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文件名称：Machine Learning. A Constraint-based Approach
文件大小：4.19MB
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更新时间：2021-08-19 16:44:46
机器学习
Machine Learning projects our ultimate desire to understand the essence of human intelligence
onto the space of technology. As such, while it cannot be fully understood
in the restricted field of computer science, it is not necessarily the search of clever
emulations of human cognition. While digging into the secrets of neuroscience might
stimulate refreshing ideas on computational processes behind intelligence, most of
nowadays advances in machine learning rely on models mostly rooted in mathematics
and on corresponding computer implementation. Notwithstanding brain science
will likely continue the path towards the intriguing connections with artificial computational
schemes, one might reasonably conjecture that the basis for the emergence of
cognition should not necessarily be searched in the astonishing complexity of biological
solutions, but mostly in higher level computational laws. Machine learning
and
information-based
laws of cognition.
The biological solutions
for supporting different forms of cognition are in fact cryptically interwound with
the parallel need of supporting other fundamental life functions, like metabolism,
growth, body weight regulation, and stress response. However, most human-like intelligent
processes might emerge regardless of this complex environment. One might
reasonably suspect that those processes be the outcome of information-based laws
of cognition, that hold regardless of biology. There is clear evidence of such an invariance
in specific cognitive tasks, but the challenge of artificial intelligence is daily
enriching the range of those tasks.While no one is surprised anymore to see the computer
power in math and logic operations, the layman is not very well aware of the
outcome of challenges on games, yet. They are in fact commonly regarded as a distinctive
sign of intelligence, and it is striking to realize that games are already mostly
dominated by computer programs! Sam Loyd’s 15 puzzle and the Rubik’s cube are
nice examples of successes of computer programs in classic puzzles. Chess, and more
recently, Go clearly indicate that machines undermines the long last reign of human
intelligence. However, many cognitive skills in language, vision, and motor control,
that likely rely strongly on learning, are still very hard to achieve.