July 2018
Intermediate to advanced
254 pages
8h 12m
English
Content preview from Hands-On Intelligent Agents with OpenAI Gym
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observation_spec()
This method is similar to env.observation_space(), which we used with the Gym environments. This method returns a list specifying all the available observations supported by the DM Lab environment. It also includes specifications about level-dependent custom observations.
The specifications contain the name, type, and shape of the tensor or string that will be returned if that specification name is specified in the observation list (such as the 'RGBD' example previously). For example, the following code snippet lists two items in the list that will be returned to give you an idea about what the specs contain:
{ 'dtype': <type'numpy.uint8'>, ## Array data type'name': 'RGBD', ## Name of observation.'shape': (4, 180, 320 ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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