250 citations · 564 across the 20 of their papers we have counts for
3 papers · 1 filter
Reinforcement Learning with Feedback-modulated TD-STDP
Stephen Chung, Robert Kozma
Spiking neuron networks have been used successfully to solve simple reinforcement learning tasks with continuous action set applying learning rules based on spike-timing-dependent…
Reinforcement learning with a network of spiking agents
Sneha Aenugu, Abhishek Sharma, Sasikiran Yelamarthi +3
Neuroscientific theory suggests that dopaminergic neurons broadcast global reward prediction errors to large areas of the brain influencing the synaptic plasticity of the neurons i…
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games
Devdhar Patel, Hananel Hazan, Daniel J. Saunders +2
Deep Reinforcement Learning (RL) demonstrates excellent performance on tasks that can be solved by trained policy. It plays a dominant role among cutting-edge machine learning appr…