Show simple item record

dc.contributor.advisorKaikhah, Kosrow
dc.contributor.authorChristenson, Christopher P. ( )
dc.identifier.citationChristenson, C. P. (2004). Evolving learning neural networks (Unpublished thesis). Texas State University-San Marcos, San Marcos, Texas.
dc.description.abstractSupervised learning has long been used to modify the artificial neural network in order to perform classification tasks. However, the standard fully connected layered design is often inadequate when performing such tasks. We show that evolution can be used to design an artificial neural network that learns faster and more accurately. By evolving artificial neural networks within a dynamic environment, the artificial neural network is forced to use learning. This strategy combined with incremental evolution produces an artificial neural network that outperforms the standard fully-connected layered design. The resulting artificial neural network can learn to solve an entire domain of problems, including those of lesser complexity. Evolution alone can be used to create a network that solves a single task. However, real world environments are dynamic, and thus require the ability to adapt to changes. By improving the design of the artificial neural network for learning tasks, we have come one step closer to artificial life.
dc.format.extent132 pages
dc.format.medium1 file (.pdf)
dc.subjectNeural networks
dc.subjectArtificial intelligence
dc.titleEvolving Learning Neural Networks
txstate.documenttypeThesis Science State University--San Marcos of Science
txstate.departmentComputer Science


This item is restricted to the Texas State University community. TXST affiliated users can access the item with their NetID and password authentication. Non-affiliated individuals should request a copy through their local library’s interlibrary loan service.

If this is your thesis or dissertation, you can make it open access. This will allow all visitors to view the document. To request open access, fill out the form linked below:

This item appears in the following Collection(s)

Show simple item record