Non-independent Intelligent Creatures Reinforcement Learning Mechanism Research Based on I-XCS
PengJian Xi, Jianxiong Tan
Available Online July 2015.
- https://doi.org/10.2991/icismme-15.2015.9How to use a DOI?
- artificial intelligence; Non-independent intelligent creatures;I-XCS;gradient descent; reinforcement learning
- In order to solve many problems of reinforcement learning of Non-independent intelligent creatures in artificial intelligence, such as the single MDP environment and narrow learning space. This paper designed an Non-independent intelligent creatures reinforcement learning mechanism based on the Improved XCS classifier. This learning mechanism based on the original XCS classification capabilities and online knowledge, it constructs a high-stability, low-dimensional approximation method by using the gradient descent related technologies. This method has low-storage ability and enhances the inductive learning ability of intelligent creatures. Simulation experiment results show that the I-XCS classification learning algorithm not only can efficiently solve MDP environment issues such as single, narrow space, but also to a certain extent improved the analysis of non-independent intelligent creatures in reinforcement learning performance.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - PengJian Xi AU - Jianxiong Tan PY - 2015/07 DA - 2015/07 TI - Non-independent Intelligent Creatures Reinforcement Learning Mechanism Research Based on I-XCS BT - First International Conference on Information Sciences, Machinery, Materials and Energy PB - Atlantis Press SP - 47 EP - 54 SN - 1951-6851 UR - https://doi.org/10.2991/icismme-15.2015.9 DO - https://doi.org/10.2991/icismme-15.2015.9 ID - Xi2015/07 ER -