Categorization + Parallelization + Code cleaning #5
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avv-va
commented
Jun 14, 2024
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avv-va
commented
- Introduce the concept of TeamType and AgentPerformance for training/evaluating the primary agent with agents with certain level of performance
- Enable parallelization for generating the FCP agent population
- Clean the code
avv-va
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Ttopiac
reviewed
Jun 26, 2024
scripts/run_overcooked_game.py
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| tm1 = load_agent(Path('/home/ava/Research/Codes/MHRI/multiHRI/agent_models/sp_det'), args) | ||
| tm2 = load_agent(Path('/home/ava/Research/Codes/MHRI/multiHRI/agent_models/sp_det'), args) | ||
| tm1 = load_agent(Path('/home/ava/Desktop/sp_det'), args) | ||
| tm2 = load_agent(Path('/home/ava/Desktop/sp_det'), args) |
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Could we store our trained agent in a specific folder under multiHRI?
(It will make our experience working on different computer easier.)
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@Ttopiac Yeah, but this is the code for loading the agents not saving them. The code for saving the agents already saves it to multiHRI/agent_models.
If you want to load your agents from the default path you could change the path in here to agent_models/specific_file_path, in here I was testing some stuff which I did not wanted to put in the agent_models folder, that's why it's using an absolute path.
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