Combining Spatial Optimization and Multi-Agent Temporal Difference Learning for Task Assignment in Uncertain Crowdsourcing

2019 ◽  
Vol 22 (6) ◽  
pp. 1447-1465 ◽  
Author(s):  
Yong Sun ◽  
Wenan Tan
2020 ◽  
Vol 18 (4) ◽  
pp. 379-389
Author(s):  
Zhinan Peng ◽  
Jiangping Hu ◽  
Rui Luo ◽  
Bijoy K. Ghosh

2001 ◽  
Vol 13 (10) ◽  
pp. 2221-2237 ◽  
Author(s):  
Rajesh P. N. Rao ◽  
Terrence J. Sejnowski

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are potentiated, while those that are activated a few milliseconds after are depressed. We show that such a mechanism can implement a form of temporal difference learning for prediction of input sequences. Using a biophysical model of a cortical neuron, we show that a temporal difference rule used in conjunction with dendritic backpropagating action potentials reproduces the temporally asymmetric window of Hebbian plasticity observed physiologically. Furthermore, the size and shape of the window vary with the distance of the synapse from the soma. Using a simple example, we show how a spike-timing-based temporal difference learning rule can allow a network of neocortical neurons to predict an input a few milliseconds before the input's expected arrival.


Author(s):  
Peng Jian-liang ◽  
Sun Xiu-xia ◽  
Zhu Fan ◽  
Li Xiang-qing
Keyword(s):  

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