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Results tagged with neural-network
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user 5041
Artificial neural networks (ANN), are composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows information to propagate through the network to solve artificial intelligence problems without the network designer having had a model of a real system.
4
votes
Accepted
Understanding Reinforcement Learning with Neural Net (Q-learning)
In Q-Learning, on every step you will use observations and rewards to update your Q-value function:
$$
Q_{t+1}(s_t,a_t) = Q_t(s_t,a_t) + \alpha [R_{t+1}+ \gamma \underset{a'}{\max} Q_t(s_{t+1},a') …
- 1,059
4
votes
How to teach neural network a policy for a board game using reinforcement learning?
You need to use some function approximation scheme. In addition, experience replay would be useful for two reasons: (1) you want to keep past memories (2) you need to decorrelate the way to teach your …
- 1,059
1
vote
How to use a different model to deep neural network with reinforcement learning based on DQN?
Well, if you remove the DNN, I would not call that a Deep Q-Network anymore.. but it is definitely possible to remove that and still consider the approach as Reinforcement Learning.
Actually, the fun …
- 1,059
2
votes
Parallel Q-learning
I think you will like the following two papers:
Available from: http://arxiv.org/abs/1507.04296
Nair A, Srinivasan P, Blackwell S, Alcicek C, Fearon R, De Maria A, et al. Massively Parallel Methods …
- 1,059