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A Distributed, Complete Method for MultiAgent Constraint Optimization

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Adrian Petcu, Boi Faltings. DCR/CP04, September 27th 2004, Toronto, Canada ... Adrian Petcu, Boi Faltings. adrian.petcu_at_epfl.ch; boi.faltings_at_epfl.ch ... – PowerPoint PPT presentation

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Title: A Distributed, Complete Method for MultiAgent Constraint Optimization


1
A Distributed, Complete Method forMulti-Agent
Constraint Optimization
  • Adrian Petcu, Boi Faltingsadrian.petcu_at_epfl.ch
    boi.faltings_at_epfl.ch Artificial Intelligence
    LaboratorySwiss Federal Institute of Technology
    (EPFL)IN-Ecublens, 1015 Lausanne,
    Switzerlandhttp//liawww.epfl.ch/People/apetcu/

2
Overview
  • Problem description
  • DTREE tree propagation algorithm
  • CyPro utility propagation with cycles
  • CyCopt splitting the problem
  • Conclusions future work

3
Multi-agent Constraint Optimization (MCOP)
  • Constraint Optimization Problems (COP) tuple
    ltX, D, Rgt
  • MCOP multi-agent version of COP in general,
    one variable per agent
  • MCOP solutions have a quality to be maximized
    (constraints are utility functions, not
    predicates)

4
Overview
  • Problem description
  • DTREE tree propagation algorithm
  • CyPro utility propagation with cycles
  • CyCopt splitting the problem
  • Conclusions future work

5
DTREE (1) main ideas
  • Distributed utility propagation algorithm
  • The leaves of the tree initiate the propagation,
    and then all nodes forward messages by the k-1
    rule
  • Nodes terminate after receiving all k messages (k
    neighbors, one message each)
  • 2 x (n-1) fixed size messages transmitted.

6
DTREE (2) message dynamics
x0
x4
x1
x3
x6
x7
x5
x2
Done!
7
DTREE (3) computation details
X2?X1
X1?X0
X3?X1
R(X1,X0)
8
Overview
  • Problem description
  • DTREE tree propagation algorithm
  • CyPro utility propagation with cycles
  • CyCopt splitting the problem
  • Conclusions future work

9
CyPro(1)
  • Idea reduce a complex problem (with cycles) to
    separate cycle-free parts
  • Choose a set of cycle cut nodes, and initiate
    propagation from them.
  • Explore all combinations of values of CC nodes,
    and have them assemble the results

10
CyPro(2)
normal nodes forward by the k-1 rule, and
combine contexts
Xj,Xk
Xj,Xk
Xkvk0
Xjvj0
Tree parts send messages as before
Cycle cuts act like leaves
11
Overview
  • Problem description
  • DTREE tree propagation algorithm
  • CyPro utility propagation with cycles
  • CyCopt splitting the problem
  • Conclusions future work

12
CyCOpt(1)
  • Cyclic sub graphs can be processed independently
    if they are connected through only one CC node.
  • A meta-tree is formed by CC nodes and cyclic sub
    graphs
  • Processing in the meta-tree proceeds like in DTREE

13
CyCOpt(2)
Xj
Xk
14
Overview
  • Problem description
  • DTREE tree propagation algorithm
  • CyPro utility propagation with cycles
  • CyCopt splitting the problem
  • Conclusions future work

15
Conclusions future work
  • Linear message size, linear memory
  • Reduction in complexity from domn gtgt domCCgtgt
    domCCs in largest subgraph
  • Choice of the cycle cutset is important
  • Exhaustive search within a cyclic subgraph is
    maybe not necessary

16
References
  • F. Kschischang, B.Frey, and H. Loeliger. Factor
    graphs and the sum-product algorithm. IEEE
    TRANSACTIONS ON INFORMATION THEORY, 2001.
  • Rina Dechter. Constraint Processing. Morgan
    Kaufmann, 2003.
  • P. Modi, W. Shen, M. Tambe, and M. Yokoo. An
    asynchronous complete method for distributed
    constraint optimization, 2003.
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