By Dr. Ben Goertzel

ISBN-10: 354023733X

ISBN-13: 9783540237334

This is often the 1st e-book on present learn on man made basic intelligence (AGI), paintings explicitly interested by engineering normal intelligence - self reliant, self-reflective, self-improving, commonsensical intelligence. each one writer explains a selected element of AGI intimately in each one bankruptcy, whereas additionally investigating the typical issues within the paintings of various teams, and posing the massive, open questions during this very important zone. This ebook might be of curiosity to researchers and scholars who require a coherent therapy of AGI and the relationships among AI and similar fields akin to physics, philosophy, neuroscience, linguistics, psychology, biology, sociology, anthropology and engineering.

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Technical Report Tech. Rep. IRIDIA/97-12, Universit´e Libre de Bruxelles, 1997. 10. Haskell Curry and Robert Feys. Combinatory Logic. North-Holland, 1958. Contemporary Approaches to Artificial General Intelligence 29 11. M. Dorigo and L. M. Gambardella. Ant Colonies for the Traveling Salesman Problem. BioSystems, 43:73–81, 1997. 12. M. Dorigo and L. M. Gambardella. Ant Colony Systems: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Trans. Evol. , 1:53–66, 1997. 13. W. Fontana and L.

Addison-Wesley, 1991. 46. Thomas S. Ray. A Proposal to Create a Network-Wide Biodiversity Reserve for Digital Organisms. Technical Report ATR Technical Report TR-H-133, ATR, 1995. 47. Thomas S. Ray and Joseph Hart. Evolution of Differentiated Multi-threaded Digital Organisms. In Artificial Life VI Proceedings. MIT Press, 1998. 48. Juergen Schmidhuber. Bias-Optimal Incremental Problem Solving. In Advances in Neural Information Processing Systems - NIPS 15. MIT Press, 2002. 49. John R. Searle. Minds, Brains, and Programs.

Representing the neural net approach in this book, we have Peter Voss’s paper on the a2i2 architecture. a2i2 is in the vein of other modern work on reinforcement learning, but it is unique in its holistic architecture focused squarely on AGI. Voss uses several different reinforcement and other learning techniques, all acting on a common network of artificial neurons and synapses. The details are original, but are somewhat inspired by prior neural net AI approaches, particularly the “neural gas” approach [41], as well as objectivist epistemology and cognitive psychology.

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Artificial General Intelligence by Dr. Ben Goertzel

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