Reinforcement Learning for RoboCup Soccer Keepaway

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How researchers see this paper

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Cognitive Radio Architecture Evolution (2009, methodology): “Early planning systems used rule bases to solve simple planning problems like the monkey and the bananas [38], stimulating the development of an entire subculture of planning technologies now integrated into a broad range of applications from factory automation to autonomous vehicles [39] and RoboCu”
Reinforcement learning in the robocup-soccer keepaway (2007, methodology): “In detail, this paper compares simulation results of Qlearning and Sarsa agents in the Keepaway domain [5].”
Transfer Learning via Inter-Task Mappings for Temporal Difference Learning (2007, methodology): “%) in all experiments and λ was set to 0, which we selected to be consistent with past work (Stone et al., 2005).”
Game-independent AI agents for playing Atari 2600 console games (2010, background): “Examples of the applications of Sarsa(λ) include RoboCup soccer keepaway [Stone et al., 2005], control of an all-terrain robot [Luders, 2007], and learning in 3D shooter games [McPartland and Gallagher, 2008].”
Adaptive Tile Coding for Value Function Approximation (2007, methodology): “We contribute an adaptive method for tile coding (Albus 1981), a simple, computationally efficient function approximator that has enjoyed broad empirical success (Sutton 1996; Stone, Sutton, K Stone, Sutton, & Kuhlmann 2005 ).”