Mainstream artificial intelligence has been very successful at designing algorithms
And devices that solve problems that most humans are not very
Good at, such as playing chess, controlling aircraft dynamics, or finding the
Three-dimensional structure of proteins. But, in doing so, it ended up neglecting
Fundamental aspects of biological intelligence, such as physical embodiment,
Behavioral autonomy, self-healing, social interaction, evolution and
Learning, that make biological organisms prone to errors and sometimes difficult
To predict, but also so successful to survive in unknown and changing
Environments.
The mid-1980s witnessed a renaissance of diverse approaches to the understanding
And engineering of intelligent systems. A range of newly born
Fields, such as embodied cognitive science, neuromorphic engineering, artificial
Life, behavior-based robotics, evolutionary robotics, and swarm intelligence,
To mention only a few, questioned the validity of the assumptions and
Methods of mainstream artificial intelligence for creating artifacts that could
Approximate the operational characteristics and performance of biological
Intelligence.
The new artificial intelligence, as it is sometimes called, that emerged at the
Turn of the millennium expanded its focus of attention from human brains
And cognitive reasoning to a wider range of organisms, processes, and phenomena that occur at multiple spatial and temporal scales. This change
Reflected not only a philosophical revolution where humans are no longer
At the center of the biological universe, but also a technological revolution
Where desktop computers are dissolving into a swarm of virtual and physical
Artifacts (Internet agents, virtual personae, personal digital assistants, communication
Devices, mobile robots, intelligent prostheses, etc.) in need of
Real-time and embedded intelligence, autonomous behavior, self-adaptation,
And social awareness to interact, merge, and substitute with us.
(1 votes, average: 5.00 out of 5)