Autonomous qualitative learning of distinctions and actions in a developing agent

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Title: Autonomous qualitative learning of distinctions and actions in a developing agent
Author: Mugan, Jonathan William
Abstract: How can an agent bootstrap up from a pixel -level representation to autonomously learn high -level states and actions using only domain general knowledge ? This thesis attacks a piece of this problem and assumes that an agent has a set of continuous variables describing the environment and a set of continuous motor primitives , and poses a solution for the problem of how an agent can learn a set of useful states and effective higher -level actions through autonomous experience with the environment . There exist methods for learning models of the environment , and there also exist methods for planning . However , for autonomous learning , these methods have been used almost exclusively in discrete environments . This thesis proposes attacking the problem of learning high -level states and actions in continuous environments by using a qualitative representation to bridge the gap between continuous and discrete variable representations . In this approach , the agent begins with a broad discretization and initially can only tell if the value of each variable is increasing , decreasing , or remaining steady . The agent then simultaneously learns a qualitative representation (discretization ) and a set of predictive models of the environment . The agent then converts these models into plans to form actions . The agent then uses those learned actions to explore the environment . The method is evaluated using a simulated robot with realistic physics . The robot is sitting at a table that contains one or two blocks , as well as other distractor objects that are out of reach . The agent autonomously explores the environment without being given a task . After learning , the agent is given various tasks to determine if it learned the necessary states and actions to complete them . The results show that the agent was able to use this method to autonomously learn to perform the tasks .
URI: http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -1726
Date: 2010-11-23

Citation

Autonomous qualitative learning of distinctions and actions in a developing agent. Doctoral dissertation, University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -1726 .

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