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t. e. Proximal policy optimization (PPO) is an algorithm in the field of reinforcement learning that trains a computer agent's decision function to accomplish difficult tasks. PPO was developed by John Schulman in 2017, [1] and had become the default reinforcement learning algorithm at American artificial intelligence company OpenAI. [2]
e. State–action–reward–state–action (SARSA) is an algorithm for learning a Markov decision process policy, used in the reinforcement learning area of machine learning. It was proposed by Rummery and Niranjan in a technical note [1] with the name "Modified Connectionist Q-Learning" (MCQ-L). The alternative name SARSA, proposed by Rich ...
e. 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. In classical reinforcement learning, an intelligent agent's goal ...
Inverse RL refers to inferring the reward function of an agent given the agent's behavior. Inverse reinforcement learning can be used for learning from demonstrations (or apprenticeship learning) by inferring the demonstrator's reward and then optimizing a policy to maximize returns with RL. Deep learning approaches have been used for various ...
Biderman's Chart of Coercion originated from Albert Biderman's study of Chinese psychological torture of American prisoners of war during the Korean War.. Biderman's Chart of Coercion, also called Biderman's Principles, is a table developed by sociologist Albert Biderman in 1957 to illustrate the methods of Chinese and Korean torture on American prisoners of war from the Korean War.
Machine learningand data mining. Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take actions in a dynamic environment in order to maximize the cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside ...
Thompson sampling. Thompson sampling, [1][2][3] named after William R. Thompson, is a heuristic for choosing actions that address the exploration-exploitation dilemma in the multi-armed bandit problem. It consists of choosing the action that maximizes the expected reward with respect to a randomly drawn belief.
Brainwashing, also known as mind control, menticide, coercive persuasion, thought control, thought reform, and forced re-education, is the controversial theory that purports that the human mind can be altered or controlled against a person's will by manipulative psychological techniques. [1] Brainwashing is said to reduce its subject's ability ...