[Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search
jasiek at snafu.de
Wed Jan 27 22:42:29 PST 2016
Congratulations to the researchers!
On 27.01.2016 21:10, Michael Markefka wrote:
> I really do hope that this also turns into a good analysis and
> teaching tool for human player. That would be a fantastic benefit from
> this advancement in computer Go.
The programs successful as computer players mostly rely on computation
power for learning and decision-making. This can be used for teaching
tools that do not need to provide text explanations and other reasoning
to the human pupils: computer game opponent, life and death playing
opponent, empirical winning percentages of patterns etc.
Currently such programs do not provide sophisticated explanations and
reasoning about tactical decision-making, strategy and positional
judgement fitting human players' / pupils' conceptual thinking.
If always correct teaching is not the aim (but if a computer teacher may
err as much as a human teacher errs), in principle it should be possible
to combine the successful means of using computation power with the
reasonably accurate human descriptions of sophisticated explanations and
reasoning. This requires implementation of expert system knowledge
adapted from the best (the least ambiguous, the most often correct /
applicable) descriptions of human-understandable go theory and further
research in the latter.
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