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The Alberta Plan for AI Research

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arxiv 2208.11173 v3 pith:4YYDWJX4 submitted 2022-08-23 cs.AI cs.LG

Richard S. Sutton , Michael Bowling , Patrick M. Pilarski This is my paper
classification cs.AIcs.LG
keywords albertaplanresearchapproachartificialcalldescribegroups
verification ladder T0 review T1 audit T2 compute T3 formal
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Herein we describe our approach to artificial intelligence research, which we call the Alberta Plan. The Alberta Plan is pursued within our research groups in Alberta and by others who are like minded throughout the world. We welcome all who would join us in this pursuit.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

    cs.LG 2025-06 conditional novelty 6.0 of 10

    A gradient-similarity tree of LoRA adapters, searched by an LCB bandit algorithm, delivers state-of-the-art continual learning accuracy with up to 3.2x faster training on ViTs and 2.4x on LLMs.

  2. The Possibility of Artificial Intelligence Becoming a Subject and the Alignment Problem

    cs.AI 2026-04 unverdicted novelty 4.0 of 10

    Dominant control-based AI alignment falls short for potential AGI subjects; a parenting model drawing on Turing's child machines should foster gradual autonomy and cooperative coexistence.

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