Decentralized control in the pursuit domain
Identifieur interne : 003907 ( Crin/Curation ); précédent : 003906; suivant : 003908Decentralized control in the pursuit domain
Auteurs : Raghav ArasSource :
English descriptors
- KwdEn :
Abstract
We study the prey-predator problem as a multi-agent system (MAS). We consider an hierarchical approach to searching optimal policies for each agent to capture the prey. In particular, we imagine decomposition of the state-space, and of the "situation" space. In other words, we consider an hierarchy of policies, the agent following the one which is most appropriate for his current state-space and for the situation in that state-space.
Links toward previous steps (curation, corpus...)
- to stream Crin, to step Corpus: Pour aller vers cette notice dans l'étape Curation :003907
Links to Exploration step
CRIN:aras03aLe document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" wicri:score="233">Decentralized control in the pursuit domain</title></titleStmt><publicationStmt><idno type="RBID">CRIN:aras03a</idno><date when="2003" year="2003">2003</date><idno type="wicri:Area/Crin/Corpus">003907</idno><idno type="wicri:Area/Crin/Curation">003907</idno><idno type="wicri:explorRef" wicri:stream="Crin" wicri:step="Curation">003907</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Decentralized control in the pursuit domain</title><author><name sortKey="Aras, Raghav" sort="Aras, Raghav" uniqKey="Aras R" first="Raghav" last="Aras">Raghav Aras</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>hierarchical approach</term><term>markov decision processes</term><term>mas</term><term>mdp</term><term>planning</term><term>prey-predator</term><term>reinforcement learning</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en" wicri:score="1083">We study the prey-predator problem as a multi-agent system (MAS). We consider an hierarchical approach to searching optimal policies for each agent to capture the prey. In particular, we imagine decomposition of the state-space, and of the "situation" space. In other words, we consider an hierarchy of policies, the agent following the one which is most appropriate for his current state-space and for the situation in that state-space.</div></front></TEI><BibTex type="techreport"><ref>aras03a</ref><crinnumber>A03-R-171</crinnumber><equipe>MAIA</equipe><author><e>Aras, Raghav</e></author><title>Decentralized control in the pursuit domain</title><institution>LORIA INRIA-Lorraine</institution><year>2003</year><type>Stage de DEA</type><month>Jul</month><keywords><e>reinforcement learning</e><e>markov decision processes</e><e>mdp</e><e>mas</e><e>prey-predator</e><e>planning</e><e>hierarchical approach</e></keywords><abstract>We study the prey-predator problem as a multi-agent system (MAS). We consider an hierarchical approach to searching optimal policies for each agent to capture the prey. In particular, we imagine decomposition of the state-space, and of the "situation" space. In other words, we consider an hierarchy of policies, the agent following the one which is most appropriate for his current state-space and for the situation in that state-space.</abstract></BibTex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Lorraine/explor/InforLorV4/Data/Crin/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 003907 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Crin/Curation/biblio.hfd -nk 003907 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Lorraine
|area= InforLorV4
|flux= Crin
|étape= Curation
|type= RBID
|clé= CRIN:aras03a
|texte= Decentralized control in the pursuit domain
}}
| This area was generated with Dilib version V0.6.33. |  |