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- Self-Organizing Systems Description: Self-organizing systems are structures or processes that can organize and adapt autonomously, without the need for external(...) Read more
- Stochastic Description: The term 'stochastic' refers to processes that are determined randomly, incorporating elements of randomness in decision-making. In(...) Read more
- State-Action Pair Description: The 'State-Action Pair' is a fundamental concept in the field of reinforcement learning, referring to the combination of a specific(...) Read more
- Sarsa Description: Sarsa is a reinforcement learning algorithm classified as an on-policy control method. Its name comes from the initials of the(...) Read more
- Sparse Rewards Description: Scarce rewards in the context of reinforcement learning refer to situations where an agent receives rewards infrequently or only(...) Read more
- State Value Function Description: The State Value Function is a fundamental concept in reinforcement learning, referring to a function that estimates the expected(...) Read more
- Suboptimal Policy Description: A suboptimal policy in the context of reinforcement learning refers to a strategy or set of actions that an agent follows, but(...) Read more
- State Representation Description: State representation in reinforcement learning refers to how the current state of the environment is encoded for the agent. This(...) Read more
- Self-Play Description: Self-Play is a training method in the field of reinforcement learning where an agent interacts with itself to improve its(...) Read more
- Stochastic Policy Description: A stochastic policy in the context of reinforcement learning is an approach that defines a probability distribution over the(...) Read more
- Skill Acquisition Description: Skill acquisition in the context of reinforcement learning refers to the process by which an agent, which can be an algorithm or an(...) Read more
- State Space Description: The 'State Space' refers to the set of all possible states that an agent can occupy in a given environment. In the context of(...) Read more
- Smoothing Algorithm Description: The smoothing algorithm is a technique used in the field of reinforcement learning to reduce fluctuations in the reward signals(...) Read more
- State-Dependent Exploration Description: State-Dependent Exploration is a strategy used in reinforcement learning that adjusts an agent's exploration rate based on its(...) Read more
- Subgoal Description: A subgoal in the context of reinforcement learning refers to an intermediate goal that an agent must achieve to facilitate the(...) Read more
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