A Quantum-Inspired Ant Colony Optimization for Robot Coalition Formation
A Quantum-Inspired Ant Colony Optimization (QACO), based on the concept and principles of quantum computing is proposed in this paper to improve the ability to search and optimization of Ant Colony Optimization (ACO). Each ant is a quantum individual and instead of Q-bit code, we use the probability of choosing robots, and QACO is successfully applied to solve robot coalition formation. The simulated results show that QACO has the better diversity of population and ability to search and optimization, and performs well, even with a small population, without premature convergence as compared to ACO.
QACO task allocation Large-scale robots Task Allocation Robot Coalition Formation
Zhang Yu Liu Shuhua Fu Shuai Wu Di
School of Computer Science, Northeast Normal University, Changchun 130117
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
626-631
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）