AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Por um escritor misterioso
Last updated 22 fevereiro 2025
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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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A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment
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Explainable artificial intelligence: an analytical review - Angelov - 2021 - WIREs Data Mining and Knowledge Discovery - Wiley Online Library
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PDF] Proving Theorems using Incremental Learning and Hindsight Experience Replay
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A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment
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ASoT] Natural abstractions and AlphaZero — AI Alignment Forum
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AI-Local search&Nodeterministic Problems&Partial observations&Online search - 丹尼尔奥利瓦- 博客园
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State of AI Report: Compute Index V2 update!
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AI high: The island of Anguilla is riding the AI wave
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Aman Madaan (@aman_madaan) / X
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Tabu Search Algorithm - an overview
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Nearly 100 Mila-affiliated scientific papers accepted at NeurIPS 2023 - Mila
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PDF] Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Petar Veličković on LinkedIn: #icml2023
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