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Date of Graduation
Bachelor of Science (BS)
Department of Computer Science
Text-based games are a very promising space for language-focused machine learning. Within them are huge hurdles in machine learning, like long-term planning and memory, interpretation and generation of natural language, unpredictability, and more. One problem to consider in the realm of natural language interpretation is how to train a machine learning model to understand a text-based game’s objective. This work considers treating this issue like a machine translation problem, where a detailed objective or list of instructions is given as input, and output is a predicted list of actions. This work also explores how a supervised learning system might learn long-term planning and memory through the example of an oracle that always knows the best path. In this exploration, the work here shows that finding this best path is infeasible.
Snarr, Anthony, "Towards natural language understanding in text-based games" (2020). Senior Honors Projects, 2020-current. 70.