AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
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This paper studies the problem of finding graphs that maximize the number of edges, while avoiding short cycles. It formulates graph generation as a reinforcement learning task, and compares methods like AlphaZero and tabu search. A key finding is that using a curriculum - building larger graphs from good smaller graphs - significantly improves performance. The work makes progress on an open problem in extremal graph theory.
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Aman Madaan (@aman_madaan) / X
Anian Ruoss (@anianruoss) / X
Juan (@jeandut14000) / X
Petar Veličković posted on LinkedIn
AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
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