By Gilles Brassard (auth.), Jan van Leeuwen (eds.)
ISBN-10: 3540601058
ISBN-13: 9783540601050
This particularly commissioned quantity provides a distinct number of expository papers on significant subject matters which are consultant for laptop technological know-how at the present time. The 38 contributions, written via across the world major specialists within the computing device technological know-how sector on own invitation, exhibit the scope and stature of the sector this present day and provides an effect of the manager motivations and demanding situations for tomorrow's desktop technological know-how and knowledge technology.
This anthology marks a really outstanding and festive second: it's the a thousandth quantity released within the Lecture Notes in laptop technological know-how sequence. It addresses all laptop scientists and anyone attracted to a consultant assessment of the field.
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Extra resources for Computer Science Today: Recent Trends and Developments
Example text
3 Origins of Behavioral Complexity Against this background, the key problem in autonomous agents research, namely how robotic agents may develop their own behavioral repertoire, has been attacked in a number of different ways. We summarise work on four different approaches which have all been strongly inspired by biological mechanisms. These Artificial Life and Real World Computing 19 Fig. 1. Overview of a robotic ecosystem built at the VUB AI laboratory in Brussels. The robots can recharge themselves by going to a charging station.
After a while it has in fact slowed down so much that it is able to halt inside the charging station and thus get a guaranteed supply of energy. g O ~ O ~ O 4 0 3 O ~ O Fig. 3. The top graph plots the energy level the bottom graph the forward speed of a robot. There is a regular cycle with two activities: recharging and seeking the charging station. A new bene is added after 100 time steps. The robot now slows down while moving in the charging station and thus ensures itself after some cycles of eternal life.
The networks are thus of great use as automatic learning tools and as adaptive and optimal controllers. Much effort has been directed towards practical applications, including, for example, those for explosion detection in airport security, signature verification, and financial and medical time-series prediction [24, 39, 38]). The networks also are popular in applications to vision, speech processing, robotics, signal processing, and many other fields (see [12],[35],[21],[28]). Some applications have been very successful; others have been less so.
Computer Science Today: Recent Trends and Developments by Gilles Brassard (auth.), Jan van Leeuwen (eds.)
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