Exam Generative AI Leader topic 1 question 4 discussion

Actual exam question from Google's Generative AI Leader

Question #: 4
Topic #: 1

A company is developing an AI character for a video game. The AI character needs to learn how to navigate a complex environment and make decisions to achieve certain objectives within the game. When the AI takes actions that lead to positive outcomes like finding a reward or overcoming an obstacle, it receives a positive score. When it takes actions that lead to negative outcomes, like hitting a wall or losing progress, it receives a negative score. Through this process of trial and error, the AI gradually improves the character’s ability to play the game effectively. What machine learning should the company use?

A. Unsupervised learning
B. Reinforcement learning
C. Supervised learning
D. Deep learning

Show Suggested Answer

Suggested Answer: B 🗳️

by Igor_B at July 27, 2025, 11:09 a.m.

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GCP72

6 days, 20 hours ago

Selected Answer: B

The company should use reinforcement learning for the AI character. Explanation Reinforcement learning is the most suitable machine learning approach for this scenario because it focuses on how an agent (the AI character) should take actions in an environment (the game world) to maximize a cumulative reward. The AI learns through trial and error, receiving positive rewards for desirable actions and negative rewards for undesirable ones. This process of learning from feedback mirrors the described problem perfectly.

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yokoyan

2 weeks, 4 days ago

Selected Answer: B

B is correct

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Igor_B

2 weeks, 5 days ago

Selected Answer: B

B is correct. In reinforcement learning, an agent learns by interacting with its environment and receiving feedback in the form of rewards or penaltie

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