DocumentCode :
603088
Title :
Towards goal based architecture design for learning high-level representation of behaviors from demonstration
Author :
Fonooni, Benjamin ; Hellstrom, T. ; Janlert, L.
Author_Institution :
Umea Univ., Umea, Sweden
fYear :
2013
fDate :
25-28 Feb. 2013
Firstpage :
67
Lastpage :
74
Abstract :
This paper gives a brief overview of challenges in designing cognitive architectures for Learning from Demonstration. By investigating features and functionality of some related architectures, we propose a modular architecture particularly suited for sequential learning high-level representations of behaviors. We head towards designing and implementing goal based imitation learning that not only allows the robot to learn necessary conditions for executing particular behaviors, but also to understand the intents of the tutor and reproduce the same behaviors accordingly.
Keywords :
behavioural sciences computing; learning (artificial intelligence); software architecture; behaviors; cognitive architectures; goal based architecture design; high-level representation; learning from demonstration; modular architecture; sequential learning; Cognition; Context; Joining processes; Radiofrequency identification; Robot sensing systems; Tin; Cognitive Architecture; Goal Based Imitation; Learning from Demonstration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2013 IEEE International Multi-Disciplinary Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2437-3
Type :
conf
DOI :
10.1109/CogSIMA.2013.6523825
Filename :
6523825
Link To Document :
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