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added first Independent Q Learning experiment #922
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added first Independent Q Learning experiment #922
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| Codecov ReportAttention: Patch coverage is  
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##            main    #922      +/-   ##
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- Coverage   0.02%   0.00%   -0.03%     
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- Hits           2       0       -2     
- Misses      7620    7631      +11     
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                src/ReinforcementLearningExperiments/src/experiments/MARL/IDQN_TicTacToe.jl
          
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      | @HenriDeh, @jeremiahpslewis would you have a look? It is supposed to just be an example on how to use  | 
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I don't see a problem with the implementation but it needs to be added to the tests of RLExperiments like the other ones are. Otherwise we may not see that a change breaks this example and it will live there broken until someone notices.
| 
 I this what you intended to say here @HenriDeh ? Commit 82f77f4 | 
adjusted tests and merged main
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    | FYI: rebased commit structure as it was messed up. | 
adjusted tests and merged main
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Yes thank you. Gotta figure out why the CI fails now.
adjusted tests and merged main
| Finally, the pipeline should be correct. I needed to add some parts, but this is also helpful for other 3rd party environments once they need to be tested. | 
| 
 this should be solved now @HenriDeh ? | 
| Hi @Mytolo, sorry for the delay, I was on vacations. You have conflicts to resolve then I can approve the PR for merging :) | 
PR Checklist
Here is an experiment for RLExperiments showing how to set up a simple independent learning with two players. (In the example, the roles of randomly choosing an action and taking create_policy -> DQN can be changed and they can also both try to approximate their Q values for action selection)