Reinforcement Learning (RL) - Revision history

BPeat at 12:49, 24 April 2025

2025-04-24T12:49:07Z

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 * [https://towardsdatascience.com/develop-your-first-ai-agent-deep-q-learning-375876ee2472 Develop Your First AI Agent: Deep Q-Learning | Heston Vaughan - Towards Data Science]
 * [https://www.zdnet.com/article/ai-has-grown-beyond-human-knowledge-says-googles-deepmind-unit/ AI has grown beyond human knowledge, says Google's DeepMind unit | Tiernan Ray - Znet] ... A new agentic approach called 'streams' will let AI models learn from the experience of the environment without human 'pre-judgment'.
 <b>Reinforcement Learning (RL)</b> A technique that teaches an AI model to find the best result through trial and error and receiving rewards or punishments based on its results, often enhanced by human feedback for games and complex tasks.

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 * [https://www.nature.com/articles/s41586-023-06004-9 Faster sorting algorithms discovered using deep reinforcement learning | D. Mankowitz, A. Michi, A. Zhernov, M. Gelmi, M. Selvi, C. Paduraru, E. Leurent, S. Iqbal, J. Lespiau, A. Ahern, T. Köppe, K. Millikin, S. Gaffney, S. Elster, J. Broshear, C. Gamble, K. Milan, R. Tung, M. Hwang, T. Cemgil, M. Barekatain, Y. Li, A. Mandhane, T. Hubert, D. Silver - Nature] ... Deep reinforcement learning has been used to improve computer code by treating the task as a game — with no special knowledge needed on the part of the player. The result has already worked its way into countless programs.
 * [https://towardsdatascience.com/develop-your-first-ai-agent-deep-q-learning-375876ee2472 Develop Your First AI Agent: Deep Q-Learning | Heston Vaughan - Towards Data Science]
 <b>Reinforcement Learning (RL)</b> A technique that teaches an AI model to find the best result through trial and error and receiving rewards or punishments based on its results, often enhanced by human feedback for games and complex tasks.

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 * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
 * [[Reinforcement Learning - Games, Self-driving Vehicles, Drones, Robotics, Management, Finance]]
-* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Grok]] | [https://x.ai/ xAI] ... [[Groq]] ... [[Ernie]] | [[Baidu]] ... [[Deepseek]] | [[Alibaba]]
+* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Grok]] | [https://x.ai/ xAI] ... [[Groq]] ... [[Ernie]] | [[Baidu]] ... [[DeepSeek]]
 * [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
 * [[Inverse Reinforcement Learning (IRL)]]

@@ Line 22: / Line 22: @@
 * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
 * [[Reinforcement Learning - Games, Self-driving Vehicles, Drones, Robotics, Management, Finance]]
 * [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
 * [[Inverse Reinforcement Learning (IRL)]]

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 * [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
 * [[Inverse Reinforcement Learning (IRL)]]
-* [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games -Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]]
+* [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games - Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]] ... [[Game Design | Design]]
 * [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
 * [[Simulation]] ... [[Simulated Environment Learning]] ... [[World Models]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]

@@ Line 26: / Line 26: @@
 * [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games -Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]]
 * [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
-* [[Simulation]] ... [[Simulated Environment Learning]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]
+* [[Simulation]] ... [[Simulated Environment Learning]] ... [[World Models]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]
 * [[Policy]]   ... [[Policy vs Plan]] ... [[Constitutional AI]] ... [[Trust Region Policy Optimization (TRPO)]] ... [[Policy Gradient (PG)]] ... [[Proximal Policy Optimization (PPO)]]
 * [[Multi-Task Learning (MTL)]] ... [[SMART - Multi-Task Deep Neural Networks (MT-DNN)]]

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 * [https://learn.microsoft.com/en-us/azure/architecture/solution-ideas/articles/machine-teaching Use subject matter expertise in machine teaching and reinforcement learning | Microsoft]
 * [https://www.nature.com/articles/s41586-023-06004-9 Faster sorting algorithms discovered using deep reinforcement learning | D. Mankowitz, A. Michi, A. Zhernov, M. Gelmi, M. Selvi, C. Paduraru, E. Leurent, S. Iqbal, J. Lespiau, A. Ahern, T. Köppe, K. Millikin, S. Gaffney, S. Elster, J. Broshear, C. Gamble, K. Milan, R. Tung, M. Hwang, T. Cemgil, M. Barekatain, Y. Li, A. Mandhane, T. Hubert, D. Silver - Nature] ... Deep reinforcement learning has been used to improve computer code by treating the task as a game — with no special knowledge needed on the part of the player. The result has already worked its way into countless programs.
 <b>Reinforcement Learning (RL)</b> A technique that teaches an AI model to find the best result through trial and error and receiving rewards or punishments based on its results, often enhanced by human feedback for games and complex tasks.
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 [http://venturebeat.com/2021/06/09/deepmind-says-reinforcement-learning-is-enough-to-reach-general-ai/ Some scientists believe that assembling multiple narrow AI modules will produce higher intelligent systems.]</i>
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