A multiagent reinforcement learning algorithm to solve the maximum independent set problem

2020 ◽  
Vol 16 (1) ◽  
pp. 101-115
Author(s):  
Mir Mohammad Alipour ◽  
Mohsen Abdolhosseinzadeh
Keyword(s):  
Reinforcement Learning ◽  
Learning Algorithm ◽  
Independent Set ◽  
Maximum Independent Set ◽  
Independent Set Problem ◽  
Multiagent Reinforcement Learning ◽  
Maximum Independent Set Problem ◽  
Reinforcement Learning Algorithm

FMRQ—A Multiagent Reinforcement Learning Algorithm for Fully Cooperative Tasks

2017 ◽  
Vol 47 (6) ◽  
pp. 1367-1379 ◽  
Author(s):  
Zhen Zhang ◽  
Dongbin Zhao ◽  
Junwei Gao ◽  
Dongqing Wang ◽  
Yujie Dai
Keyword(s):  
Reinforcement Learning ◽  
Learning Algorithm ◽  
Cooperative Tasks ◽  
Multiagent Reinforcement Learning ◽  
Reinforcement Learning Algorithm

Fuzzy Maximum Independent Set Problem

2014 ◽  
Vol 687-691 ◽  
pp. 1161-1165
Author(s):  
Dong Ling Luo ◽  
Chen Yin Wang ◽  
Yang Yi ◽  
Dong Ling Zhang ◽  
Xiao Cong Zhou
Keyword(s):  
Dominating Set ◽  
Fuzzy Variable ◽  
Independent Set ◽  
Credibility Theory ◽  
Covering Problem ◽  
Maximum Independent Set ◽  
Independent Set Problem ◽  
Intelligence Algorithm ◽  
Hybrid Intelligence ◽  
Maximum Independent Set Problem

Edge covering problem, dominating set problem, and independent set problem are classic problems in graph theory except for vertex covering problem. In this paper, we study the maximum independent set problem under fuzzy uncertainty environments, which aims to search for the independent set with maximum value in a graph. First, credibility theory is introduced to describe the fuzzy variable. Three decision models are performed based on the credibility theory. A hybrid intelligence algorithm which integrates genetic algorithm and fuzzy simulation is proposed due to the unavailability of traditional algorithm. Finally, numerical experiments are performed to prove the efficiency of the fuzzy decision modes and the hybrid intelligence algorithm.

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