Williams RJ. (1992). Simple statistical gradient-following algorithms for connectionist reinforcement learning Mach Learn. 8

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References and models cited by this paper
References and models that cite this paper

Fiete IR, Fee MS, Seung HS. (2007). Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. Journal of neurophysiology. 98 [PubMed]

Florian RV. (2007). Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity. Neural computation. 19 [PubMed]

Fujita H, Ishii S. (2007). Model-based reinforcement learning for partially observable games with sampling-based state estimation. Neural computation. 19 [PubMed]

Richmond P, Buesing L, Giugliano M, Vasilaki E. (2011). Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations. PloS one. 6 [PubMed]

Roelfsema PR, van Ooyen A. (2005). Attention-gated reinforcement learning of internal representations for classification. Neural computation. 17 [PubMed]

Swinehart CD, Abbott LF. (2005). Supervised learning through neuronal response modulation. Neural computation. 17 [PubMed]

Werfel J, Xie X, Seung HS. (2005). Learning curves for stochastic gradient descent in linear feedforward networks. Neural computation. 17 [PubMed]

Whittington JCR, Bogacz R. (2017). An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity. Neural computation. 29 [PubMed]

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