Epstein Secrets

ges 51 Our goal in this chapter Ls to provide practical techniques for approximating the ideal pro- vided by algorithmic probability, based on what Pei Wang has termed the assumption of in- sufficient knowledge and resources tWan061, and assuming an AGI architecture that's at least vaguely humanlike in n

l Ant Problem 224 33.3.5 Discussion 229 33.3.6 Conclusion 229 33.4 Integrating Feature Selection Into the Learning Process 230 33.4.1 Machine Learning, Feature Selection and AGI 231 33.4.2 Data- and Feature- Focusable Learning Problems 232 33.4.3 Integrating Feature Selection Into Learning 233

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