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Title: Reinforcement Learning with Guarantees that Hold for Ever
Reinforcement learning is a successful explore-and-exploit approach, where a controller tries to learn how to navigate an unknown environment. The principle approach is for an intelligent agent to learn how to maximise expected rewards. But what happens if the objective refers to non-terminating systems? We can obviously not wait until an infinite amount of time has passed, assess the success, and update. But what can we do? This talk will tell.  more » « less
Award ID(s):
2009022 2146563
NSF-PAR ID:
10417919
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Groote, J.F.; Huisman, M.
Date Published:
Journal Name:
Formal Methods for Industrial Critical Systems. FMICS 2022
Volume:
13487
Page Range / eLocation ID:
3-7
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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