The Soar Cognitive Architecture
Abstract
The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.
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Human cognition seamlessly synthesizes past experiences into coherent episodic memories that support personalized interactions.
“Human cognition seamlessly synthesizes past experiences into coherent episodic memories that support personalized interactions (Piaget et al., 1952; Carey, 1985; Laird, 2012).”
From Pre-Storage Reasoning for Episodic Memory: Shifting Inference Burden to Memory for Personalized Dialogue (2025) · cites this paper as Laird, 2012
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Cited by 1,108
- Authors
- Laird, J. E.
- Corresponding author
- Laird, John E.
- ORCID
- Laird, John E.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 2012-04-13
- OpenAlex
- W419646410
- Cited by
- 1,108
- References
- 0
- Citations by year
- 2026: 70 · 2025: 78 · 2024: 52 · 2023: 78 · 2022: 76 · 2021: 102 · 2020: 103 · 2019: 108 · 2018: 87 · 2017: 83 · 2016: 78 · 2015: 64 · 2014: 49 · 2013: 52 · 2012: 27
- FWCI
- 28.57
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Physical Sciences › Computer Science › Artificial Intelligence › Cognitive Computing and Networks
- Keywords
- Soar cognitive architecture, hierarchical reasoning, planning, experiential learning, reinforcement learning, semantic memory, episodic memory, mental imagery, agent development
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