Function Approximation |   |   | Partial Observability |   |   | Learning Methods |   |   | Ensembles |   |   |
Stochastic Optimisation |   |   | General RL |   |   | General ML |   |   | Multiagent Learning |   |   |
Comparison/Integration |   |   | Bandits |   |   | Applications |   |   | Robot Soccer |   |   |
Humanoids |   |   | Parameter |   |   | MDP |   |   | Empirical |   |   |
Failure Warning |   |   | Representation |   |   | General AI |   |   | Neural Networks |   |   |
All |   |   |
Artificial Intelligence: An Empirical Science
Herbert A. Simon, 1995
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Benchmarks, Test Beds, Controlled Experimentation, and the Design of Agent Architectures
Steve Hanks, Martha E. Pollack, and Paul R. Cohen, 1993
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Machine Learning as an Experimental Science
Pat Langley, 1988
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The Future of Data Analysis
John W. Tukey, 1962
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