feat(*): Update rewards and terminal conditions after 528 million timesteps

This commit is contained in:
Josh Creek
2023-10-10 19:46:23 +01:00
parent f5657ec565
commit a427c1f58d
2 changed files with 20 additions and 2 deletions
+18
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@@ -37,6 +37,8 @@ This bot is configured to be able to play any Rocket League game mode. The plan
Learn the basic mechanics as fast as possible. To do this I'm using 3v3, so that there are 6 agents training for each instance of the game. This will make the logs noisier, but should give the bot more exposure to the basics of the game.
#### 0 steps
Reward functions at this point are as below, along with their scale:
- VelocityPlayerToBallReward - 0.1
@@ -64,6 +66,8 @@ Terminal conditions for the first 265million steps:
- NoTouchTimeoutCondition(fps * 10)
- GoalScoredCondition()
#### ~250 million steps
After 265 million steps I changed the terminal conditions and reward weightings.
- TimeoutCondition -> fps * 300
@@ -74,6 +78,20 @@ After 265 million steps I changed the terminal conditions and reward weightings.
This is to try to get the bot to gain experience in other areas of the game now it has vaguely got the hang of what a kickoff is.
#### ~500 million steps
After 528 million steps I changed things again, switching to 1v1 instead of 3v3, and changing the rewards as below:
- VelocityBallToGoalReward -> 10
- EventReward -> 10
- RewardIfClosestToBall -> 1
- LiuDistancePlayerToBallReward -> 1
- AlignBallGoal -> 20
#### ~1 billion steps
The bot should now have acceptable mechanics and a vague understanding of 1v1 strategies.
### Stage 2
Learn the strategies for playing each game mode. To do this I will make the bot train in each game mode in series, or possibly in parallel if I can configure it to run different game modes in different instances of Rocket League.