SARSA
SARSA is a reinforcement learning algorithm that updates its action-value estimates based on the current state, action, reward, next state, and next action.
Selection
Selection is the process of choosing the most suitable option from a set of alternatives based on specific criteria or goals.
Sensor
A sensor is a device that detects and measures physical or environmental changes and converts them into signals for monitoring or control.
Simulation-Based Search
Simulation-Based Search is a problem-solving technique that uses computer simulations to explore and optimize complex decision-making processes.
Skill
Skill is the ability to perform tasks effectively and efficiently through knowledge, practice, and experience.
Softmax Exploration
Softmax Exploration is a strategy in reinforcement learning that selects actions probabilistically based on their estimated values, promoting a balance between exploration and exploitation.
Sparse Reward
Sparse reward is a type of feedback in reinforcement learning where signals are given infrequently, often only after a series of actions or upon task completion.
State-Value
State-value is a function that estimates the expected return or future rewards achievable from a given state in a decision-making process.
Stochastic Game
Stochastic game is a strategic game model where outcomes depend on probabilistic transitions between states and the decisions of multiple players.
Structural Credit Assignment
Structural Credit Assignment is the process of determining the contribution of individual components within a complex system to the overall outcome or performance.
Subgoal
A subgoal is a smaller, manageable objective set within a larger goal to help systematically achieve the main outcome.