By Max Lungarella, Fumiya Iida, Josh Bongard, Rolf Pfeifer
This Festschrift quantity, released in social gathering of the fiftieth Anniversary of synthetic Intelligence, comprises 34 refereed papers written via top researchers within the box of man-made 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 historic, enterprise, political and academic views of AI; clinical alternate at the cutting-edge; speculations concerning the destiny; contributions by way of researchers from various yet comparable parts; displays of the newest learn by way of most sensible scientists within the box; in addition to many casual discussions one of the individuals and viewers. the chosen papers replicate the breadth of the themes provided and mentioned on the summit, masking topics starting from the heritage and customers of AI, to speech reputation and processing, linguistics, bionics, and consciousness.
The papers are prepared in topical sections on old and Philosophical matters; info concept and Quantification; Morphology and Dynamics; Neurorobotics; computer Intelligence, Cognition, and normal Language Processing; Human-Like Intelligence: Motivation, feelings, and realization; robotic systems; and artwork and AI.
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Extra info for 50 Years of Artificial Intelligence 4850
From this point of view, ontologies and language are seen as complex adaptive systems in constant flux. Language nor the meanings expressed by language are based on a static set of conventions that can be induced statistically from language data. Today this viewpoint is being explored under the label of semiotic dynamics (Steels, 2006). Semiotic dynamics studies how ontologies and symbol systems may emerge in a group of agents and by what mechanisms they may continue to evolve and complexify. The study of semiotic dynamics uses similar tools and techniques as other research in the social sciences concerned with opinion dynamics, collective economical decision making, etc.
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]. Amazingly, they seem to match a binary logarithmic scale marking exponentially declining temporal intervals , each half the size of the previous one, and measurable in terms of powers of 2 multiplied by a human lifetime (roughly 80 years—throughout recorded history many individuals have reached this age, although the average lifetime often was shorter, mostly due to high children mortality).
For several reasons, however, the first RNNs could not learn to look far back into the past. This problem was overcome by RNNs of the Long Short-Term Memory type (LSTM), currently the most powerful and practical supervised RNN architecture for many applications, trainable either by gradient descent  or evolutionary methods , occasionally profiting from a marriage with probabilistic approaches . Unsupervised RNNs that learn without a teacher to control physical processes or robots frequently use evolutionary algorithms [10, 22] to learn appropriate programs (RNN weight matrices) through trial and error .
50 Years of Artificial Intelligence 4850 by Max Lungarella, Fumiya Iida, Josh Bongard, Rolf Pfeifer