Innateness, AlphaZero, and Artificial Intelligence
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Abstract (arXiv)
The concept of innateness is rarely discussed in the context of artificial intelligence. When it is discussed, or hinted at, it is often the context of trying to reduce the amount of innate machinery in a given system. In this paper, I consider as a test case a recent series of papers by Silver et al (Silver et al., 2017a) on AlphaGo and its successors that have been presented as an argument that a "even in the most challenging of domains: it is possible to train to superhuman level, without human examples or guidance", "starting tabula rasa." I argue that these claims are overstated, for multiple reasons. I close by arguing that artificial intelligence needs greater attention to innateness, and I point to some proposals about what that innateness might look like.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jan 2018.
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Citing papers per year: 2021: 3; 2022: 4; 2023: 0; 2024: 2; 2025: 1.
10 papers.
- 2024ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Searchcited by 338
- 2021Why AI is Harder Than We Thinkcited by 40
- 2022DALL-E 2 Fails to Reliably Capture Common Syntactic Processescited by 31
- 2022Emergent Bartering Behaviour in Multi-Agent Reinforcement Learningcited by 18
- 2021Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variantscited by 6
- 2021Generalisation in Neural Networks Does not Require Feature Overlapcited by 0
- 2022AIGenC: An AI generalisation model via creativitycited by 0
- 2022A Roadmap to Domain Knowledge Integration in Machine Learningcited by 0
- 2024The μG Language for Programming Graph Neural Networkscited by 0
- 2025From Mimicry to True Intelligence (TI) -- A New Paradigm for Artificial General Intelligencecited by 0
- 2025From Mimicry to True Intelligence (TI) -- A New Paradigm for Artificial General Intelligence17 Sep 2025
- 2024The μG Language for Programming Graph Neural Networks12 Jul 2024
- 2024ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search6 Jun 2024
- 2022A Roadmap to Domain Knowledge Integration in Machine Learning12 Dec 2022
- 2022DALL-E 2 Fails to Reliably Capture Common Syntactic Processes23 Oct 2022
- 2022AIGenC: An AI generalisation model via creativity19 May 2022
- 2022Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning13 May 2022
- 2021Generalisation in Neural Networks Does not Require Feature Overlap4 Jul 2021
- 2021Why AI is Harder Than We Think26 Apr 2021
- 2021Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants24 Feb 2021