Question
Which of the following accurately describes how
reinforcement learning differs from supervised learning in machine learning?Solution
Reinforcement learning (RL) differs fundamentally from supervised learning (SL) in its focus and methodology. RL is designed to handle sequential decision-making problems, where an agent interacts with an environment and learns by maximizing cumulative rewards over time. Key distinctions include: 1. Sequential Decision-Making: RL considers the state of an environment at each step and takes actions that impact future states. For example, in a robot navigating a maze, each action influences the subsequent positions, making the process dynamic and sequential. 2. Absence of Labeled Data: Unlike SL, RL does not rely on labeled input-output pairs. Instead, it uses reward signals as feedback to adjust its actions. 3. Cumulative Reward Optimization: RL aims to maximize long-term benefits, taking into account delayed rewards. This approach is essential in tasks like game-playing or resource allocation. In contrast, SL operates on fixed datasets where inputs and corresponding outputs are predefined, making it effective for tasks like classification and regression but unsuitable for dynamic environments. Why Other Options Are Incorrect: тАв A) RL requires labeled data: RL does not use labeled datasets; it relies on interaction and feedback from the environment. тАв B) SL optimizes based on immediate feedback: SL does not work with feedback; it uses labeled data to minimize loss. RL focuses on cumulative rewards, not immediate feedback. тАв C) RL operates without feedback: RL explicitly depends on feedback in the form of rewards or penalties. тАв D) SL is used for exploration: SL predicts based on historical data, whereas RL uses exploration to improve decision-making policies.
рд╢реБрджреНрдз рд╢рдмреНрдж рд╣реИ
'рд╕рдореНрдореБрдЦ' рдХрд╛ рд╡рд┐рдкрд░реАрддрд╛рд░реНрдердХ рд╣реИ
рдорд╛рддреНрд░рд╛рдПрдБ рдХрд┐рддрдиреЗ рдкреНрд░рдХрд╛рд░ рдХреЗ рд╣реЛрддреЗ рд╣реИ ?
┬арддрддреНрд╕рдо рд╢рдмреНрдж рд╣реИ
рдХрд┐рд╕ рд╡рд╛рдХреНрдпреЗ рдореЗрдВ рднрд╡рд╡рд╛рдЪреНрдп рдХрд╛ рдкреНрд░рдпреЛрдЧ рд╣реБрдЖ рд╣реИ ?
'рдзрдиреНрдпрд╡рд╛рдж' рд╢рдмреНрдж рдореЗрдВ рдХреМрди-рд╕рд╛ рдЙрдкрд╕рд░реНрдЧ рд╣реИ?
рдирд┐рдореНрдирд▓рд┐рдЦрд┐рдд рдореЗрдВ рд╕реЗ рд╕реНрддреНрд░реА рдХрд╛ рдкрд░реНрдпрд╛рдпрд╡рд╛рдЪреА рдирд╣реАрдВ рд╣реИ :
рдЕрдзреЛрд▓рд┐рдЦрд┐рдд рдореЗрдВ рд╕реЗ рдХреМрди-рд╕рд╛ рдпреБрдЧреНрдо рд╡рд┐рд╢реЗрд╖рдг рдирд╣реАрдВ рд╣реИрдВ?
' рдЬрд▓реЗ рдкрд░ рдирдордХ рдЫрд┐рдбрд╝рдХрдирд╛ ' рдореБрд╣рд╛рд╡рд░реЗ рдХрд╛ рд╕рдЯреАрдХ рдЕрд░реНрде рд╣реИ :
рдХреМрди-рд╕рд╛ рд╢рдмреНрдж рд╢реБрджреНрдз рдирд╣реАрдВ рд╣реИ