AsymDPOP: Complete Inference for Asymmetric Distributed Constraint Optimization Problems

05/28/2019
by   Yanchen Deng, et al.
0

Asymmetric distributed constraint optimization problems (ADCOPs) are an emerging model for coordinating agents with personal preferences. However, the existing inference-based complete algorithms which use local eliminations cannot be applied to ADCOPs, as the parent agents are required to transfer their private functions to their children. Rather than disclosing private functions explicitly to facilitate local eliminations, we solve the problem by enforcing delayed eliminations and propose AsymDPOP, the first inference-based complete algorithm for ADCOPs. To solve the severe scalability problems incurred by delayed eliminations, we propose to reduce the memory consumption by propagating a set of smaller utility tables instead of a joint utility table, and to reduce the computation efforts by sequential optimizations instead of joint optimizations. The empirical evaluation indicates that AsymDPOP significantly outperforms the state-of-the-arts, as well as the vanilla DPOP with PEAV formulation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/16/2019

PT-ISABB: A Hybrid Tree-based Complete Algorithm to Solve Asymmetric Distributed Constraint Optimization Problems

Asymmetric Distributed Constraint Optimization Problems (ADCOPs) have em...
research
06/07/2017

Improving Max-Sum through Decimation to Solve Loopy Distributed Constraint Optimization Problems

In the context of solving large distributed constraint optimization prob...
research
09/13/2019

AED: An Anytime Evolutionary DCOP Algorithm

Evolutionary optimization is a generic population-based metaheuristic th...
research
09/13/2019

A Particle Swarm Based Algorithm for Functional Distributed Constraint Optimization Problems

Distributed Constraint Optimization Problems (DCOPs) are a widely studie...
research
02/04/2014

Asymmetric Distributed Constraint Optimization Problems

Distributed Constraint Optimization (DCOP) is a powerful framework for r...
research
03/08/2022

Mini-batch stochastic three-operator splitting for distributed optimization

We consider a network of agents, each with its own private cost consisti...
research
11/28/2019

HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-based Inference

Search and inference are two main strategies for optimally solving Distr...

Please sign up or login with your details

Forgot password? Click here to reset