Adaptive control of thought theory

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## Contents

* 1 Definition
* 2 Overview
* 3 ACT as modeling framework
* 4 ACT theory in education
* 5 Links
* 6 References

## Definition[edit | edit source]

John R. Anderson's et al.s Adaptive Control of Thought (ACT*) theories are human information processing and knowledge representation theories.

ACT theory started out in the Simon-Newell tradition, i.e. as a purely symbolic model of human thought and memory. The latest version is Adaptive control of thought-rational (ACT-R Version 6) (Anderson et al., 2004) and incorporates more recent ideas about embodyment (perception and action) and subsymbolic processes.

## Overview[edit | edit source]

Related to the distinction of declarative vs. procedural knowledge, the critical atomic components of cognition and human memory are identified as chunks and productions. According to Yates (2007:32), Anderson (1996) claims the following: "All that there is to intelligence is the simple accrual and tuning of many small units of knowledge that in total produce complex cognition. The whole is no more than the sum of its parts, but it has a lot of parts. (p. 356)."

According to Yates (2007:33):

Procedural knowledge consists of condition-action (IF-THEN) pairs called productions which are activated according to rules relating to a goal structure (Anderson, 1983). Within the ACT framework, all knowledge is initially declarative and is interpreted by general procedures. Productions, then, connect declarative knowledge with behavior. Procedural knowledge represents "how to do things." It is knowledge that is displayed in our behavior, but that we do not hold consciously (Anderson & Lebiere, 1998).

As a task is performed, interpretive applications are gradually replaced with productions that perform the task directly, a process called proceduralization. For example, rehearsing how to manually shift gears in a car is gradually replaced by a production that recognizes and executes the production. In other words, explicit declarative knowledge is replaced by direct application of procedural knowledge (Anderson, 2005). Sequences of productions may be combined into a single production, a process called composition. Together, proceduralization and composition are called knowledge compilation, which creates task-specific productions during practice. The process of proceduralization affects working memory by reducing the load resulting from information being retrieved from long-term memory.

See production system and Soar for some technical background.

According to ACT*, all knowledge begins as declarative information; procedural knowledge is learned by making inferences from already existing factual knowledge. ACT* supports three fundamental types of learning: generalization, in which productions become broader in their range of application, discrimination, in which productions become narrow in their range of application, and strengthening, in which some productions are applied more often. New productions are formed by the conjunction or disjunction of existing productions. (Kearsley: 1994)

Summary of ACT-R (Anderson et al. 2004).

1. There are multiple independent modules whose information processing is encapsulated.
2. The modules can place chunks reflecting their processing in their buffers and the production system can detect when critical patterns are satisfied among these chunks.
3. From those productions whose conditions are satisfied a single production will be selected at any time and fire, leading to updates to various buffers that in turn can trigger information processing in their respective modules.
4. While chunks and productions are the symbolic components of the system reflecting its overall information flow, chunks have subsymbolic activations and productions have subsymbolic utilities that control which chunks and productions get used.
5. Learning can involve either acquiring new chunks and productions or tuning their subsymbolic parameters.
6. These processes are stochastic and take place in real time.

## ACT as modeling framework[edit | edit source]

"ACT-R is a cognitive architecture: a theory about how human cognition works. On the exterior, ACT-R looks like a programming language; however, its constructs reflect assumptions about human cognition. These assumptions are based on numerous facts derived from psychology experiments" (About, retrieved 11:05, 16 November 2007 (MET)).

## ACT theory in education[edit | edit source]

ACT* theory can explain a range of learning types and therefore influence instructional design models. It also is popular in research on intelligent tutoring systems since the ACT* is a model of a cognitive architecture embedded in a modeling/programming language. As such it can be used to model learners, e.g. "understand" what difficulties they might have.

(This section needs to be expanded a lot ...)

## Links[edit | edit source]

* ACT Theory HomePage

## References[edit | edit source]

* Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

* Anderson, J., Boyle, C., Farrell, R. & Reiser, B. (1987). "Cognitive principles in the design of computer tutors", in P. Morris (ed.), Modeling Cognition. NY: John Wiley.

* Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51(4), 355-365.

* Anderson, J. R. (2005). Cognitive psychology and its implications (6th ed.). New York: Worth Publishers.

* Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of the mind. Psychological Review, 111(4), 1036-1060.

* Anderson, J. R., & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Lawrence Erlbaum Associates.

* Kearsley, G., Seidel, R. & Park, D.K. (1993). Theory Into Practice.

* Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y . (2004). An integrated theory of the mind. Psychological Review 111, (4). 1036-1060. PDF Preprint

* Yates, Kenneth A. (2007). Towards a taxonomy of cognitive task analysis methods: A search for cognition and task analysis interactions. Unpublished Doctoral Dissertation, University of Southern California, Los Angeles. PDF