Implement a passive learning agent in a simple environment, such as the 4 x 3 world. For the case of an initially unknown environment model, compare the learning performance of the direct utility estimation, TD, and ADP algorithms. Do the comparison for the optimal policy and for several random policies. For which do the utility estimates converge faster! What happens when the size of the environment is increased? (Try environments with and without obstacles.)

Database System Concepts
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ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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Implement a passive learning agent in a simple environment, such as the 4 x 3 world.
For the case of an initially unknown environment model, compare the learning performance
of the direct utility estimation, TD, and ADP algorithms. Do the comparison for the optimal
policy and for several random policies. For which do the utility estimates converge faster!
What happens when the size of the environment is increased? (Try environments with and
without obstacles.)
Transcribed Image Text:Implement a passive learning agent in a simple environment, such as the 4 x 3 world. For the case of an initially unknown environment model, compare the learning performance of the direct utility estimation, TD, and ADP algorithms. Do the comparison for the optimal policy and for several random policies. For which do the utility estimates converge faster! What happens when the size of the environment is increased? (Try environments with and without obstacles.)
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