Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148080
Title: Model-based RL in ATARI games
Authors: Akarapu, Bharadwaj
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Akarapu, B. (2021). Model-based RL in ATARI games. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148080
Project: SCSE20-0485
Abstract: This report describes the implementation of the world model reinforcement learning algorithm to gauge its performance against traditional reinforcement learning algorithms like deep Q-learning. The algorithm will be tested in different Atari Environments, some of which pose great difficultly due to the smaller signals in the observation frames. Specific modifications were required to tailor the world model for each of the different environments.
URI: https://hdl.handle.net/10356/148080
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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