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Life Long Learning in Sparse Learning Environments

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Date Issued:
2013
Abstract/Description:
Life long learning is a machine learning technique that deals with learning sequential tasks over time. It seeks to transfer knowledge from previous learning tasks to new learning tasks in order to increase generalization performance and learning speed. Real-time learning environments in which many agents are participating may provide learning opportunities but they are spread out in time and space outside of the geographical scope of a single learning agent. This research seeks to provide an algorithm and framework for life long learning among a network of agents in a sparse real-time learning environment. This work will utilize the robust knowledge representation of neural networks, and make use of both functional and representational knowledge transfer to accomplish this task. A new generative life long learning algorithm utilizing cascade correlation and reverberating pseudo-rehearsal and incorporating a method for merging divergent life long learning paths will be implemented.
Title: Life Long Learning in Sparse Learning Environments.
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Name(s): Reeder, John, Author
Georgiopoulos, Michael, Committee Chair
Gonzalez, Avelino, Committee Member
Sukthankar, Gita, Committee Member
Anagnostopoulos, Georgios, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2013
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Life long learning is a machine learning technique that deals with learning sequential tasks over time. It seeks to transfer knowledge from previous learning tasks to new learning tasks in order to increase generalization performance and learning speed. Real-time learning environments in which many agents are participating may provide learning opportunities but they are spread out in time and space outside of the geographical scope of a single learning agent. This research seeks to provide an algorithm and framework for life long learning among a network of agents in a sparse real-time learning environment. This work will utilize the robust knowledge representation of neural networks, and make use of both functional and representational knowledge transfer to accomplish this task. A new generative life long learning algorithm utilizing cascade correlation and reverberating pseudo-rehearsal and incorporating a method for merging divergent life long learning paths will be implemented.
Identifier: CFE0004917 (IID), ucf:49601 (fedora)
Note(s): 2013-08-01
Ph.D.
Engineering and Computer Science, Electrical Engineering and Computing
Doctoral
This record was generated from author submitted information.
Subject(s): Machine Learning -- life long learning -- neural networks -- cascade correlation -- multi-task learning -- observational learning
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0004917
Restrictions on Access: public 2013-08-15
Host Institution: UCF

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