Major environment refactoring (base version) #169
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| demand_distribution: Union[ | ||
| int, float, type, Callable | ||
| ] = Uniform, | ||
| vehicle_capacity: float = 1.0, |
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I think vehicle_capacity and capacity should be the same parameter, is it right?
EDIT: my bad - capacity is actually the "maximum capacity" to normalize
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Yes, maybe later we want to rename the capacity. I think now this may be confusing to some users.
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Ok, let's leave it as simple as possible for now
| log = get_pylogger(__name__) | ||
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| class MPDPEnv(RL4COEnvBase): | ||
| """Multi-agent Pickup and Delivery Problem environment. | ||
| """Multi-agent Pickup and Delivery Problem (mPDP) environment. |
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Note that actually this should be called "mPDTSP", but I guess we can leave it like that for now
| self.depot_sampler = get_sampler("depot", depot_distribution, min_loc, max_loc, **kwargs) | ||
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| # Prize distribution | ||
| self.deterministic_prize_sampler = get_sampler("deterministric_prize", "uniform", 0.0, 4.0/self.num_loc, **kwargs) |
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This one cannot be changed via kwargs, right?
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Yes, since there is a specific rule for the value range of the deterministic_prize and also the following stochastic_prize. Here I hardcode the distribution to Uniform.
Description
Please refer to the full environment refactor PR: #166.
Motivation and Context
Please refer to the full environment refactor PR: #166.
Types of changes
Compare with the full environment refactor, this base refactor only touches:
And as a base refactor, this PR keeps:
Overall, this base version PR only works on moving code and doesn't change the logic for consequence. In the future version, we will refactor environments with the guide of the full refactor version step by step.
For more details, please refer to the full environment refactor PR: #166.
Checklist