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Type of Talk: UTCS Colloquia/AI

Speaker/Affiliation: Jeff Clune/Cornell University

Talk Audience: UTCS Faculty, Graduate Students, Undergraduate Students and Outside Interested Parties

Date/Time: Friday, September 14, 2012, 11:00 am

Location: ACES 2.402

Host: Risto Miikkulanien

Talk Title: Automatically generating regular, modular neural networks with computational abstractions of evolution and developmental biology

Talk Abstract:
I will describe how to combine computational abstractions of evolution and developmental biology to automatically produce modular, regular neural networks (digital models of brains). The properties generated, such as functional modules, symmetries, and repeated motifs, are desirable properties found in biological brains. These properties are key innovations in our quest to generate artificially intelligent robots that rival their natural counterparts. Such structurally organized neural networks can exploit the regularity of problems and increasingly outcompete previous methods as problem regularity increases. Moreover, the functional modularity of such networks enables building block modules to be quickly rewired, facilitating learning and adaptation to new challenges. I will also briefly describe how the same algorithm can generate complex, recognizable three-dimensional objects, enabling us to simultaneously design the bodies of robots along with their neural controllers.

Bio:
Jeff Clune is a Postdoctoral Fellow in Hod Lipson's lab at Cornell University, funded by a Postdoctoral Research Fellowship from the US National Science Foundation, and will soon be an assistant professor in the Computer Science Department at the University of Wyoming. Jeff has a bachelor's degree in philosophy from the University of Michigan and a Ph.D. in computer science and a master's degree in philosophy from Michigan State University.