An agent achieves its goals by interacting with its environment, cyclically choosing and executing suitable actions. An action execution process is a reasonable and critical part of an entire cognitive architecture, because the process of generating executable motor commands is not only driven by low-level environmental information, but is also initiated and affected by the agent’s high-level mental processes. This review focuses on cognitive models of action, or more specifically, of the action execution process, as implemented in a set of popular cognitive architectures. We examine the representations and procedures inside the action execution process, as well as the cooperation between action execution and other high-level cognitive modules. We finally conclude with some general observations regarding the nature of action execution.
If the inline PDF is not rendering correctly, you can download the PDF file here.
ACT-R 6.0 Tutorial. 2012. Unpublished manuscript. Retrieved from http://actr.psy.cmu.edu/wordpress/wp-content/themes/ACT-R/actr6/actr6.zip
Albus, J. S., and Barbera, A. J. 2005. RCS: A cognitive architecture for intelligent multi-agent systems. Annual Reviews in Control, 29(1):87-99.
Anderson, J. 2007. How can the human mind occur in the physical universe? : Oxford University Press.
Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., and Qin, Y. 2004. An integrated theory of the mind. Psychological Review, 111(4):1036-1060.
Arrabales, R., Ledezma, A., and Sanchis, A. 2009. CERA-CRANIUM: A test bed for machine consciousness research. International Workshop on Machine Consciousness.
Baars, B. J. 1988. A cognitive theory of consciousness. New York: Cambridge University Press.
Baars, B. J. 2002. The conscious access hypothesis: origins and recent evidence. Trends in cognitive sciences, 6(1):47-52.
Bothell, D. n.d. ACT-R 6.0 Reference Manual (Working Draft). Retrieved from http://actr.psy.cmu.edu/wordpress/wp-content/themes/ACT-R/actr6/reference-manual.pdf
Brooks, R. A. 1991. How to build complete creatures rather than isolated cognitive simulators.Architectures for Intelligence: The Twenty-second Carnegie Mellon Symposium on Cognition:225-239.
Budiu, R. 2013. ACT-R Website. from http://act-r.psy.cmu.edu/
Byrne, M. D., and Anderson, J. R. 2001. Serial modules in parallel: The psychological refractory period and perfect time-sharing. Psychological Review, 108(4):847-869.
Castiello, U. 2005. The neuroscience of grasping. Nature Reviews Neuroscience, 6(9):726-736.
Dickmanns, E. D. 1992. A general dynamic vision architecture for UGV and UAV. Applied Intelligence, 2(3):251-270.
Dickmanns, E. D. 2000. An expectation-based, multi-focal, saccadic (EMS) vision system for vehicle guidance. Paper presented at the International Symposium of Robotics Research (ISRR’99), 421-430, Snowbird Utah, USA.
Dong, D., and Franklin, S. 2014. Sensory Motor System: Modeling the process of action execution. Paper presented at the Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2145-2150, Austin TX, USA.
Duch, W., Oentaryo, R. J., and Pasquier, M. 2008. Cognitive Architectures: Where do we go from here? Paper presented at the AGI, 122-136, Memphis TN, USA.
Franklin, S., and Graesser, A. 1997. Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents Intelligent agents III agent theories, architectures, and languages, 21-35.London, UK: Springer-Verlag.
Franklin, S., Madl, T., D’Mello, S., and Snaider, J. 2014. LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning. IEEE Transactions on Autonomous Mental Development, 6(1):19-41. doi: 10.1109/TAMD.2013.2277589
Goertzel, B., Lian, R., Arel, I., De Garis, H., and Chen, S. 2010. A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures. Neurocomputing, 74(1):30-49.
Goodale, M. A., and Milner, A. D. 1992. Separate visual pathways for perception and action.Trends in neurosciences, 15(1):20-25.
Grafton, S. T. 2010. The cognitive neuroscience of prehension: recent developments. Experimental brain research, 204(4):475-491. Jeannerod, M. 2006. Motor cognition: What actions tell the self. Oxford, UK: Oxford University Press.
Kieras, D. E., and Meyer, D. E. 1996. The EPIC architecture: Principles of operation. Unpublished manuscript from ftp://ftp.eecs.umich.edu/people/kieras/EPICarch.ps.
Kieras, D. E., and Meyer, D. E. 1997. An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-computer interaction, 12(4):391-438.
Laird, J. 2012. The Soar cognitive architecture: MIT Press.
Laird, J. E. 2008. Extending the Soar cognitive architecture. Paper presented at the Artificial General Intelligence 2008, 224-235, Memphis TN, USA.
Laird, J. E., Congdon, C. B., Coulter, K. J., Derbinsky, N., and Xu, J. 2012. The Soar User’s Manual Version 9.3.2. Computer Science and Engineering Department. University of Michigan. Unpublished manuscript.
Langley, P., and Choi, D. 2006. A unified cognitive architecture for physical agents. Paper presented at the Proceedings of the National Conference on Artificial Intelligence, 1469-1474, Boston MA, USA.
Langley, P., Laird, J. E., and Rogers, S. 2009. Cognitive architectures: Research issues and challenges. Cognitive Systems Research, 10(2):141-160.
Milner, D., and Goodale, M. A. 2008. Two visual systems re-viewed. Neuropsychologia, 46(3):774-785.
Rohrer, B. 2012. BECCA: Reintegrating AI for natural world interaction. Paper presented at the AAAI Spring Symposium on Designing Intelligent Robots: Reintegrating AI, Stanford California, USA.
Russell, S. J., and Norvig, P. 2009. Artificial intelligence: a modern approach (Third ed.): Prentice hall.
Searle, J. R. 1983. Intentionality: An essay in the philosophy of mind: Cambridge University Press.
Shapiro, S. C., and Bona, J. P. 2010. The GLAIR cognitive architecture. International Journal of Machine Consciousness, 2(2):307-332.
Sun, R. 2003. A tutorial on CLARION 5.0. Unpublished manuscript.
Sun, R. 2006. The CLARION cognitive architecture: Extending cognitive modeling to social simulation. In R. Sun (Ed.), Cognition and multi-agent interaction, 79-99. New York: Cambridge University Press.