A New Learning Method Inspired by Cooperative Transportation in Ants:Modelling and Simulation
Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbors Discounted Information (NDI) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NDI learning, the I-interval neighbors information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NDI learning are recommended by controlling the parameters according to time-relativity of concrete tasks. By applying this learning method, the cooperative transport of ants is simulated. Experiment results show that the transport process in simulation is very similar to the phenomenon in natural world, which proves the designed learning mechanisms rationality.
neighbors discounted information learning(NDI learning) I-interval neighbor discounted reward qlearning swarm intelligence
Fuming LI Peilin CHENG
College of Economics and Management, YanShan University, Qinhuangdao, China School of Electrical Engineering YanShan University, Qinhuangdao, China
国际会议
太原
英文
586-590
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）