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- Overestimation Bias Description: Overestimation bias is a phenomenon that occurs in reinforcement learning, where the estimated value of an action is systematically(...) Read more
- Optimal Stochastic Control Description: Optimal Stochastic Control is a theoretical framework used to make decisions in uncertain environments, aiming to maximize expected(...) Read more
- Optimal Policy Iteration Description: Optimal Policy Iteration is a fundamental algorithm in the field of reinforcement learning, used to find the optimal policy of an(...) Read more
- Optimal Action Selection Description: Optimal Action Selection is a fundamental concept in the field of Reinforcement Learning, referring to the process of choosing the(...) Read more
- Optimal Stochastic Policy Description: The Optimal Stochastic Policy is a fundamental concept in the field of reinforcement learning, referring to a strategy that(...) Read more
- Optimal Reward Description: Optimal reward in the context of reinforcement learning refers to the maximum reward an agent can achieve by following an optimal(...) Read more
- Overestimation Description: Overestimation in the context of reinforcement learning refers to the phenomenon where an agent evaluates a value or outcome as(...) Read more
- Optimal Stochastic Policy Iteration Description: The Optimal Stochastic Policy Iteration is a fundamental algorithm in the field of reinforcement learning that combines policy(...) Read more
- Outcome Probability Description: The probability of outcome in the context of reinforcement learning refers to the measure by which an agent can anticipate a(...) Read more
- Overtraining Description: Overfitting is a phenomenon that occurs in the training of machine learning models, including a wide range of algorithms and(...) Read more
- Oracles Description: Oracles in the context of blockchain technology are systems that enable interoperability between different networks and protocols,(...) Read more
- One-shot Learning Description: One-Shot Learning is an approach within machine learning that allows models to learn to classify or recognize objects from a single(...) Read more
- Overlapping Distributions Description: Overlapping distributions refer to situations where two or more probability distributions share some common outcomes. This(...) Read more
- Object Proposal Description: The object proposal in the context of convolutional neural networks (CNN) refers to a method used in object detection that aims to(...) Read more
- Oversegmentation Description: Over-segmentation is a phenomenon that occurs in the realm of convolutional neural networks (CNNs) when an image is divided into(...) Read more
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