DocumentCode :
630846
Title :
Multi-agent discrete-time graphical games: interactive Nash equilibrium and value iteration solution
Author :
Abouheaf, Mohammed ; Lewis, Frank ; Haesaert, Sofie ; Babuska, Robert ; Vamvoudakis, Kyriakos
Author_Institution :
Arlington Res. Inst., Univ. of Texas at Arlington, Fort Worth, TX, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
4189
Lastpage :
4195
Abstract :
This paper introduces a new class of multi-agent discrete-time dynamical games known as dynamic graphical games, where the interactions between agents are prescribed by a communication graph structure. The graphical game results from multi-agent dynamical systems, where pinning control is used to make all the agents synchronize to the state of a command generator or target agent. The relation of dynamic graphical games and standard multi-player games is shown. A new notion of Interactive Nash equilibrium is introduced which holds if the agents are all in Nash equilibrium and the graph is strongly connected. The paper brings together discrete Hamiltonian mechanics, distributed multi-agent control, optimal control theory, and game theory to formulate and solve these multi-agent graphical games. The relationships between the discrete-time Hamilton Jacobi equation and discrete-time Bellman equation are used to formulate a discrete-time Hamilton Jacobi Bellman equation for dynamic graphical games. Proofs of Nash, stability, and convergence are given. A reinforcement learning value iteration algorithm is given to solve the dynamic graphical games.
Keywords :
discrete time systems; distributed control; game theory; iterative methods; learning (artificial intelligence); multi-agent systems; multi-robot systems; agent interaction; communication graph structure; discrete Hamiltonian mechanics; discrete-time Bellman equation; discrete-time Hamilton Jacobi equation; distributed multiagent control; dynamic graphical games; game theory; interactive Nash equilibrium; multiagent discrete-time graphical games; multiagent dynamical system; optimal control theory; pinning control; reinforcement learning value iteration algorithm; Electronic mail; Equations; Games; Jacobian matrices; Lead; Optical coupling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580483
Filename :
6580483
Link To Document :
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