Curiosity-driven algorithm for reinforcement learning

Curiosity-driven algorithm for reinforcement learning

One problem of current Reinforcement Learning algorithms is finding a balance between exploitation of existing knowledge and exploration for a new experience. Curiosity exploration bonus has been proposed to address this problem, but current implementations are vulnerable to stochastic noise inside...

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Bibliographic Details
Main Author: Tsybulko, Vitalii
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:eng
Published: 2019
Subjects:
reinforcement learning
proximal policy optimisation
curiosity-driven exploration bonus
Tietotekniikka
Mathematical Information Technology
602
tekoäly
koneoppiminen
palkitseminen
artificial intelligence
machine learning
rewarding
Online Access: https://jyx.jyu.fi/handle/123456789/64268

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