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  2. Reinforcement learning from human feedback - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning...

    In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning .

  3. Reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning

    Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...

  4. Human-in-the-loop - Wikipedia

    en.wikipedia.org/wiki/Human-in-the-loop

    Humanistic intelligence, which is intelligence that arises by having the human in the feedback loop of the computational process [9] Reinforcement learning from human feedback; MIM-104 Patriot - Examples of a human-on-the-loop lethal autonomous weapon system posing a threat to friendly forces.

  5. Deep reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Deep_reinforcement_learning

    Various techniques exist to train policies to solve tasks with deep reinforcement learning algorithms, each having their own benefits. At the highest level, there is a distinction between model-based and model-free reinforcement learning, which refers to whether the algorithm attempts to learn a forward model of the environment dynamics.

  6. Exploration–exploitation dilemma - Wikipedia

    en.wikipedia.org/wiki/Exploration–exploitation...

    In the context of machine learning, the exploration–exploitation tradeoff is fundamental in reinforcement learning (RL), a type of machine learning that involves training agents to make decisions based on feedback from the environment. Crucially, this feedback may be incomplete or delayed. [4]

  7. Warehouse robot uses AI to play real-life Tetris to handle ...

    www.aol.com/warehouse-robot-uses-ai-play...

    Adaptive intelligence: Trained using Sim2Real reinforcement learning, AmbiStack can make real-time decisions, adapting to various scenarios and delivering a faster return on investment.

  8. Multi-agent reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Multi-agent_reinforcement...

    Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. [ 1 ] Each agent is motivated by its own rewards, and does actions to advance its own interests; in some environments these interests are opposed to the ...

  9. A flying phobia affects more than 25 million Americans. Here ...

    www.aol.com/plane-accidents-triggering-people...

    People who seek treatment for fear of flying usually have a debilitating phobia. (rudi_suardi/E+/Getty Images)