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This class is a base class for all the models an agent can have about the world. A subclass should implement a specific model of the world, and a specific way to process percepts for this model. There can be multiple ways to process percepts for any given model, so an example class hierarchy could be: ------------------- | AgentWorldModel | ------------------- / ---------- ---------- | Model1 | | Model2 | ---------- ---------- / \ \ ------------------- ------------------ . |with method 1 to | |with method 2 to| . |processPercepts | |processPercepts | . |for Model1 | |for Model1 | ------------------- ------------------
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A list of ShipExternalState |
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A list of ShipExternalState |
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ShipExternalState |
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numpy array (vector) |
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numpy array (vector) |
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Obstacles |
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Every world model contains a queue for incoming messages. Note that outgoing msgs are inside strategy. TODO: does this design need change? |
For a given concrete model, this method implements a specific method of updating this model from percepts. This is just an extra layer of flexibility, in case there are multiple methods to update percepts for the same model.
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Get a list of estimated ShipExternalState of all other ships in the system.
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Get a list of estimated ShipExternalState of all other ships indexed by shipIndices.
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Get the estimated ShipExternalState as estimated by the world model.
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Get the estimated wind vector in the location of the ship.
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Get the estimated water vector in the location of the ship.
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Get a list of estimated obstacle shapes.
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