A Computational Model of Match Decision-Making Problem Using Spiking SHESN with Reward-Modulated Reinforcement Learning.
Zhidong DengGuorun YangPublished in: ICONIP (1) (2015)
Keyphrases
- computational model
- reinforcement learning
- decision making
- action selection
- basal ganglia
- function approximation
- computational models
- state space
- decision makers
- computational framework
- eligibility traces
- cognitive modeling
- model free
- reinforcement learning algorithms
- feed forward
- language acquisition
- working memory
- multi agent
- reward function
- learning algorithm
- decentralized decision making
- bio inspired
- markov decision processes
- temporal difference
- cognitive architecture
- long run
- spiking neural networks
- dynamic programming
- partially observable environments
- visual processing
- neural network
- optimal policy
- single neuron
- reward shaping
- machine learning