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- Episode Description: In the context of reinforcement learning, an 'episode' is defined as a sequence of states, actions, and rewards that culminates in(...) Read more
- Expected Reward Description: Expected reward is a fundamental concept in reinforcement learning, referring to the anticipation of the reward that can be(...) Read more
- Exploration Rate Description: The exploration rate is a fundamental concept in reinforcement learning that refers to the probability that an agent will choose a(...) Read more
- Experience Replay Description: Experience replay is a fundamental technique in reinforcement learning, where past experiences are stored and reused to improve(...) Read more
- Epsilon-Greedy Description: Epsilon-Greedy is a strategy used in the field of reinforcement learning that seeks to balance exploration and exploitation in(...) Read more
- Exploration Strategy Description: Exploration strategy is a fundamental approach in reinforcement learning used to decide how an agent should explore the available(...) Read more
- Exploration Function Description: The exploration function in the context of reinforcement learning is a crucial component that determines how an agent interacts(...) Read more
- Exogenous Variables Description: Exogenous variables in the context of reinforcement learning refer to external factors that can influence an agent's learning(...) Read more
- Episodic Control Description: Episodic Control is an approach within reinforcement learning that focuses on decision-making through discrete episodes. In this(...) Read more
- Exploratory Behavior Description: Exploratory behavior refers to the actions taken by an agent to discover new information in its environment. This concept is(...) Read more
- Effective Learning Rate Description: The effective learning rate is a fundamental concept in the field of reinforcement learning, referring to the speed at which an(...) Read more
- Evolving Strategies Description: Evolutionary Strategies in the context of reinforcement learning are approaches that allow an agent to adapt and improve its(...) Read more
- Exploration Horizon Description: The exploration horizon in the context of reinforcement learning refers to the time frame in which an agent makes decisions and(...) Read more
- Evolving Policies Description: Evolutionary policies in the context of reinforcement learning refer to strategies that adapt and improve over time as the agent(...) Read more
- Encoder Description: An encoder is a device that converts the position or movement of an object into an electrical signal. This conversion process(...) Read more
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