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Found 7 papers, 0 papers with code
From "What" to "When" -- a Spiking Neural Network Predicting Rare Events and Time to their Occurrence
In the context of SNNs, events are represented as spikes emitted by network neurons or input nodes.
A Spiking Binary Neuron -- Detector of Causal Links
Causal relationship recognition is a fundamental operation in neural networks aimed at learning behavior, action planning, and inferring external world dynamics.
A Spiking Neural Network Learning Markov Chain
In this paper, the question how spiking neural network (SNN) learns and fixes in its internal structures a model of external world dynamics is explored.
Model-based Reinforcement Learning
Reinforcement Learning (RL)
Neuromorphic Artificial Intelligence Systems
Modern AI systems, based on von Neumann architecture and classical neural networks, have a number of fundamental limitations in comparison with the brain.
A Spiking Neural Network Structure Implementing Reinforcement Learning
At present, implementation of learning mechanisms in spiking neural networks (SNN) cannot be considered as a solved scientific problem despite plenty of SNN learning algorithms proposed.
Neural Network Optimization for Reinforcement Learning Tasks Using Sparse Computations
This article proposes a sparse computation-based method for optimizing neural networks for reinforcement learning (RL) tasks.
A Spiking Neuron Synaptic Plasticity Model Optimized for Unsupervised Learning
Spiking neural networks (SNN) are considered as a perspective basis for performing all kinds of learning tasks - unsupervised, supervised and reinforcement learning.
