Title :
Biology: see it again-for the first time
Author :
Luke, Sean ; Hamahashi, Shugo ; Kyoda, Koji ; Ueda, Hiroki
Author_Institution :
Comput. Sci. Lab., Sony Corp., Tokyo, Japan
Abstract :
Computer science owes a huge debt to biological systems. The field came about largely as an attempt to understand and replicate the function and abilities of the brain. From this early lineage have sprung many subfields derived largely from biological metaphors: computer vision, neural networks, evolutionary computation, robotics, multiagent studies, and much of artificial intelligence. In some areas, the computer has bested its biological counterparts in efficiency and simplicity. But for many domains the biological “real thing” remains superior to the artificial algorithms that it inspired. While computer science has been simplifying its inspirations from biology, biologists have been catching up. Soon it will be possible to model entire neurosystems, gene-regulation mechanisms, evolutionary processes and even whole organisms on a computer. Given how much biological metaphors have inspired AI and computer science, biology can help reinvigorate many other AI subfields. Moreover, modeling and analysis promise to enable many things that have long been pipe dreams of autonomous robotics, artificial life, and cognitive science
Keywords :
artificial intelligence; biology computing; computer science; artificial intelligence; artificial life; biological metaphors; biological systems; biology; brain; cognitive science; computer science; computer vision; evolutionary computation; evolutionary processes; gene-regulation mechanisms; multiagent studies; neural networks; neurosystems; robotics; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological system modeling; Biological systems; Biology computing; Computer science; Computer vision; Evolution (biology); Evolutionary computation;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.722341