Reaktor race-condition: Difference between revisions
From wikiluntti
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https://www.youtube.com/results?search_query=neat+algorithm+game | https://www.youtube.com/results?search_query=neat+algorithm+game | ||
https://medium.com/@nirajsawant2313/a-simple-ai-using-neat-neuroevolution-of-augmenting-topologies-ae1b7d8f4a5e | |||
* Inputs: The relative position of the ball to the paddle, velocity of the ball. Totally 4. | |||
* Outputs: Left, Right, place | |||
* Fitness function: +10 if hits, -5 if misses. | |||
https://towardsdatascience.com/neuro-evolution-on-steroids-82bd14ddc2f6 | |||
=== Soft Actor-Critic Algorithm === | === Soft Actor-Critic Algorithm === | ||
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https://github.com/trackmania-rl/tmrl | https://github.com/trackmania-rl/tmrl | ||
* Soft Actor-Critic: a beginner-friendly introduction https://www.youtube.com/watch?v=LN29DDlHp1U | * Soft Actor-Critic: a beginner-friendly introduction https://www.youtube.com/watch?v=LN29DDlHp1U | ||
Latest revision as of 15:32, 12 May 2023
Introduction
https://race-condition.reaktor.com/play
Input data
- FPV view
- speed?
- best lap time, last lap time?
Output
- throttle
- steering
Theory
Rules
PID algorithm
PID to stay in the blue area.
NEAT algorithm
Input
- Distance to some black; about 15.
A.I. teaches itself to drive in Trackmania: https://www.youtube.com/watch?v=a8Bo2DHrrow
- The neat algorithm: https://neat-python.readthedocs.io/en/latest/neat_overview.html
- Input: Wall distances and speed (shown at t=1.01; 7 or 15 distances)
- 8 inputs (distances and speed) -> 3 outputs (left, right, throttle)
- Fitness function: distance traveled by the car in a given time
- Generation 1: Population of 100.
- Generation n: crossovers of best individuals + random mutations
- Q-learning,
https://www.youtube.com/results?search_query=neat+algorithm+game
- Inputs: The relative position of the ball to the paddle, velocity of the ball. Totally 4.
- Outputs: Left, Right, place
- Fitness function: +10 if hits, -5 if misses.
https://towardsdatascience.com/neuro-evolution-on-steroids-82bd14ddc2f6
Soft Actor-Critic Algorithm
https://github.com/trackmania-rl/tmrl
- Soft Actor-Critic: a beginner-friendly introduction https://www.youtube.com/watch?v=LN29DDlHp1U
