Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Effective reinforcement learning through intrinsic motivation and visual external memory in partially observable environments
Download
Burak_Han_Demirbilek_MSc_Thesis.pdf
Date
2023-9
Author
Demirbilek, Burak Han
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
149
views
57
downloads
Cite This
Reinforcement learning in practical scenarios often includes partial observability that requires long-term remembering of visual observations to obtain optimal policies. Addressing this challenge, this study introduces agents augmented with visual external memories, enhancing agents decision-making capabilities by constructing a context derived from both current observations and memory data. Moreover, to ensure effective utilization of the external memory for the agent, intrinsic motivation is incorporated as a secondary reward system, promoting long-term beneficial behaviors of using memory. Key contributions from this study include a novel framework for integrating visual external memory in reinforcement learning agents, the development of intrinsic motivation functions to efficiently learn how to utilize external memory to improve overall learning, empirical evaluations and experiments in various environments, and detailed comparison and analysis against the state-of-the-art. The results highlight the potential and advantages of the proposed approaches and present numerous possibilities for future investigation within this particular field of study.
Subject Keywords
Reinforcement learning
,
Partial observability
,
External memory management
,
Intrinsic motivation
URI
https://hdl.handle.net/11511/105568
Collections
Graduate School of Natural and Applied Sciences, Thesis
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. H. Demirbilek, “Effective reinforcement learning through intrinsic motivation and visual external memory in partially observable environments,” M.S. - Master of Science, Middle East Technical University, 2023.