#
Quiz

The best way to learn and to avoid the illusion of competence is to test yourself. This will help you to find where you need to reinforce your knowledge.

###
Q1: Chose the option which fits better when comparing different types of multi-agent environments

- Your agents aim to maximize common benefits in ____ environments
- Your agents aim to maximize common benefits while minimizing opponent’s in ____ environments

competitive, cooperative cooperative, competitive

###
Q2: Which of the following statements are true about decentralized learning?

Each agent is trained independently from the others Inputs from other agents are just considered environment data Considering other agents part of the environment makes the environment stationary

###
Q3: Which of the following statements are true about centralized learning?

It learns one common policy based on the learnings from all agents' interactions The reward is global The environment with this approach is stationary

###
Q4: Explain in your own words what is the Self-Play approach

Solution

`Self-play` is an approach to instantiate copies of agents with the same policy as your as opponents, so that your agent learns from agents with same training level.

###
Q5: When configuring Self-play , several parameters are important. Could you identify, by their definition, which parameter are we talking about?

- The probability of playing against the current self vs an opponent from a pool
- Variety (dispersion) of training levels of the opponents you can face
- The number of training steps before spawning a new opponent
- Opponent change rate

window, play_against_latest_model_ratio, save_steps, swap_steps+team_change play_against_latest_model_ratio, save_steps, window, swap_steps+team_change play_against_latest_model_ratio, window, save_steps, swap_steps+team_change swap_steps+team_change, save_steps, play_against_latest_model_ratio, window

###
Q6: What are the main motivations to use a ELO rating Score?

The score takes into account the different of skills between you and your opponent Although more points can be exchanged depending on the result of the match and given the levels of the agents, the sum is always the same It's easy for an agent to keep a high score rate It works well calculating the individual contributions of each player in a team

Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read the chapter again to reinforce (😏) your knowledge.

< > Update on GitHub