Title :
Fuzzy cognitive modeling for argumentative agent
Author :
Tao, XueHong ; Yelland, Nicola ; Zhang, Yanchun
Author_Institution :
Centre of Appl. Inf., Victoria Univ., Melbourne, VIC, Australia
Abstract :
Argumentation plays an important role in promoting deep learning, fostering conceptual change and supporting problem solving. The new “learning by arguing” paradigm leads to new learning opportunities. However, due to the difficulties in modeling human cognition, there are few learning systems that can facilitate argumentation dialogues between systems and learners. Fuzzy Cognitive Map (FCM) is an effective tool in modeling human cognition. This paper proposes an FCM based argumentation model. Based on this model we design an argumentative software agent to facilitate argumentative learning. Provided with the domain knowledge and argumentation capability, the agent is able to simulate a peer learner and automatically conduct argumentative dialogues with learners. The argumentative agent can be applied in general school education as well as special domains like diabetes education and eHealth decision support.
Keywords :
cognitive systems; fuzzy set theory; learning (artificial intelligence); problem solving; software agents; FCM; argumentation dialogues; argumentative software agent; deep learning; diabetes education; eHealth decision support; fuzzy cognitive map; fuzzy cognitive modeling; human cognition; learning systems; problem solving; school education; Artificial intelligence; Cognition; Collaboration; Computational modeling; Diabetes; Humans; Proposals; Fuzzy cognitive map; argumentative learning; collaborative argumentation; intelligent software agent; intelligent tutoring system;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251204