1930s. It asserts that any function which can be computed by an algorithm can be computed by a Turing machine. In other words, it provides a precise definition of what it means for a function to be “computable.”
