AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

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.

AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

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

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Petar Veličković on LinkedIn: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

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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

TransformerCVAE/data/arxiv/artificial intelligence_10047_15000_15_title.txt at master · fangleai/TransformerCVAE · GitHub

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Immunity-based Ebola optimization search algorithm for minimization of feature extraction with reduction in digital mammography using CNN models

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

Comparison of Taboo Search Methods for Atomic Cluster Global Optimization with a Basin-Hopping Algorithm

Petar Veličković - CatalyzeX