Advanced Actor Critic (A2C) - Revision history

BPeat: Text replacement - "http:" to "https:"

2023-03-28T00:29:13Z

Text replacement - "http:" to "https:"

BPeat at 11:15, 6 July 2020

2020-07-06T11:15:33Z

BPeat at 11:12, 6 July 2020

2020-07-06T11:12:27Z

BPeat at 20:20, 3 July 2020

2020-07-03T20:20:58Z

BPeat at 20:20, 3 July 2020

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BPeat at 20:16, 3 July 2020

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BPeat at 19:38, 3 July 2020

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BPeat at 19:37, 3 July 2020

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@@ Line 5: / Line 5: @@
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning YouTube search...]
+[https://www.youtube.com/results?search_query=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning YouTube search...]
-[http://www.google.com/search?q=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning ...Google search]
+[https://www.google.com/search?q=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning ...Google search]
 * [[Reinforcement Learning (RL)]]
@@ Line 23: / Line 23: @@
 ** [[Hierarchical Reinforcement Learning (HRL)]]
-* [http://towardsdatascience.com/advanced-reinforcement-learning-6d769f529eb3 Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning | Joyce Xu - Towards Data Science]
+* [https://towardsdatascience.com/advanced-reinforcement-learning-6d769f529eb3 Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning | Joyce Xu - Towards Data Science]
 * [[Policy Gradient (PG)]]
 * [[Proximal Policy Optimization (PPO)]]
-A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science]
+A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [https://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science]

@@ Line 18: / Line 18: @@
 ** [[Evolutionary Computation / Genetic Algorithms]]
 ** [[Actor Critic]]
 *** Advanced Actor Critic (A2C)
 *** [[Lifelong Latent Actor-Critic (LILAC)]]
 ** [[Hierarchical Reinforcement Learning (HRL)]]
 * [http://towardsdatascience.com/advanced-reinforcement-learning-6d769f529eb3 Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning | Joyce Xu - Towards Data Science]
 * [[Policy Gradient (PG)]]

@@ Line 8: / Line 8: @@
 [http://www.google.com/search?q=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning ...Google search]
-* [[Reinforcement Learning (RL)]]:
+* [[Reinforcement Learning (RL)]]
 ** [[Monte Carlo]] (MC) Method - Model Free Reinforcement Learning
 ** [[Markov Decision Process (MDP)]]
 ** [[Q Learning]]
-** [[State-Action-Reward-State-Action (SARSA)]]
+*** [[Deep Q Network (DQN)]]
 ** [[Deep Reinforcement Learning (DRL)]] DeepRL
 ** [[Distributed Deep Reinforcement Learning (DDRL)]]
 ** [[Evolutionary Computation / Genetic Algorithms]]
 ** [[Actor Critic]]
 *** Advanced Actor Critic (A2C)
 *** [[Asynchronous Advantage Actor Critic (A3C)]]
 *** [[Lifelong Latent Actor-Critic (LILAC)]]
 ** [[Hierarchical Reinforcement Learning (HRL)]]

@@ Line 25: / Line 25: @@
 * [[Policy Gradient (PG)]]
 * [[Proximal Policy Optimization (PPO)]]
 A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science]
 <youtube>GlwgeUmhWIM</youtube>

@@ Line 24: / Line 24: @@
 * [http://towardsdatascience.com/advanced-reinforcement-learning-6d769f529eb3 Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning | Joyce Xu - Towards Data Science]
 * [[Policy Gradient (PG)]]
 A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science]

@@ Line 27: / Line 27: @@
 A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science]
+<youtube>GlwgeUmhWIM</youtube>
 <youtube>asBFJACi698</youtube>
 <youtube>9MlRgyav_2c</youtube>
 <youtube>GCfUdkCL7FQ</youtube>
 <youtube>JykBihC0TvM</youtube>

← Older revision		Revision as of 19:38, 3 July 2020
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	A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C \| Chris Yoon - Towards Data Science]		A2C produces comparable performance to [[Asynchronous Advantage Actor Critic (A3C)]] while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. [http://towardsdatascience.com/understanding-actor-critic-methods-931b97b6df3f Understanding Actor Critic Methods and A2C \| Chris Yoon - Towards Data Science]
		+

	<youtube>asBFJACi698</youtube>		<youtube>asBFJACi698</youtube>

← Older revision		Revision as of 19:28, 3 July 2020
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	<youtube>9MlRgyav_2c</youtube>		<youtube>9MlRgyav_2c</youtube>
	<youtube>GCfUdkCL7FQ</youtube>		<youtube>GCfUdkCL7FQ</youtube>
		+	<youtube>JykBihC0TvM</youtube>

← Older revision		Revision as of 19:27, 3 July 2020
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	<youtube>asBFJACi698</youtube>		<youtube>asBFJACi698</youtube>
		+	<youtube>9MlRgyav_2c</youtube>
		+	<youtube>GCfUdkCL7FQ</youtube>