Brave mobots use representation: Emergence of representation in fight-or-flight learning [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 7 (4):475-494 (1997)
The paper uses ideas from Machine Learning, Artificial Intelligence and Genetic Algorithms to provide a model of the development of a fight-or-flight response in a simulated agent. The modelled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structures which can be given a representational interpretation. It also shows how these may form the infrastructure for closely-coupled agent/environment interaction
|Keywords||Artificial Intelligence Emergence Learning Representation Science|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Mark H. Bickhard (1993). Representational Content in Humans and Machines. Journal of Experimental and Theoretical Artificial Intelligence 5:285-33.
Nancy J. Nersessian (1989). Conceptual Change in Science and in Science Education. Synthese 80 (1):163 - 183.
Nello Cristianini (1995). Evolution and Learning: An Epistemological Perspective. [REVIEW] Axiomathes 6 (3):429-437.
Mark H. Bickhard (2004). Process and Emergence: Normative Function and Representation. Axiomathes - An International Journal in Ontology and Cognitive Systems 14:135-169.
Susan Hanson & D. Burr (1990). What Connectionist Models Learn. Behavioral and Brain Sciences.
Mark H. Bickhard (2009). The Interactivist Model. Synthese 166 (3):547 - 591.
Added to index2009-01-28
Total downloads36 ( #45,906 of 1,096,707 )
Recent downloads (6 months)7 ( #30,906 of 1,096,707 )
How can I increase my downloads?