Human-Level Intelligence or Animal-Like Abilities?
Not on the map. Why?
Abstract (arXiv)
The vision systems of the eagle and the snake outperform everything that we can make in the laboratory, but snakes and eagles cannot build an eyeglass or a telescope or a microscope. (Judea Pearl)
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jul 2017.
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Citing papers per year: 2021: 5; 2022: 1; 2023: 1; 2024: 1.
8 papers.
- 2021Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use casescited by 39
- 2021Learning First-Order Representations for Planning from Black-Box States: New Resultscited by 23
- 2021Neuro-Symbolic Constraint Programming for Structured Predictioncited by 11
- 2022A Test for Evaluating Performance in Human-Computer Systemscited by 8
- 2021Target Languages (vs. Inductive Biases) for Learning to Act and Plancited by 5
- 2023Q-Cogni: An Integrated Causal Reinforcement Learning Frameworkcited by 2
- 2021Teaching Machine Learning in K-12 Computing Education: Potential and Pitfallscited by 1
- 2024Backward explanations via redefinition of predicatescited by 0
- 2024Backward explanations via redefinition of predicates5 Aug 2024
- 2023Q-Cogni: An Integrated Causal Reinforcement Learning Framework26 Feb 2023
- 2022A Test for Evaluating Performance in Human-Computer Systems24 Jun 2022
- 2021Target Languages (vs. Inductive Biases) for Learning to Act and Plan15 Sep 2021
- 2021Teaching Machine Learning in K-12 Computing Education: Potential and Pitfalls2 Jun 2021
- 2021Learning First-Order Representations for Planning from Black-Box States: New Results23 May 2021
- 2021Neuro-Symbolic Constraint Programming for Structured Prediction31 Mar 2021
- 2021Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases23 Feb 2021