Auto Topic: possession
auto_possession | topic
Coverage Score
1
Mentioned Chunks
7
Mentioned Docs
1
Required Dimensions
definitionpros_cons
Covered Dimensions
definitionpros_cons
Keywords
possession
Relations
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Evidence Chunks
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textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.59 | 3 | ... l, and shooting; each of these can be broken down further into lower-level motor behaviors. Obviously, there are multiple ways of obtaining possession and shooting, multiple Section 23.4 Generalization in Reinforcement Learning 859 teammates one could pass to, and so on, so each ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... ethods described Hierarchical reinforcement learning in Chapter 11. For example, scoring a goal in soccer can be broken down into obtaining possession, passing to a teammate, receiving the ball from a team-mate, dribbling toward the goal, and shooting; each of these can be broken ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... e to a desired terminal state. For example,Φ for the soccer- playing robot could add a constant bonus for states where the robot’s team has possession and another bonus for reducing the distance of the ball from the opponents’ goal. This will result in faster learning overall, bu ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... hoice of what to do at the top level depends mainly on whether the player has the ball or not: while not IS-T ERMINAL (s) do if BALL -IN-MY-POSSESSION (s) then choose({PASS, HOLD, DRIBBLE }) else choose({STAY, MOVE, INTERCEPT -BALL }). Each of these choices invokes a subroutine t ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... , if not impossible, to write down the rules for determining the speed and direction of the kick to maximize the probability of maintaining possession. Similarly, it is far from obvious how to choose the right teammate to receive the ball or where to move in order to make oneself ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... e method for learning complex behaviors. In keep- away, an HRL agent based on the partial program sketched above learns a policy that keeps possession forever against the standard taker policy—a significant improvement on the pre- vious record of about 10 seconds. One important ch ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... total reward during MOVE-I NTO -SPACE. The former depends only on whether the ball gets to Ali with enough time and space for Ali to retain possession, and the latter depends only on whether the agent reaches a good location to receive the ball. In other words, the overall utilit ... |