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131 lines
4.3 KiB
Plaintext
131 lines
4.3 KiB
Plaintext
# Quiz
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The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
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### Q1: Which of the following tools are specifically designed for video games development?
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<Question
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choices={[
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{
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text: "Unity (C#)",
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explain: "",
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correct: true,
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},
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{
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text: "Unreal Engine (C++)",
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explain: "",
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correct: true,
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},
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{
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text: "Godot (GDScript, C++, C#)",
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explain: "",
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correct: true,
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},
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{
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text: "JetBrains' Rider",
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explain: "Although useful for its support of C# for Unity, it's not a video games development IDE",
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correct: false,
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},
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{
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text: "JetBrains' CLion",
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explain: "Although useful for its support of C++ for Unreal Engine, it's not a video games development IDE",
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correct: false,
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},
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{
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text: "Microsoft Visual Studio and Visual Studio Code",
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explain: "Including support for both Unity and Unreal, they are generic IDEs, not video games oriented.",
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correct: false,
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},
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]}
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/>
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### Q2: What of the following statements are true about Unity ML-Agents?
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<Question
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choices={[
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{
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text: "Unity ´Scene´ objects can be used to create learning environments",
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explain: "",
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correct: true,
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},
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{
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text: "Unit ML-Agents allows you to create and train your agents using Reinforcement Learning",
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explain: "",
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correct: true,
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},
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{
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text: "Its `Communicator` component manages the communication between Unity's C# Environments/Agents and a Python back-end",
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explain: "",
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correct: true,
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},
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{
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text: "The training process uses Reinforcement Learning algorithms, implemented in Pytorch",
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explain: "",
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correct: true,
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},
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{
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text: "Unity ML-Agents only support Proximal Policy Optimization (PPO)",
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explain: "No, Unity ML-Agents supports several families of algorithms, including Actor-Critic which is going to be explained in the next section",
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correct: false,
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},
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{
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text: "It includes a Gym Wrapper and a multi-agent version of it called `PettingZoo`",
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explain: "",
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correct: true,
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},
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]}
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/>
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### Q3: Fill the missing letters
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- In Unity ML-Agents, the Policy of an Agent is called a b _ _ _ n
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- The component in charge of orchestrating the agents is called the _ c _ _ _ m _
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<details>
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<summary>Solution</summary>
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- b r a i n
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- a c a d e m y
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</details>
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### Q4: Define with your own words what is a `raycast`
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<details>
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<summary>Solution</summary>
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A raycast is (most of the times) a linear projection, as a `laser` which aims to detect collisions through objects.
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</details>
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### Q5: Which are the differences between capturing the environment using `frames` or `raycasts`?
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<Question
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choices={[
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{
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text: "By using `frames`, the environment is defined by each of the pixels of the screen. By using `raycasts`, we only send a sample of those pixels.",
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explain: "`Raycasts` don't have anything to do with pixels. They are linear projections (lasers) that we spawn to look for collisions.",
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correct: false,
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},
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{
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text: "By using `raycasts`, the environment is defined by each of the pixels of the screen. By using `frames`, we spawn a (usually) line to check what objects it collides with",
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explain: "It's the other way around - `frames` collect pixels, `raycasts` check for collisions.",
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correct: false,
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},
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{
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text: "By using `frames`, we collect all the pixels of the screen, which define the environment. By using `raycast`, we don't use pixels, we spawn (normally) lines and check their collisions",
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explain: "",
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correct: true,
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},
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]}
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/>
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### Q6: Name several environment and agent input variables used to train the agent in the Snowball or Pyramid environments
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<details>
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<summary>Solution</summary>
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- Collisions of the raycasts spawned from the agent detecting blocks, (invisible) walls, stones, our target, switches, etc.
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- Traditional inputs describing agent features, as its speed
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- Boolean vars, as the switch (on/off) in Pyramids or the `can I shoot?` in the SnowballTarget.
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</details>
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Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read the chapter again to reinforce (😏) your knowledge.
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