Algorithmes de co-évolution pour la résolution approchée de PDM multi-agent
Identifieur interne :
000438 ( PascalFrancis/Corpus );
précédent :
000437;
suivant :
000439
Algorithmes de co-évolution pour la résolution approchée de PDM multi-agent
Auteurs : Iadine ChadesSource :
-
Revue d'intelligence artificielle [ 0992-499X ] ; 2006.
RBID : Pascal:06-0329057
Descripteurs français
- Pascal (Inist)
- Prise décision,
Système incertain,
Système aide décision,
Système multiagent,
Intelligence artificielle,
Coordination,
Empathie,
Perception,
Planification,
Décision Markov,
Décision séquentielle,
Système décentralisé,
Processus Markov,
Résolution problème,
Modélisation,
Système coordonnée,
..
English descriptors
- KwdEn :
- Artificial intelligence,
Coordinate system,
Coordination,
Decentralized system,
Decision making,
Decision support system,
Empathy,
Markov decision,
Markov process,
Modeling,
Multiagent system,
Perception,
Planning,
Problem solving,
Sequential decision,
Uncertain system.
Abstract
Markov Decision Processes (MDP) provide a formal approach for solving sequential decision problems under uncertainty. Decentralized Markov Decision Processes extend MDP. They are used to model the problem of several agents making decision under uncertainty. However, solving a decentralized markov decision process is NEXP-complete as soon as two agents are involved. In this paper we propose algorithms for solving approximately Multi-agent MDP problems in a centralized or decentralized way. The aim of our methods is to design a system in which agents coordinate to achieve a task in collaboration. Coordination is based on two major properties: subjectivity and empathy. While subjectivity allows an agent to deal with incomplete and local perceptions, thus to design memory less policies, empathy allows an agent to adapt its decisions in regards with the uncertainty of the decisions of the others.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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| A05 | | | | @2 20 |
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| A06 | | | | @2 2-3 |
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| A08 | 01 | 1 | FRE | @1 Algorithmes de co-évolution pour la résolution approchée de PDM multi-agent |
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| A09 | 01 | 1 | FRE | @1 Décision et planification dans l'incertain |
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| A11 | 01 | 1 | | @1 CHADES (Iadine) |
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| A12 | 01 | 1 | | @1 CHARPILLET (F.) @9 ed. |
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| A12 | 02 | 1 | | @1 GARCIA (F.) @9 ed. |
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| A12 | 03 | 1 | | @1 PERNY (Patrice) @9 ed. |
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| A12 | 04 | 1 | | @1 SIGAUD (Olivier) @9 ed. |
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| A14 | 01 | | | @1 Equipe Méthodes Mathématiques et Informatique pour la Décision Unité de Biométrie et Intelligence Artificielle INRA, BP27 @2 31326 Castanet-Tolosan @3 FRA @Z 1 aut. |
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| A15 | 01 | | | @1 LORIA-INRIA @2 Nancy @3 FRA @Z 1 aut. |
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| A15 | 02 | | | @1 INRA-MIA @2 Toulouse @3 FRA @Z 2 aut. |
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| A15 | 03 | | | @1 LIP6 @2 Paris @3 FRA @Z 3 aut. @Z 4 aut. |
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| C01 | 01 | | ENG | @0 Markov Decision Processes (MDP) provide a formal approach for solving sequential decision problems under uncertainty. Decentralized Markov Decision Processes extend MDP. They are used to model the problem of several agents making decision under uncertainty. However, solving a decentralized markov decision process is NEXP-complete as soon as two agents are involved. In this paper we propose algorithms for solving approximately Multi-agent MDP problems in a centralized or decentralized way. The aim of our methods is to design a system in which agents coordinate to achieve a task in collaboration. Coordination is based on two major properties: subjectivity and empathy. While subjectivity allows an agent to deal with incomplete and local perceptions, thus to design memory less policies, empathy allows an agent to adapt its decisions in regards with the uncertainty of the decisions of the others. |
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| C02 | 01 | X | | @0 001D01A08 |
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| C02 | 02 | X | | @0 001D02C |
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| C03 | 01 | X | FRE | @0 Prise décision @5 06 |
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| C03 | 01 | X | ENG | @0 Decision making @5 06 |
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| C03 | 01 | X | SPA | @0 Toma decision @5 06 |
|---|
| C03 | 02 | X | FRE | @0 Système incertain @5 07 |
|---|
| C03 | 02 | X | ENG | @0 Uncertain system @5 07 |
|---|
| C03 | 02 | X | SPA | @0 Sistema incierto @5 07 |
|---|
| C03 | 03 | X | FRE | @0 Système aide décision @5 08 |
|---|
| C03 | 03 | X | ENG | @0 Decision support system @5 08 |
|---|
| C03 | 03 | X | SPA | @0 Sistema ayuda decisíon @5 08 |
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| C03 | 04 | X | FRE | @0 Système multiagent @5 09 |
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| C03 | 04 | X | ENG | @0 Multiagent system @5 09 |
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| C03 | 04 | X | SPA | @0 Sistema multiagente @5 09 |
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| C03 | 05 | X | FRE | @0 Intelligence artificielle @5 10 |
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| C03 | 05 | X | SPA | @0 Inteligencia artificial @5 10 |
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| C03 | 06 | X | FRE | @0 Coordination @5 11 |
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| C03 | 06 | X | ENG | @0 Coordination @5 11 |
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| C03 | 06 | X | SPA | @0 Coordinación @5 11 |
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| C03 | 07 | X | FRE | @0 Empathie @5 12 |
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| C03 | 07 | X | ENG | @0 Empathy @5 12 |
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| C03 | 07 | X | SPA | @0 Empatía @5 12 |
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| C03 | 08 | X | FRE | @0 Perception @5 13 |
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| C03 | 08 | X | ENG | @0 Perception @5 13 |
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| C03 | 08 | X | SPA | @0 Percepción @5 13 |
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| C03 | 09 | X | FRE | @0 Planification @5 14 |
|---|
| C03 | 09 | X | ENG | @0 Planning @5 14 |
|---|
| C03 | 09 | X | SPA | @0 Planificación @5 14 |
|---|
| C03 | 10 | X | FRE | @0 Décision Markov @5 18 |
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| C03 | 10 | X | ENG | @0 Markov decision @5 18 |
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| C03 | 10 | X | SPA | @0 Decisión Markov @5 18 |
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| C03 | 11 | X | FRE | @0 Décision séquentielle @5 19 |
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| C03 | 11 | X | ENG | @0 Sequential decision @5 19 |
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| C03 | 11 | X | SPA | @0 Decisión secuencial @5 19 |
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| C03 | 12 | X | FRE | @0 Système décentralisé @5 20 |
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| C03 | 12 | X | ENG | @0 Decentralized system @5 20 |
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| C03 | 12 | X | SPA | @0 Sistema descentralizado @5 20 |
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| C03 | 13 | X | FRE | @0 Processus Markov @5 23 |
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| C03 | 13 | X | ENG | @0 Markov process @5 23 |
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| C03 | 13 | X | SPA | @0 Proceso Markov @5 23 |
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| C03 | 14 | X | FRE | @0 Résolution problème @5 24 |
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| C03 | 14 | X | ENG | @0 Problem solving @5 24 |
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| C03 | 14 | X | SPA | @0 Resolución problema @5 24 |
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| C03 | 15 | X | FRE | @0 Modélisation @5 25 |
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| C03 | 15 | X | ENG | @0 Modeling @5 25 |
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| C03 | 15 | X | SPA | @0 Modelización @5 25 |
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| C03 | 16 | X | FRE | @0 Système coordonnée @5 26 |
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| C03 | 16 | X | ENG | @0 Coordinate system @5 26 |
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| C03 | 16 | X | SPA | @0 Sistema coordenadas @5 26 |
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| C03 | 17 | X | FRE | @0 . @4 INC @5 82 |
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| N21 | | | | @1 212 |
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| N44 | 01 | | | @1 OTO |
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| N82 | | | | @1 OTO |
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| pR |
| A30 | 01 | 1 | FRE | @1 Décision dynamique et planification dans l'incertain. Journée @3 Paris FRA @4 2004-05-07 |
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Format Inist (serveur)
| NO : | PASCAL 06-0329057 INIST |
|---|
| FT : | Algorithmes de co-évolution pour la résolution approchée de PDM multi-agent |
|---|
| AU : | CHADES (Iadine); CHARPILLET (F.); GARCIA (F.); PERNY (Patrice); SIGAUD (Olivier) |
|---|
| AF : | Equipe Méthodes Mathématiques et Informatique pour la Décision Unité de Biométrie et Intelligence Artificielle INRA, BP27/31326 Castanet-Tolosan/France (1 aut.); LORIA-INRIA/Nancy/France (1 aut.); INRA-MIA/Toulouse/France (2 aut.); LIP6/Paris/France (3 aut., 4 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Revue d'intelligence artificielle; ISSN 0992-499X; France; Da. 2006; Vol. 20; No. 2-3; Pp. 345-382; Abs. anglais; Bibl. 1 p.1/4 |
|---|
| LA : | Français |
|---|
| EA : | Markov Decision Processes (MDP) provide a formal approach for solving sequential decision problems under uncertainty. Decentralized Markov Decision Processes extend MDP. They are used to model the problem of several agents making decision under uncertainty. However, solving a decentralized markov decision process is NEXP-complete as soon as two agents are involved. In this paper we propose algorithms for solving approximately Multi-agent MDP problems in a centralized or decentralized way. The aim of our methods is to design a system in which agents coordinate to achieve a task in collaboration. Coordination is based on two major properties: subjectivity and empathy. While subjectivity allows an agent to deal with incomplete and local perceptions, thus to design memory less policies, empathy allows an agent to adapt its decisions in regards with the uncertainty of the decisions of the others. |
|---|
| CC : | 001D01A08; 001D02C |
|---|
| FD : | Prise décision; Système incertain; Système aide décision; Système multiagent; Intelligence artificielle; Coordination; Empathie; Perception; Planification; Décision Markov; Décision séquentielle; Système décentralisé; Processus Markov; Résolution problème; Modélisation; Système coordonnée; . |
|---|
| ED : | Decision making; Uncertain system; Decision support system; Multiagent system; Artificial intelligence; Coordination; Empathy; Perception; Planning; Markov decision; Sequential decision; Decentralized system; Markov process; Problem solving; Modeling; Coordinate system |
|---|
| SD : | Toma decision; Sistema incierto; Sistema ayuda decisíon; Sistema multiagente; Inteligencia artificial; Coordinación; Empatía; Percepción; Planificación; Decisión Markov; Decisión secuencial; Sistema descentralizado; Proceso Markov; Resolución problema; Modelización; Sistema coordenadas |
|---|
| LO : | INIST-21320.354000142556580070 |
|---|
| ID : | 06-0329057 |
|---|
Links to Exploration step
Pascal:06-0329057
Le document en format XML
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</keywords><front><div type="abstract" xml:lang="en">Markov Decision Processes (MDP) provide a formal approach for solving sequential decision problems under uncertainty. Decentralized Markov Decision Processes extend MDP. They are used to model the problem of several agents making decision under uncertainty. However, solving a decentralized markov decision process is NEXP-complete as soon as two agents are involved. In this paper we propose algorithms for solving approximately Multi-agent MDP problems in a centralized or decentralized way. The aim of our methods is to design a system in which agents coordinate to achieve a task in collaboration. Coordination is based on two major properties: subjectivity and empathy. While subjectivity allows an agent to deal with incomplete and local perceptions, thus to design memory less policies, empathy allows an agent to adapt its decisions in regards with the uncertainty of the decisions of the others.</div>
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<s5>08</s5>
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<s5>09</s5>
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<s5>10</s5>
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<s5>10</s5>
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<s5>11</s5>
</fC03><fC03 i1="06" i2="X" l="ENG"><s0>Coordination</s0>
<s5>11</s5>
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<s5>11</s5>
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<s5>12</s5>
</fC03><fC03 i1="07" i2="X" l="SPA"><s0>Empatía</s0>
<s5>12</s5>
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<s5>13</s5>
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<s5>13</s5>
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<s5>14</s5>
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<s5>14</s5>
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<s5>18</s5>
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<s5>18</s5>
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<s5>18</s5>
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<s5>19</s5>
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<s5>19</s5>
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<s5>19</s5>
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<s5>20</s5>
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<s5>20</s5>
</fC03><fC03 i1="12" i2="X" l="SPA"><s0>Sistema descentralizado</s0>
<s5>20</s5>
</fC03><fC03 i1="13" i2="X" l="FRE"><s0>Processus Markov</s0>
<s5>23</s5>
</fC03><fC03 i1="13" i2="X" l="ENG"><s0>Markov process</s0>
<s5>23</s5>
</fC03><fC03 i1="13" i2="X" l="SPA"><s0>Proceso Markov</s0>
<s5>23</s5>
</fC03><fC03 i1="14" i2="X" l="FRE"><s0>Résolution problème</s0>
<s5>24</s5>
</fC03><fC03 i1="14" i2="X" l="ENG"><s0>Problem solving</s0>
<s5>24</s5>
</fC03><fC03 i1="14" i2="X" l="SPA"><s0>Resolución problema</s0>
<s5>24</s5>
</fC03><fC03 i1="15" i2="X" l="FRE"><s0>Modélisation</s0>
<s5>25</s5>
</fC03><fC03 i1="15" i2="X" l="ENG"><s0>Modeling</s0>
<s5>25</s5>
</fC03><fC03 i1="15" i2="X" l="SPA"><s0>Modelización</s0>
<s5>25</s5>
</fC03><fC03 i1="16" i2="X" l="FRE"><s0>Système coordonnée</s0>
<s5>26</s5>
</fC03><fC03 i1="16" i2="X" l="ENG"><s0>Coordinate system</s0>
<s5>26</s5>
</fC03><fC03 i1="16" i2="X" l="SPA"><s0>Sistema coordenadas</s0>
<s5>26</s5>
</fC03><fC03 i1="17" i2="X" l="FRE"><s0>.</s0>
<s4>INC</s4>
<s5>82</s5>
</fC03><fN21><s1>212</s1>
</fN21><fN44 i1="01"><s1>OTO</s1>
</fN44><fN82><s1>OTO</s1>
</fN82><pR><fA30 i1="01" i2="1" l="FRE"><s1>Décision dynamique et planification dans l'incertain. Journée</s1>
<s3>Paris FRA</s3>
<s4>2004-05-07</s4>
</fA30><server><NO>PASCAL 06-0329057 INIST</NO>
<FT>Algorithmes de co-évolution pour la résolution approchée de PDM multi-agent</FT>
<AU>CHADES (Iadine); CHARPILLET (F.); GARCIA (F.); PERNY (Patrice); SIGAUD (Olivier)</AU>
<AF>Equipe Méthodes Mathématiques et Informatique pour la Décision Unité de Biométrie et Intelligence Artificielle INRA, BP27/31326 Castanet-Tolosan/France (1 aut.); LORIA-INRIA/Nancy/France (1 aut.); INRA-MIA/Toulouse/France (2 aut.); LIP6/Paris/France (3 aut., 4 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Revue d'intelligence artificielle; ISSN 0992-499X; France; Da. 2006; Vol. 20; No. 2-3; Pp. 345-382; Abs. anglais; Bibl. 1 p.1/4</SO>
<LA>Français</LA>
<EA>Markov Decision Processes (MDP) provide a formal approach for solving sequential decision problems under uncertainty. Decentralized Markov Decision Processes extend MDP. They are used to model the problem of several agents making decision under uncertainty. However, solving a decentralized markov decision process is NEXP-complete as soon as two agents are involved. In this paper we propose algorithms for solving approximately Multi-agent MDP problems in a centralized or decentralized way. The aim of our methods is to design a system in which agents coordinate to achieve a task in collaboration. Coordination is based on two major properties: subjectivity and empathy. While subjectivity allows an agent to deal with incomplete and local perceptions, thus to design memory less policies, empathy allows an agent to adapt its decisions in regards with the uncertainty of the decisions of the others.</EA>
<CC>001D01A08; 001D02C</CC>
<FD>Prise décision; Système incertain; Système aide décision; Système multiagent; Intelligence artificielle; Coordination; Empathie; Perception; Planification; Décision Markov; Décision séquentielle; Système décentralisé; Processus Markov; Résolution problème; Modélisation; Système coordonnée; .</FD>
<ED>Decision making; Uncertain system; Decision support system; Multiagent system; Artificial intelligence; Coordination; Empathy; Perception; Planning; Markov decision; Sequential decision; Decentralized system; Markov process; Problem solving; Modeling; Coordinate system</ED>
<SD>Toma decision; Sistema incierto; Sistema ayuda decisíon; Sistema multiagente; Inteligencia artificial; Coordinación; Empatía; Percepción; Planificación; Decisión Markov; Decisión secuencial; Sistema descentralizado; Proceso Markov; Resolución problema; Modelización; Sistema coordenadas</SD>
<LO>INIST-21320.354000142556580070</LO>
<ID>06-0329057</ID>
</server>
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