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Deep Self-Modeling for Robotic Systems

As self-awareness is important to human higher level cognition so too is the ability to self-model important to performing complex behaviors. The power of these self-models is one that I demonstrate grows with the complexity of problems being solved, and thus provides the framework for higher level cognition. I demonstrate that self-models can be used to effectively control and improve on existing control algorithms to allow agents to perform complex tasks. I further investigate new ways in which these self-models can be learned and applied to increase their efficacy and improve the ability of these models to generalize across tasks and bodies. Finally, I demonstrate the overall power of these self-models to allow for complex tasks to be completed with little data across a variety of bodies and using a number of algorithms.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/gtv9-0f69
Date January 2022
CreatorsKwiatkowski, Robert
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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