Difference between revisions of "Deep Q Network (DQN)"
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Deep Q learning (DQN), as published in [http://arxiv.org/abs/1312.5602 Playing Atari with Deep Reinforcement Learning | Mnih et al, 2013], leverages advances in deep learning to learn policies from high dimensional sensory input. A convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards. [http://towardsdatascience.com/dqn-part-1-vanilla-deep-q-networks-6eb4a00febfb Vanilla Deep Q Networks: Deep Q Learning Explained | Chris Yoon - Towards Data Science] | Deep Q learning (DQN), as published in [http://arxiv.org/abs/1312.5602 Playing Atari with Deep Reinforcement Learning | Mnih et al, 2013], leverages advances in deep learning to learn policies from high dimensional sensory input. A convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards. [http://towardsdatascience.com/dqn-part-1-vanilla-deep-q-networks-6eb4a00febfb Vanilla Deep Q Networks: Deep Q Learning Explained | Chris Yoon - Towards Data Science] | ||
| − | Training deep neural networks to show that a novel end-to-end reinforcement learning agent, termed a deep Q-network (DQN) [http://deepmind.com/research/dqn/ Human-level control through Deep Reinforcement Learning | Deepmind] | + | Training deep neural networks to show that a novel end-to-end reinforcement learning [[Agents|agent]], termed a deep Q-network (DQN) [http://deepmind.com/research/dqn/ Human-level control through Deep Reinforcement Learning | Deepmind] |
<youtube>79pmNdyxEGo</youtube> | <youtube>79pmNdyxEGo</youtube> | ||
Revision as of 08:10, 4 February 2023
Youtube search... ...Google search
- Reinforcement Learning (RL)
- Monte Carlo (MC) Method - Model Free Reinforcement Learning
- Markov Decision Process (MDP)
- State-Action-Reward-State-Action (SARSA)
- Q Learning
- Deep Q Network (DQN)
- Deep Reinforcement Learning (DRL) DeepRL
- Distributed Deep Reinforcement Learning (DDRL)
- Evolutionary Computation / Genetic Algorithms
- Actor Critic
- Hierarchical Reinforcement Learning (HRL)
Deep Q learning (DQN), as published in Playing Atari with Deep Reinforcement Learning | Mnih et al, 2013, leverages advances in deep learning to learn policies from high dimensional sensory input. A convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards. Vanilla Deep Q Networks: Deep Q Learning Explained | Chris Yoon - Towards Data Science
Training deep neural networks to show that a novel end-to-end reinforcement learning agent, termed a deep Q-network (DQN) Human-level control through Deep Reinforcement Learning | Deepmind
