InforLorV4, PascalFrancis, Curation, bibRecord, 000739

Analyse d'un algorithme d'intelligence en essaim pour le fourragement

Identifieur interne : 000739 ( PascalFrancis/Curation ); précédent : 000738; suivant : 000740

Analyse d'un algorithme d'intelligence en essaim pour le fourragement

Auteurs : Amine Boumaza [France] ; Bruno Scherrer [France]

Source :

Revue d'intelligence artificielle [ 0992-499X ] ; 2008.

RBID : Pascal:09-0030850

Descripteurs français

Pascal (Inist)
- Intelligence artificielle, Solution optimale, Système multiagent, Planification, Commande optimale, Contrôle optimal, Point fixe, Insecte social, Formicoidea, Analyse algorithme, Intelligence en essaim, Taux convergence, Convergence numérique, Modélisation, Méthode espace état, Contraction, ..
Wicri :
- topic : Intelligence artificielle.

English descriptors

KwdEn :
- Algorithm analysis, Artificial intelligence, Contraction, Convergence rate, Fix point, Formicoidea, Modeling, Multiagent system, Numerical convergence, Optimal control, Optimal control (mathematics), Optimal solution, Planning, Social insect, State space method, Swarm intelligence.

Abstract

We present a swarm intelligence algorithm that solves a discrete foraging problem. We describe simulations and provide a complete convergence analysis: we show that the population computes the solution of some optimal control problem and that its dynamics converges. We discuss the rate of convergence with respect to the number of agents: we give experimental and theoretical arguments that suggest that this convergence rate is superlinear with respect to the number of agents. Furthermore, we explain how this model can be extended to the case where the state space is continuous, and in order to solve optimal control problems in general. We argue that such an approach can be applied to any problem that involves the computation of the fixed point of a contraction mapping. This allows to design a large class of formally well understood swarm intelligence algorithms.

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C01	`01`		`ENG`	@0 We present a swarm intelligence algorithm that solves a discrete foraging problem. We describe simulations and provide a complete convergence analysis: we show that the population computes the solution of some optimal control problem and that its dynamics converges. We discuss the rate of convergence with respect to the number of agents: we give experimental and theoretical arguments that suggest that this convergence rate is superlinear with respect to the number of agents. Furthermore, we explain how this model can be extended to the case where the state space is continuous, and in order to solve optimal control problems in general. We argue that such an approach can be applied to any problem that involves the computation of the fixed point of a contraction mapping. This allows to design a large class of formally well understood swarm intelligence algorithms.
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C03	`11`	`X`	`FRE`	`@0 Intelligence en essaim @5 24`
C03	`11`	`X`	`ENG`	`@0 Swarm intelligence @5 24`
C03	`11`	`X`	`SPA`	`@0 Inteligencia de enjambre @5 24`
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C03	`16`	`X`	`FRE`	`@0 Contraction @5 29`
C03	`16`	`X`	`ENG`	`@0 Contraction @5 29`
C03	`16`	`X`	`SPA`	`@0 Contracción @5 29`
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C07	`02`	`X`	`FRE`	`@0 Hymenoptera @2 NS`
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C07	`03`	`X`	`FRE`	`@0 Insecta @2 NS`
C07	`03`	`X`	`ENG`	`@0 Insecta @2 NS`
C07	`03`	`X`	`SPA`	`@0 Insecta @2 NS`
C07	`04`	`X`	`FRE`	`@0 Arthropoda @2 NS`
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Le document en format XML

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<s5>24</s5>
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<s5>24</s5>
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<s5>25</s5>
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<s5>25</s5>
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<s5>25</s5>
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<s5>26</s5>
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<s5>26</s5>
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<s5>27</s5>
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<s5>28</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Contraction</s0>
<s5>29</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Contraction</s0>
<s5>29</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Contracción</s0>
<s5>29</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>.</s0>
<s4>INC</s4>
<s5>82</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Aculeata</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Aculeata</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Aculeata</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="FRE"><s0>Hymenoptera</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="ENG"><s0>Hymenoptera</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="SPA"><s0>Hymenoptera</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="FRE"><s0>Insecta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="ENG"><s0>Insecta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="SPA"><s0>Insecta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="FRE"><s0>Arthropoda</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="ENG"><s0>Arthropoda</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="SPA"><s0>Arthropoda</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="05" i2="X" l="FRE"><s0>Invertebrata</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="05" i2="X" l="ENG"><s0>Invertebrata</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="05" i2="X" l="SPA"><s0>Invertebrata</s0>
<s2>NS</s2>
</fC07>
<fN21><s1>022</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
</inist>
</record>

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{{Explor lien
   |wiki=    Wicri/Lorraine
   |area=    InforLorV4
   |flux=    PascalFrancis
   |étape=   Curation
   |type=    RBID
   |clé=     Pascal:09-0030850
   |texte=   Analyse d'un algorithme d'intelligence en essaim pour le fourragement
}}

This area was generated with Dilib version V0.6.33.
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Serveur d'exploration sur la recherche en informatique en Lorraine

Analyse d'un algorithme d'intelligence en essaim pour le fourragement

Analyse d'un algorithme d'intelligence en essaim pour le fourragement

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Descripteurs français

English descriptors

Abstract

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