Applications of the principle of least effort in data transformation
File(s)
Date
2019-12Author
Veenhuis, Luke
Publisher
University of Wisconsin--Whitewater
Advisor(s)
Nguyen, Hien
Gunawardena, Athula
Zhou, Jiazhen
Metadata
Show full item recordAbstract
I am interested in applying the Principle of Least Effort to data transformation in an effort to solve three important challenges in using video games as a testbed for the study of inverse reinforcement learning. These challenges are as follows: the very large state space created by high granularity of time, the very large range of feature values provided by quantitative features, and the difficulty to measure similarity of trajectories. Through exploring The Principle of Least Effort from the Social Sciences, I propose a form of data transformation that categorizes data according to the familiarity and preferences of the modeled user. Furthermore I will also show how this approach can be used to create a similarity comparison between trajectories in accordance to The Principle of Least Effort. For the collection of test data I have utilized a reinforcement learning agent to play the minigame BuildMarines for StarCraft II as provided by DeepMind.
Subject
User interfaces (Computer systems)
Least effort principle (Psychology)
Video games
Reinforcement learning
Permanent Link
http://digital.library.wisc.edu/1793/79577Description
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