Cognitive architecture
A cognitive architecture refers to both a theory about the structure of the
The Institute for Creative Technologies defines cognitive architecture as: "hypothesis about the fixed structures that provide a mind, whether in natural or artificial systems, and how they work together – in conjunction with knowledge and skills embodied within the architecture – to yield intelligent behavior in a diversity of complex environments."[3]
History
John R. Anderson started research on human memory in the early 1970s and his 1973 thesis with Gordon H. Bower provided a theory of human associative memory.[5] He included more aspects of his research on long-term memory and thinking processes into this research and eventually designed a cognitive architecture he eventually called ACT. He and his students were influenced by Allen Newell's use of the term "cognitive architecture". Anderson's lab used the term to refer to the ACT theory as embodied in a collection of papers and designs (there was not a complete implementation of ACT at the time).
In 1983 John R. Anderson published the seminal work in this area, entitled The Architecture of Cognition.
Distinctions
Cognitive architectures can be
In traditional
Notable examples
Some well-known cognitive architectures, in alphabetical order:
Name | Description |
---|---|
4CAPS | developed at Carnegie Mellon University by Marcel A. Just and Sashank Varma. |
4D-RCS Reference Model Architecture | developed by NIST is a reference model architecture that provides a theoretical foundation for designing, engineering, integrating intelligent systems software for unmanned ground vehicles.[8]
|
ACT-R | developed at Carnegie Mellon University under John R. Anderson. |
ASMO[9] |
developed by Rony Novianto, Mary-Anne Williams and Benjamin Johnston at the University of Technology Sydney. This cognitive architecture is based on the idea that actions/behaviours compete for an agents resources. |
CHREST |
developed under Brunel University and Peter C. Lane at the University of Hertfordshire .
|
CLARION | the cognitive architecture, developed under Ron Sun at Rensselaer Polytechnic Institute and University of Missouri. |
CMAC | The Cerebellar Model Articulation Controller (CMAC) is a type of neural network based on a model of the mammalian classification in the machine learning community.
|
Copycat | by Indiana University .
|
DAYDREAMER | developed by Erik Mueller at the University of California in Los Angeles under Michael G. Dyer |
DUAL |
developed at the New Bulgarian University under Boicho Kokinov. |
FORR | developed by Susan L. Epstein at The City University of New York .
|
Framsticks | a connectionist distributed neural architecture for simulated creatures or robots, where modules of neural networks composed of heterogenous neurons (including receptors and effectors) can be designed and evolved. |
Google DeepMind | The company has created a video games in a similar fashion to humans[11] and a neural network that may be able to access an external memory like a conventional Turing machine,[12] resulting in a computer that appears to possibly mimic the short-term memory of the human brain. The underlying algorithm is based on a combination of Q-learning with multilayer recurrent neural network.[13] (Also see an overview by Jürgen Schmidhuber on earlier related work in deep learning.[14][15] )
|
Holographic associative memory | This architecture is part of the family of correlation-based associative memories, where information is mapped onto the phase orientation of complex numbers on a Riemann plane. It was inspired by holonomic brain model by Karl H. Pribram. Holographs have been shown to be effective for associative memory tasks, generalization, and pattern recognition with changeable attention. |
Hierarchical temporal memory | This architecture is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world. |
CoJACK | An ACT-R inspired extension to the JACK multi-agent system that adds a cognitive architecture to the agents for eliciting more realistic (human-like) behaviors in virtual environments. |
IDA and LIDA | implementing Global Workspace Theory, developed under Stan Franklin at the University of Memphis .
|
MANIC (Cognitive Architecture) |
Michael S. Gashler, University of Arkansas. |
PRS |
'Procedural Reasoning System', developed by Michael Georgeff and Amy Lansky at SRI International. |
Psi-Theory |
developed under . |
Spaun (Semantic Pointer Architecture Unified Network) | by Chris Eliasmith at the Centre for Theoretical Neuroscience at the spiking neurons, which uses groups of these neurons to complete cognitive tasks via flexibile coordination. Components of the model communicate using spiking neurons that implement neural representations called "semantic pointers" using various firing patterns. Semantic pointers can be understood as being elements of a compressed neural vector space.[16]
|
Soar | developed under Allen Newell and John Laird at Carnegie Mellon University and the University of Michigan. |
Society of Mind | proposed by Marvin Minsky. |
The Emotion Machine | proposed by Marvin Minsky. |
Sparse distributed memory | was proposed by Pentti Kanerva at NASA Ames Research Center as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs.[17] |
Subsumption architectures | developed e.g. by Rodney Brooks (though it could be argued whether they are cognitive). |
See also
- Artificial brain
- Artificial consciousness
- Autonomous agent
- Biologically inspired cognitive architectures
- Blue Brain Project
- BRAIN Initiative
- Cognitive architecture comparison
- Cognitive computing
- Cognitive science
- Commonsense reasoning
- Computer architecture
- Conceptual space
- Deep learning
- Google Brain
- Image schema
- Knowledge level
- Neocognitron
- Neural correlates of consciousness
- Pandemonium architecture
- Simulated reality
- Social simulation
- Unified theory of cognition
- Never-Ending Language Learning
- Bayesian Brain
- Open Mind Common Sense
References
- ISBN 9781138207929.
- ^ Newell, Allen. 1990. Unified Theories of Cognition. Harvard University Press, Cambridge, Massachusetts.
- ^ "Cognitive Architecture". Institute for Creative Technologies. 2024. Retrieved 11 February 2024.
- ^ "The Feigenbaum Papers". Stanford University. Retrieved 11 February 2024.
- ^ "This Week's Citation Classic: Anderson J R & Bower G H. Human associative memory. Washington," in: CC. Nr. 52 Dec 24–31, 1979.
- ^ John R. Anderson. The Architecture of Cognition, 1983/2013.
- S2CID 9709702.
- ^ Douglas Whitney Gage (2004). Mobile robots XVII: 26–28 October 2004, Philadelphia, Pennsylvania, USA. Society of Photo-optical Instrumentation Engineers. page 35.
- ^ Novianto, Rony (2014). Flexible Attention-based Cognitive Architecture for Robots (PDF) (Thesis).
- .
- ].
- ].
- S2CID 205242740.
- ^ "DeepMind's Nature Paper and Earlier Related Work".
- S2CID 11715509.
- S2CID 1673514.
- ^ Denning, Peter J. "Sparse distributed memory." (1989).Url: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19920002425.pdf
External links
- Media related to Cognitive architecture at Wikimedia Commons
- Quotations related to Cognitive architecture at Wikiquote