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Distinguishing System Components in a Learning Scenario
A smart home thermostat is designed to learn the optimal temperature settings for a household to maximize comfort and minimize energy costs. It observes the time of day, current indoor temperature, and whether people are present in the house. Based on these observations, it decides whether to raise, lower, or maintain the current temperature. The system receives positive feedback when energy consumption is low and negative feedback when a resident manually overrides the temperature setting. In this system, identify the 'agent' and the 'environment'. Explain your reasoning by describing the distinct role each plays in the decision-making and learning process.
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A new automated vacuum cleaner is programmed to learn the most efficient path to clean a room. It uses its sensors to detect its current location, the position of furniture, and the amount of dirt on the floor. Based on this information, it chooses to move forward, turn left, or turn right. After each cleaning session, it receives a positive signal based on the total area cleaned and a negative signal for each time it bumps into an obstacle. It uses these signals to improve its cleaning path for the next session. In this learning system, what component is the 'agent'?
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Distinguishing System Components in a Learning Scenario
A self-driving car is being trained to navigate a city. Analyze the components of this system and match each component with its correct functional role in the learning process.