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Scenario We are on the way to setting foot on Mars. To do so , we need to refuel our space capsule in a space
Scenario
We are on the way to setting foot on Mars. To do so we need to refuel our space capsule in a space station thousands of miles away from Earth.
We need to perform a docking operation similarly as shown in this video.
Goal
Build a reinforcement learning model to perfom the docking operation autonomously while respecting safety and time constraints.
Time constraint
The docking operation must be done in minutes s
Safety constraint
For the docking operation to be performed safely, the space capsule needs to be aligned cm from the docking center of the space station.
Actions
You only have actions: go left, do nothing, go right.
Observations
Space capsule alignment with the space station. It is assumed the alignment can range from m to m where m means perfect alignment. We also assume that negative values describe a misalignment to the left and positive values represent a misalignment to the right.
Tasks
Create a new py file called SpaceCapsuleEnvironment.py and build a model that keeps the space capsule in the safety range for as long as possible using SARSA algorithm.
points Create a SpaceEnv class with the following function
pointsinitself an initilization function that defines the initial values for the environment.
points stepself action a step function that provides the next observation state of the system, a reward, and stopping criteria done given an action.
points resetself a function to reset the values of the environment after each epsiode.
points Discretize the alignment range in evenly spaced numbers over the interval cm and cm You should use the function nplinspace. Also, update the function getStateobservation
points Run SARSA algorithm with the SpaceEnv you've just created. You should save the plot containing the results.
points Change the learning rate parameter ALPHA to and then to and discuss your findings.
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