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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Reusable Reinforcement Learning for Modular Self Motivated Agents |
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Authors: |
Jaroslav Vitku, Pavel Nahodil |
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Published in:
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(2014).ECMS 2014 Proceedings edited
by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for
Modeling and Simulation. doi:10.7148/2014 ISBN:
978-0-9564944-8-1 28th
European Conference on Modelling and Simulation, Brescia,
Italy, May 27th – 30th,
2014 |
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Citation
format: |
Jaroslav Vitku, Pavel Nahodil (2014).
Reusable Reinforcement Learning for
Modular Self Motivated Agents, ECMS 2014 Proceedings edited by: Flaminio Squazzoni, Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for Modeling and Simulation. doi:10.7148/2014-0352 |
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DOI: |
http://dx.doi.org/10.7148/2014-0352 |
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Abstract: |
Presented topic is from the
research fields called Artificial Life and Artificial Intelligence (AI). In
this paper, there is presented novel approach to designing agent
architectures with its requirements. The approach is inspired by inherited
modularity of biological brains and agent architectures are represented here
as set of given reusable modules connected into a particular topology. This
paper presents design of two particular modules for future use in more
complex architectures. The modules are used for implementing model-free motivation-driven
Reinforcement Learning (RL). First, the novel framework for these
architectures is described together with a used simulator. Then, the design
of two new reusable domain-independent components of agent architectures is
described. Finally, experimental validation of these new components and their
future use is mentioned. |
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