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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. 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]

  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. Fine-tuning (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Fine-tuning_(deep_learning)

    Fine-tuning is typically accomplished via supervised learning, but there are also techniques to fine-tune a model using weak supervision. [7] Fine-tuning can be combined with a reinforcement learning from human feedback-based objective to produce language models such as ChatGPT (a fine-tuned version of GPT models) and Sparrow. [8] [9]

  7. Mobileye Global (MBLY) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/finance/mobileye-global-mbly-q4-2024...

    Reinforcement learning is becoming a very critical tool in building foundation models. ... I'm wondering what feedback you're getting on DXP from your current engagements and potential additional ...

  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. Joe Alwyn Says Neighbors Called Police on Him as Kid When He ...

    www.aol.com/joe-alwyn-says-neighbors-called...

    Joe Alwyn was a prankster as a kid.. The Brutalist actor, 33, revealed on The Drew Barrymore Show that he once pulled a prank on his neighbors that landed him and his older brother a visit from ...