Policy Derivation Methods for Critic-Only Reinforcement Learning in Continuous Action Spaces
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F16%3A00300604" target="_blank" >RIV/68407700:21730/16:00300604 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S2405896316303305" target="_blank" >http://www.sciencedirect.com/science/article/pii/S2405896316303305</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ifacol.2016.07.127" target="_blank" >10.1016/j.ifacol.2016.07.127</a>
Alternative languages
Result language
angličtina
Original language name
Policy Derivation Methods for Critic-Only Reinforcement Learning in Continuous Action Spaces
Original language description
State-of-the-art critic-only reinforcement learning methods can deal with a small discrete action space. The most common approach to real-world problems with continuous actions is to discretize the action space. In this paper a method is proposed to derive a continuous-action policy based on a value function that has been computed for discrete actions by using any known algorithm such as value iteration. Several variants of the policy-derivation algorithm are introduced and compared on two continuous state-action benchmarks: double pendulum swing-up and 3D mountain car.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GA15-22731S" target="_blank" >GA15-22731S: Symbolic Regression for Reinforcement Learning in Continuous Spaces</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
4th IFAC Conference on Intelligent Control and Automation Sciences ICONS 2016
ISBN
—
ISSN
2405-8963
e-ISSN
—
Number of pages
6
Pages from-to
285-290
Publisher name
Elsevier
Place of publication
Lausanne
Event location
Reims
Event date
Jun 1, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000381503600049