Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms
@article{Leeuwen2020HybridDS, title={Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms}, author={Cornelis Jan van Leeuwen and Przemyzlaw Pawelczak}, journal={ArXiv}, year={2020}, volume={abs/2009.02240} }
We propose a novel method for expediting both symmetric and asymmetric Distributed Constraint Optimization Problem (DCOP) solvers. The core idea is based on initializing DCOP solvers with greedy fast non-iterative DCOP solvers. This is contrary to existing methods where initialization is always achieved using a random value assignment. We empirically show that changing the starting conditions of existing DCOP solvers not only reduces the algorithm convergence time by up to 50\%, but also…
References
SHOWING 1-10 OF 29 REFERENCES
CoCoA: A Non-Iterative Approach to a Local Search (A)DCOP Solver
- Computer ScienceAAAI
- 2017
The key strategy of the algorithm is to use a semi-greedy approach in which knowledge is distributed amongst neighboring agents, and assigning a value only once instead of an iterative approach, which allows it to very quickly find solutions of high quality with a smaller communication overhead.
Explorative anytime local search for distributed constraint optimization
- Computer ScienceArtif. Intell.
- 2014
Distributed Breakout: Beyond Satisfaction
- Computer ScienceIJCAI
- 2016
In the theoretical analysis, it is proven that some variants of GDBA are equivalent for certain problems, and it is proved that other variants may find suboptimal solutions even on tree topologies where DBA is complete.
An Iterative Refined Max-sum_AD Algorithm via Single-side Value Propagation and Local Search
- Computer ScienceAAMAS
- 2017
It is illustrated that value propagation can eliminate the inconsistent contexts in Max-sum_AD and break ties among utilities, but it also restricts the exploration brought by Max-Sum, so that the methods are independent of initial assignments and less likely to get stuck in local optima.
A Scalable Method for Multiagent Constraint Optimization
- Computer ScienceIJCAI
- 2005
A new, complete method for distributed constraint optimization, based on dynamic programming, inspired by the sum-product algorithm, which is correct only for tree-shaped constraint networks is extended using a pseudotree arrangement of the problem graph.
Adopt: asynchronous distributed constraint optimization with quality guarantees
- Computer ScienceArtif. Intell.
- 2005
Asynchronous Forward Bounding for Distributed COPs
- Computer ScienceJ. Artif. Intell. Res.
- 2009
Experimental evaluation shows that AFB outperforms synchronous branch and bound by many orders of magnitude, and produces a phase transition as the tightness of the problem increases, an analogous effect to the phase transition that has been observed when local consistency maintenance is applied to MaxCSPs.
Distributed Algorithms for DCOP: A Graphical-Game-Based Approach
- Computer SciencePDCS
- 2004
A decomposition of DCOP into a graphical game and the evolution of various stochastic and deterministic algorithms are investigated to prove monotonicity properties of certain approaches and detail arguments about equilibrium sets that offer insight into the tradeoffs involved in leveraging efficiency and solution quality.
Local search for distributed asymmetric optimization
- Computer ScienceAAMAS
- 2010
The present paper proposes a general framework for Asymmetric DCOPs (ADCOPs), a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned by different agents.
Max/min-sum distributed constraint optimization through value propagation on an alternating DAG
- Computer ScienceAAMAS
- 2012
A version of the Max-sum algorithm that operates on an alternating directed acyclic graph (Max-sum_AD), which guarantees convergence in linear time is proposed, which reveals a large improvement in the quality of the solutions produced by Max-Sum_AD with value propagation (VP), when solving problems which include cycles.