By Max Lungarella, Fumiya Iida, Josh Bongard, Rolf Pfeifer
This Festschrift quantity, released in occasion of the fiftieth Anniversary of man-made Intelligence, comprises 34 refereed papers written by means of major researchers within the box of synthetic Intelligence. The papers have been rigorously chosen from the invited lectures given on the fiftieth Anniversary Summit of AI, held on the Centro Stefano Franscini, Monte Verità, Ascona, Switzerland, July 9-14, 2006.
The summit supplied a venue for discussions on old, company, political and academic views of AI; clinical trade at the state-of-the-art; speculations concerning the destiny; contributions through researchers from assorted yet comparable components; shows of the most recent learn by way of best scientists within the box; in addition to many casual discussions one of the members and viewers. the chosen papers replicate the breadth of the subjects provided and mentioned on the summit, masking topics starting from the background and clients of AI, to speech acceptance and processing, linguistics, bionics, and consciousness.
The papers are equipped in topical sections on old and Philosophical matters; details conception and Quantification; Morphology and Dynamics; Neurorobotics; computer Intelligence, Cognition, and average Language Processing; Human-Like Intelligence: Motivation, feelings, and recognition; robotic systems; and paintings and AI.
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Additional info for 50 Years of Artificial Intelligence 4850
In the 1960s and 1970s Ray Solomonoff combined theoretical CS and probability theory to establish a general theory of universal inductive inference and predictive AI  closely related to the concept of Kolmogorov complexity . His theoretically optimal predictors and their Bayesian learning algorithms only assume that the observable reactions of the environment in response to certain action sequences are sampled from an unknown probability distribution contained in a set M of all enumerable distributions.
However there are strong indications that new generations of parallel computers are going to become available soon. They will make experiments possible that are too slow today or can only be done by a very limited number of people. If we want to exploit the promise of massively parallel computing, we will need to come up with novel computing paradigms, exploiting metaphors from biology or chemistry rather than from logic and mathematics. Research in membrane computing, molecular computing, amorphous computing, etc.
We will mostly restrict ourselves to trivial predictions like those above and refrain from too much speculation in form of nontrivial ones. However, we may have a look at previous unexpected scientific breakthroughs and try to discern a pattern, a pattern that may not allow us to precisely predict the details of the next revolution but at least its timing. 38 J. 1 A Pattern in the History of Revolutions? Let us put the AI-oriented developments  discussed above in a broader context, and look at the history of major scientific revolutions and essential historic developments (that is, the subjects of the major chapters in history books) since the beginnings of modern man over 40,000 years ago [30, 31].
50 Years of Artificial Intelligence 4850 by Max Lungarella, Fumiya Iida, Josh Bongard, Rolf Pfeifer