Epstein Secrets

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

ledge and intuition regarding CogPrime. For example, beyond the ideas presented here, there is a body of work on the OpenCog wiki site, and then the OpenCog codebase itself. More extensive introductory remarks may be found in Preface of Part 1, including a brief history of the book and acknowledgements

sign. No doubt it will evolve in some respects as implementation progresses; one of the principles kept in mind during the design and development of OpenCog was modular- ity, enabling substantial modifications to particular parts of the framework to occur without requiring wholesale changes throughout th

ique that does feature selection repeatedly during the MOSES learning process, rather than just doing it initially prior to MOSES learning. 33.4.1 Machine Learning, Feature Selection and AGI The relation between feature selection and machine learning appears an excellent example of the way that, even when the

N nodes are activated and exported to the OpenCog Atomspace • Recognition that a block is present is carried out, either by - PLN inference within OpenCog, drawing the conclusion that a block is present from the exported predicates, using ImplicationLinks comprising a working definition of a "block"

ning to bridge DeSTIN and PLN Ls intended to fit. This architecture is not yet fully implemented, but is a straightforward extension of the current OpenCog architecture for processing data from game worlds IGEA08], and is scheduled for implementation later in 2013 in the course of a funded project invo

lvin. The Cerebral Code. MIT Press, 1996. Car85. S. Carey. Conceptual Change in Childhood. MIT Press, 1985. Car97. R Caruana. Multitask learning. Machine Learning, 1997. Cas85. R. Case. Intellectual development: Birth to adulthood. Academic Press, 1985. Cas04. N. L. Cassimatis. Grammatical processing using

zed Terms • Abduction: A general form of inference that goes from data describing something to a hypothesis that accounts for the data. Often in an OpenCog context, this refers to the PLN abduction rule, a specific First-Order PLN rule (If A implies C, and B implies C, then maybe A is B), which embodie

bility. EFTA00624100 Appendix A Glossary A.1 List of Specialized Acronyms This includes acronyms that are commonly used in discussing CogPrime, OpenCog and related ideas, plus sonic that occur here and there in the text for relatively ephemeral reasons. • AA: Attention Allocation • ADF: Automatica

2006. William Calvin. The Cerebral Code. MIT Press, 1996. S. Carey. Conceptual Change in Childhood. MIT Press, 1985. R Caruana. Multitask learning. Machine Learning, 1997. R. Case. Intellectual development: Birth to adulthood. Academic Press, 1985. N. L. Cassimatis. Grammatical processing using the mechanisms o

HOUSE_OVERSIGHT_013240 Appendix A Glossary A.1 List of Specialized Acronyms This includes acronyms that are commonly used in discussing CogPrime, OpenCog and related ideas, plus some that occur here and there in the text for relatively ephemeral reasons. AA: Attention Allocation ADF: Automatically De

alized Terms Abduction: A general form of inference that goes from data describing something to a hypothesis that accounts for the data. Often in an OpenCog context, this refers to the PLN abduction rule, a specific First-Order PLN rule (If A implies C, and B implies C, then maybe A is B), which embodies