# The Alberta Plan for AI Research

arXiv: https://arxiv.org/abs/2208.11173 · HTML: https://mlsanity.com/paper/2208.11173/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 44 references that are in the map.
- First posted on arXiv 23 Aug 2022.

## Builds on (most cited first, 10 of 10)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Continual Lifelong Learning with Neural Networks: A Review](https://mlsanity.com/paper/1802.07569/) (2018)
- [Reinforcement Learning with Unsupervised Auxiliary Tasks](https://mlsanity.com/paper/1611.05397/) (2016)
- [Towards Continual Reinforcement Learning: A Review and Perspectives](https://mlsanity.com/paper/2012.13490/) (2020)
- [The Option Keyboard: Combining Skills in Reinforcement Learning](https://mlsanity.com/paper/2106.13105/) (2021)
- [Reward-Respecting Subtasks for Model-Based Reinforcement Learning](https://mlsanity.com/paper/2202.03466/) (2022)
- [The Quest for a Common Model of the Intelligent Decision Maker](https://mlsanity.com/paper/2202.13252/) (2022)
- [Learning Agent State Online with Recurrent Generate-and-Test](https://mlsanity.com/paper/2112.15236/) (2021)
- [The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents](https://mlsanity.com/paper/2203.09498/) (2022)

## Built on by (most cited first, 18 of 18)

- [Harms from Increasingly Agentic Algorithmic Systems](https://mlsanity.com/paper/2302.10329/) (2023)
- [Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning](https://mlsanity.com/paper/2306.03186/) (2023)
- [Sample-Efficient Alignment for LLMs](https://mlsanity.com/paper/2411.01493/) (2024)
- [Rethinking the Foundations for Continual Reinforcement Learning](https://mlsanity.com/paper/2504.08161/) (2025)
- [Locality Sensitive Sparse Encoding for Learning World Models Online](https://mlsanity.com/paper/2401.13034/) (2024)
- [UniZero: Generalized and Efficient Planning with Scalable Latent World Models](https://mlsanity.com/paper/2406.10667/) (2024)
- [Harnessing Discrete Representations For Continual Reinforcement Learning](https://mlsanity.com/paper/2312.01203/) (2023)
- [Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks](https://mlsanity.com/paper/2211.11869/) (2022)
- [Toward Agents That Reason About Their Computation](https://mlsanity.com/paper/2510.22833/) (2025)
- [Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement Learning](https://mlsanity.com/paper/2301.10119/) (2023)
- [Scaling Goal-based Exploration via Pruning Proto-goals](https://mlsanity.com/paper/2302.04693/) (2023)
- [NEOLAF, an LLM-powered neural-symbolic cognitive architecture](https://mlsanity.com/paper/2308.03990/) (2023)
- [Exploration by Random Distribution Distillation](https://mlsanity.com/paper/2505.11044/) (2025)
- [Position: Deployed Reinforcement Learning should be Continual](https://mlsanity.com/paper/2606.04029/) (2026)
- [Going Beyond State-Reaching: Learning Abstractions for Intrinsically Motivated Option Discovery](https://mlsanity.com/paper/2609.36473/) (2026)
- [Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning](https://mlsanity.com/paper/2406.19561/) (2024)
- [Lessons from Neuroscience for AI: How integrating Actions, Compositional Structure and Episodic Memory could enable Safe, Interpretable and Human-Like AI](https://mlsanity.com/paper/2512.22568/) (2025)
- [A Sense of Proprioception in Language Models](https://mlsanity.com/paper/2610.17495/) (2026)

## Abstract (arXiv)

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.