Masters Thesis Defense “Implementation and Evaluation of Goal Selection in a Cognitive Architecture” By Sravya Kondrakunta

Wednesday, July 26, 2017, 11 am to 1 pm
Campus: 
Dayton
304 Russ Engineering
Audience: 
Current Students
Faculty
Staff

ABSTRACT:

A cognitive system attempts to achieve its goals by utilizing the appropriate resources present to yield the best possible outcome within a short duration. To achieve the goals in such an efficient manner, it is important for the agent to manage its goals well. Goal management not only makes the agent efficient but also flexible, more durable to the sudden changes in environment, and self-reliant. Goal Management consists of various goal operations including goal formulation, selection, change, delegation, achievement and monitoring. Each operation is unique and has its own significance in aiding the performance of the agent. The thesis work focuses on the implementation of two particular goal operations. These are goal selection and goal change.

Goal selection allows the agents to choose among its goals by using any criteria which is appropriate for the domain. Goal change allows the agent to change its current goal to another goal because of reasons like inadequate amount of resources or detection of a discrepancy. The implementation of these operations is done within a cognitive architecture called Meta-Cognitive Integrated Dual Cycle Architecture (MIDCA) in two domains construction and restaurant. In the construction domain, the goals are to construct the towers using the resources within a provided time limit, and in the restaurant domain the goals are to satisfy the maximum number of people by serving the items ordered with a limited amount of money. After the implementation of goal selection and goal change, the work is evaluated using various methods, one of which is the comparison of the performance of MIDCA with and without those goal change operations and the other is by comparing two different goal selection methods. Several graphical depictions and mathematical formulae are presented that support the course of performance comparison

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