Bellman equation, Reinforcement learning, Learning, Machine learning, Artificial neural network, Neural network

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On Oct 13, 2020
@janexwang shared
New work out by the super talented @flennerhag and colleagues on exploration: Temporal Difference Uncertainties as a Signal for Exploration https://t.co/mfSu1VbQys w/@pablosprechmann, @FrancescoVisin, A. Galashov, S. Kapturowski, D. Borsa, N. Heess, @andre_s_barreto, R. Pascanu https://t.co/AsEri4ynka
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16 Basic Credit Assignment Exploration Generalization Memory Noise Scale .25 .5 .75 1 0.0 0.01 0.5 Basic Credit Assignment Exploration Generalization Memory Noise Scale .25 .5 .75 1 agent discount factor (γ) 0.99 batch size 32 num hidden layers 2 hidden layer sizes [64, 64] ensemble size ...

arxiv.org
On Oct 13, 2020
@janexwang shared
New work out by the super talented @flennerhag and colleagues on exploration: Temporal Difference Uncertainties as a Signal for Exploration https://t.co/mfSu1VbQys w/@pablosprechmann, @FrancescoVisin, A. Galashov, S. Kapturowski, D. Borsa, N. Heess, @andre_s_barreto, R. Pascanu https://t.co/AsEri4ynka
Open

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16 Basic Credit Assignment Exploration Generalization Memory Noise Scale .25 .5 .75 1 0.0 0.01 0.5 Basic Credit Assignment Exploration Generalization Memory Noise Scale .25 .5 .75 1 ...

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Using the sampled transition and (1), we obtain the following loss function to minimize: (3)Li(θi) = Esˆ,aˆ[(yi −Q(sˆ, aˆ; θi))2] where yi = Esˆ,aˆ[r + γmaxa′ Q(s′, a′; θi−1) | sˆ, aˆ] is ...

omerbsezer/Reinforcement_learning_tutorial_with_demo

omerbsezer/Reinforcement_learning_tutorial_with_demo

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta ...

Revisiting Fundamentals of Experience Replay

Revisiting Fundamentals of Experience Replay

Deep Q-Networks (DQN) (Mnih et al., 2015) combine Q-learning with neural network function approximation and experience replay (Lin, 1992) to yield a scalable reinforcement learn- ing ...

Machine Learning Glossary

Machine Learning Glossary

Compilation of key machine-learning and TensorFlow terms, with beginner-friendly definitions.

Deep Learning cheatsheet

Deep Learning cheatsheet

Teaching page of Shervine Amidi, Graduate Student at Stanford University.

Reinforcement learning explained

Reinforcement learning explained

Reinforcement learning uses rewards and penalties to teach computers how to play games and robots how to perform tasks independently

Generative Adversarial Nets

Generative Adversarial Nets

(1) In the next section, we present a theoretical analysis of adversarial nets, essentially showing that the training criterion allows one to recover the data generating distribution as G ...