AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Por um escritor misterioso
Last updated 14 abril 2025

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.

A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment

Explainable artificial intelligence: an analytical review - Angelov - 2021 - WIREs Data Mining and Knowledge Discovery - Wiley Online Library

PDF] Proving Theorems using Incremental Learning and Hindsight Experience Replay

A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment

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PDF] Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Petar Veličković on LinkedIn: #icml2023
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