DocumentCode
3666795
Title
Robotic episodes learning for building cognitive experience map
Author
Dong Liu;Ming Cong;Xiaodong Han;Yu Du
Author_Institution
School of Mechanical Engineering, Dalian University of Technology, Dalian, China
fYear
2015
fDate
6/1/2015 12:00:00 AM
Firstpage
1210
Lastpage
1215
Abstract
This paper is about incremental online learning of robotic experience under uncertainty based on biology-inspired episodic memory. The episodic memory-driving Markov decision process (EM-MDP) with a novel episode model is proposed by imitating the firing patterns of hippocampal CA1 neurons, to simulate the organization process of episodic memory. Episodes learning method is presented by utilizing sparse distributed memory (SDM) for building experience map, and the uncertain information of system is considered. The experience map has the bionic cognitive abilities of self-organizing, self-learning and adaptivity based on episodic memory. Experimental results show that the approach has robustness to uncertainty and can realize memory real-time storage, incremental accumulation, integration and updating.
Keywords
"Neurons","Learning systems","Robot sensing systems","Planning","Trajectory"
Publisher
ieee
Conference_Titel
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN
978-1-4799-8728-3
Type
conf
DOI
10.1109/CYBER.2015.7288116
Filename
7288116
Link To Document