# Understanding ACT-R - an Outsider's Perspective

arXiv: https://arxiv.org/abs/1306.0125 · HTML: https://mlsanity.com/paper/1306.0125/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jun 2013.

## Built on by (most cited first, 4 of 4)

- [Attention Heads of Large Language Models: A Survey](https://mlsanity.com/paper/2409.03752/) (2024)
- [Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens](https://mlsanity.com/paper/2505.18237/) (2025)
- [Human-inspired Perspectives: A Survey on AI Long-term Memory](https://mlsanity.com/paper/2411.00489/) (2024)
- [Modeling Human Behavior Part II -- Cognitive approaches and Uncertainty](https://mlsanity.com/paper/2205.06483/) (2022)

## Abstract (arXiv)

The ACT-R theory of cognition developed by John Anderson and colleagues endeavors to explain how humans recall chunks of information and how they solve problems. ACT-R also serves as a theoretical basis for "cognitive tutors", i.e., automatic tutoring systems that help students learn mathematics, computer programming, and other subjects. The official ACT-R definition is distributed across a large body of literature spanning many articles and monographs, and hence it is difficult for an "outsider" to learn the most important aspects of the theory. This paper aims to provide a tutorial to the core components of the ACT-R theory.