An advanced Business Game is presented in the paper, built on the methodology of System Dynamics. It can be used for cognitive learning and knowledge transmission in schools and Universities; it allows the learners to take decisions at each time step, after which it calculates the corresponding results, showing them according to the principles of double entry accounting. An agent based framework is then discussed, which constitutes a form of virtual tutorship for the learners. The agents act as a decision support system for the decisions to be taken, and can explain some cause/effect relations. The agents themselves learn how the model work by practicing it, through some reinforcement learning techniques.
Titolo: | A Web Based Business Game Built on System Dynamics Using Cognitive Agents as Virtual Tutors | |
Autori Riconosciuti: | ||
Autori: | M. REMONDINO | |
Data di pubblicazione: | 2008 | |
Abstract: | An advanced Business Game is presented in the paper, built on the methodology of System Dynamics. It can be used for cognitive learning and knowledge transmission in schools and Universities; it allows the learners to take decisions at each time step, after which it calculates the corresponding results, showing them according to the principles of double entry accounting. An agent based framework is then discussed, which constitutes a form of virtual tutorship for the learners. The agents act as a decision support system for the decisions to be taken, and can explain some cause/effect relations. The agents themselves learn how the model work by practicing it, through some reinforcement learning techniques. | |
Editore: | IEEE Computer Society | |
Titolo del libro: | Tenth International Conference on Computer Modeling and Simulation (uksim 2008) | |
Volume: | - | |
Pagina iniziale: | 568 | |
Pagina finale: | 572 | |
Nome del convegno: | IEEE EUROSIM/UKSIM 2008 | |
Luogo del convegno: | Cambridge | |
Anno del convegno: | 1-3 aprile 2008 | |
ISBN: | 9780769531144 | |
Parole Chiave: | Business game; intelligent agents; reinforcement learning | |
Appare nelle tipologie: | 04A-Conference paper in volume |