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Nov 7, 2023 at 13:27 comment added Neil Slater @rafiqollective The environment does not sound too complex for RL, but you may want to rethink features or training routine to address your collision issue. And if possible do try to assess what the correct behaviour is, by e.g. playing the game yourself - that will give you more clues on what the agent should know and react to in order to succeed.
Nov 7, 2023 at 13:15 comment added rafiqollective Yes you get the environment very well. When you say it like that I'm afraid the environment may be too complicated for the agent to solve. I try feature engineering as you suggested and change reward function. I hope it works. @NeilSlater
Nov 7, 2023 at 13:02 comment added Neil Slater @rafiqollective: My understanding of the environment is that the implementation is like a game with physics engine. And the car cannot change its speed, only steer. So depending on what physics applies to steering, and how the collision detection is done, it is possible to have a problem with this environment where your goal is not realisable, or very hard (e.g. perhaps collision detection is tooo wide, or in practice the agent's car has to steer into alternative lane a long way ahead of other car, and has to predict what lane the other car is in from cartesian co-ordinates)
Nov 7, 2023 at 12:57 history edited Neil Slater CC BY-SA 4.0
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Nov 7, 2023 at 12:56 comment added rafiqollective Thanks for sharing your opinions with me. I see what you mean. Environment actually has two lanes so avoiding is not difficult. I will try what you suggested. Thank you a lot.
Nov 7, 2023 at 12:54 history edited Neil Slater CC BY-SA 4.0
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Nov 7, 2023 at 12:44 history edited Neil Slater CC BY-SA 4.0
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Nov 7, 2023 at 12:19 history answered Neil Slater CC BY-SA 4.0