DocumentCode
1643750
Title
Hybridization of cognitive models using evolutionary strategies
Author
López, Óscar J Romero ; de Antonio Jimenez, Angelica
Author_Institution
Software Eng. Dept., Univ. Politec. de Madrid, Madrid
fYear
2009
Firstpage
3213
Lastpage
3218
Abstract
Incorporating different kinds of micro-theories of cognition and modulating several mechanisms to unify all the recommended actions and outputs of an intelligent system when a huge amount of environmental variables are changing continuously with increasing complexity, may become a very comprehensive task. The presented framework proposes an hybrid cognitive architecture that relies on integrating of emergent systems approaches -connectionist and autopoietic systems-, and cognitivist approaches, in order to combine implicit and explicit processes necessary in developing cognitive skills. The proposed architecture includes different kinds of learning capabilities at each cognitive level which grant to the architecture a big plasticity. In addition, the propounded attention module includes an evolutionary mechanism based on gene expression programming to evolve a set of eligibility conditions in charge of modulating the coalition/subordination of specialized behaviours, taking into consideration the theatre metaphor for consciousness. Finally, a co-evolutionary mechanism is proposed to propagate behaviours and knowledge between cognitive systems -agents- on the basis of memetic engineering. The proposed architecture was proved in an animat environment using a multi-agent platform where several emergent properties of self-organization arose.
Keywords
evolutionary computation; inference mechanisms; software architecture; autopoietic systems; coalition-subordination modulation; cognitive models; cognitivist approaches; evolutionary mechanism; evolutionary strategies; gene expression programming; hybrid cognitive architecture; intelligent system; memetic engineering; multiagent platform; theatre metaphor; Artificial intelligence; Biology computing; Cognition; Computer architecture; DNA; Gene expression; History; Knowledge representation; Organisms; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location
Trondheim
Print_ISBN
978-1-4244-2958-5
Electronic_ISBN
978-1-4244-2959-2
Type
conf
DOI
10.1109/CEC.2009.4983351
Filename
4983351
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