Deriving strategies from perfect play

Deriving strategies from perfect play

A number of games have been solved: Checkers, Nine-men’s morris,
Connect-Four, Go-Moku, Awari. This means that perfect play in these
games is available. Some of these games have been solved with a
knowledge based approach. Some with a brute-force approach. Now the
question is what this means for human
play: can we learn form these perfect lines of play. Can a
knowledge-based approach be found by mining the brute force data? Is it possible to
summarize easy to remember rules of thumb? Is it possible to summarize
or generalize concepts form these perfect strategies? This topic
involves artificial intelligence, machine learning, concept learning,
generalization, and, in a sense learn the ultimate compression method
for (some of) these games.

LIACS intern

Student Profile

Time frame

Scientific Challenge
Machine learning of game playing concepts

Walter Kosters
Jan van Rijn
Aske Plaat


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