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Dual Process Theory Opposes Decision Theory?

Do any of the findings that support the dual-process theory of instrumental action enable us to construct a good objection to decision theory as an elucidation of subjective probabilities and preferences?

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The dual-process theory of instrumental action was introduced in Goal-Directed and Habitual Processes.

We considered decision theory as an elucidation of subjective probabilities and preferences in What Are Preferences?.


The following claims cannot all be true:

  1. Decision theory provides an ‘elucidation of the notions of subjective probability and subjective desirability or utility’ (Jeffrey, 1983, p. xi).

  2. The notions elucidated are those of belief and desire, which also feature in goal-directed processes.

  3. Some instrumental actions are dominated by habitual processes (see Goal-Directed and Habitual: Some Evidence).

  4. Habitual and goal-directed processes can pull in opposing directions (see The Minor Puzzle about Habitual Processes).

What think that these are jointly inconsistent? Because their truth would indicate that we have no grounds to expect agents to act in accordance with the axioms required to make (1) true.[1]

The joint inconsistency of these claims is significant: it suggests that we cannot use decision theory as an anchor for thinking about notions of belief and desire. But perhaps there is a way to avoid this conclusion?

Are the claims actually inconsistent? Or is there some way to use decision theory as an anchor for thinking about notions of belief and desire despite the inconsistency of the above claims?

Note on Sources

One possibile response to the joint inconsistency of the claims above discussed in the lecture involves a distinction between between computational description and implementation details. This is a rough-and-ready approximation to a famous three-fold distinction from Marr (1982); in terms of that theory my ‘implementation details’ are what Marr calls representations and algorithms.

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anchor : A theory, fact or other thing that is used by a group of researchers to ensure that they have a shared understanding of a phenomenon. An anchor is needed when it is unclear whether different researchers are offering incompatible claims about a single phenomenon or compatible claims about distinct phenomena. For example, we might take decision theory to anchor a shared understanding of belief and desire.
computational description : A computational description of a system or ability specifies what the thing is for and how it achieves this. Marr (1982) distinguishes the computational description of a system from representations and algorithms and its hardware implementation.
decision theory : I use ‘decision theory’ for the theory elaborated by Jeffrey (1983). Variants are variously called ‘expected utility theory’ (Hargreaves-Heap & Varoufakis, 2004), ‘revealed preference theory’ (Sen, 1973) and ‘the theory of rational choice’ (Sugden, 1991). As the differences between variants are not important for our purposes, the term can be used for any of core formal parts of the standard approaches based on Ramsey (1931) and Savage (1972).
dual-process theory of instrumental action : Instrumental action ‘is controlled by two dissociable processes: a goal-directed and an habitual process’ (Dickinson, 2016, p. 177). (See instrumental action.)
goal-directed process : A process which involves ‘a representation of the causal relationship between the action and outcome and a representation of the current incentive value, or utility, of the outcome’ and which influences an action ‘in a way that rationalizes the action as instrumental for attaining the goal’ (Dickinson, 2016, p. 177).
habitual process : A process underpinning some instrumental actions which obeys Thorndyke’s Law of Effect: ‘The presenta­tion of an effective [=rewarding] outcome following an action [...] rein­forces a connection between the stimuli present when the action is per­formed and the action itself so that subsequent presentations of these stimuli elicit the [...] action as a response’ (Dickinson, 1994, p. 48). (Interesting complication which you can safely ignore: there is probably much more to say about under what conditions the stimulus–action connection is strengthened; e.g. Thrailkill, Trask, Vidal, Alcalá, & Bouton, 2018.)
representations and algorithms : To specify the representations and algorithms involved in a system is to specify how the inputs and outputs are represented and how the transformation from input to output is accomplished. Marr (1982) distinguishes the {representations and algorithms} from the computational description of a system and its hardware implementation.


Chater, N. (2018). The Mind is Flat: The Illusion of Mental Depth and The Improvised Mind. Penguin UK.
Davidson, D. (1987). Problems in the explanation of action. In P. Pettit, R. Sylvan, & J. Norman (Eds.), Metaphysics and morality: Essays in honour of j. J. C. smart (pp. 35–49). Oxford: Blackwell.
Dickinson, A. (1994). Instrumental conditioning. In N. Mackintosh (Ed.), Animal learning and cognition. London: Academic Press.
Dickinson, A. (2016). Instrumental conditioning revisited: Updating dual-process theory. In J. B. Trobalon & V. D. Chamizo (Eds.), Associative learning and cognition (Vol. 51, pp. 177–195). Edicions Universitat Barcelona.
Hargreaves-Heap, S., & Varoufakis, Y. (2004). Game theory: A critical introduction. London: Routledge. Retrieved from
Jeffrey, R. C. (1983). The logic of decision, second edition. Chicago: University of Chicago Press.
Marr, D. (1982). Vision : A computational investigation into the human representation and processing of visual information. San Francisco: W.H. Freeman.
Ramsey, F. (1931). Truth and probability. In R. Braithwaite (Ed.), The foundations of mathematics and other logical essays. London: Routledge.
Savage, L. J. (1972). The foundations of statistics (2nd rev. ed). New York: Dover Publications.
Sen, A. (1973). Behaviour and the Concept of Preference. Economica, 40(159), 241–259.
Sugden, R. (1991). Rational Choice: A Survey of Contributions from Economics and Philosophy. The Economic Journal, 101(407), 751–785.
Thrailkill, E. A., Trask, S., Vidal, P., Alcalá, J. A., & Bouton, M. E. (2018). Stimulus control of actions and habits: A role for reinforcer predictability and attention in the development of habitual behavior. Journal of Experimental Psychology: Animal Learning and Cognition, 44, 370–384.
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323.


  1. On what the axioms are, see What Are Preferences?. ↩︎