A particle swarm based algorithm for functional distributed constraint optimization problems
Abstract Distributed Constraint Optimization Problems (DCOPs) are a widely studied
constraint handling framework. The objective of a DCOP algorithm is to optimize a global …
constraint handling framework. The objective of a DCOP algorithm is to optimize a global …
[PDF][PDF] A local search based approach to solve continuous DCOPs
Distributed Constraint Optimization Problems (DCOPs) are a powerful framework to model
cooperative multi-agent systems wherein multiple agents communicate directly or indirectly …
cooperative multi-agent systems wherein multiple agents communicate directly or indirectly …
[PDF][PDF] New algorithms for continuous distributed constraint optimization problems
ABSTRACT Distributed Constraint Optimization Problems (DCOPs) are a powerful tool to
model multi-agent coordination problems that are distributed by nature. The formulation is …
model multi-agent coordination problems that are distributed by nature. The formulation is …
AED: An anytime evolutionary DCOP algorithm
Evolutionary optimization is a generic population-based metaheuristic that can be adapted
to solve a wide variety of optimization problems and has proven very effective for …
to solve a wide variety of optimization problems and has proven very effective for …
[PDF][PDF] Speeding up incomplete GDL-based algorithms for multi-agent optimization with dense local utilities
Incomplete GDL-based algorithms including Maxsum and its variants are important methods
for multi-agent optimization. However, they face a significant scalability challenge as the …
for multi-agent optimization. However, they face a significant scalability challenge as the …
Dynamic continuous distributed constraint optimization problems
Abstract The Distributed Constraint Optimization Problem (DCOP) formulation is a powerful
tool to model multi-agent coordination problems that are distributed by nature. While DCOPs …
tool to model multi-agent coordination problems that are distributed by nature. While DCOPs …
A Population-Based Search Approach to Solve Continuous Distributed Constraint Optimization Problems
X Liao, KD Hoang - Applied Sciences, 2024 - mdpi.com
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely
used in multi-agent collaborative modeling. The traditional DCOP framework assumes that …
used in multi-agent collaborative modeling. The traditional DCOP framework assumes that …
A generic approach to accelerating belief propagation based incomplete algorithms for dcops via a branch-and-bound technique
Belief propagation approaches, such as Max-Sum and its variants, are important methods to
solve large-scale Distributed Constraint Optimization Problems (DCOPs). However, for …
solve large-scale Distributed Constraint Optimization Problems (DCOPs). However, for …
Utility distribution matters: Enabling fast belief propagation for multi-agent optimization with dense local utility function
Belief propagation algorithms including Max-sum and its variants are important methods for
multi-agent optimization. However, they face a significant scalability challenge as the …
multi-agent optimization. However, they face a significant scalability challenge as the …
Learning optimal temperature region for solving mixed integer functional DCOPs
Distributed Constraint Optimization Problems (DCOPs) are an important framework for
modeling coordinated decision-making problems in multi-agent systems with a set of …
modeling coordinated decision-making problems in multi-agent systems with a set of …