June 2018
Intermediate to advanced
318 pages
9h 24m
English
Content preview from Hands-On Reinforcement Learning with Python
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Imagination augmented agents
Are you a fan of the game chess? If I asked you to play chess, how would you play the game? Before moving any pieces on the chessboard, you might imagine the consequences of moving any piece and move the piece you think would help you to win. So, basically, before taking any action, you imagine the consequence and, if it is favorable, you proceed with that action, or else you refrain from performing that action.
Similarly, imagination augmented agents are augmented with imagination; before taking any action in an environment they imagine the consequences of taking the action and, if they think the action will provide a good reward, they will perform the action. They also imagine the consequences of taking a different ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.