Measuring universal intelligence: Towards an anytime intelligence test
By José Hernandez-Orallo, David L. Dowe. 2010
182 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Evaluation & Benchmarks, Philosophy
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Marc G. Bellemare
- Michael H. Bowling
- Joel Veness
- Sergey Levine
- Pieter Abbeel
- José Hernandez-Orallo
- David Silver
- Joelle Pineau
In Computational Theory and Mathematics
- José Hernandez-Orallo
- Ben Goertzel
- Joel Veness
- Marc G. Bellemare
- Michael H. Bowling
- Yavar Naddaf
- Shane Legg
- Pei Wang
In Evaluation & Benchmarks
- Marc G. Bellemare
- Michael H. Bowling
- Joel Veness
- José Hernandez-Orallo
- Shane Legg
- Ben Goertzel
- David Silver
- Joelle Pineau
In Philosophy
- José Hernandez-Orallo
- Joel Veness
- Shane Legg
- Ben Goertzel
- Michael H. Bowling
- Marc G. Bellemare
- Yavar Naddaf
Citations in the corpus
- The Arcade Learning Environment: An Evaluation Platform for General Agents (2012, methodology): “More recently, the approaches of Hernández-Orallo and Dowe (2010) and of Legg and Veness (2011) appear to have some potential.”
- Evaluation in artificial intelligence: from task-oriented to ability-oriented measurement (2017, background): “A first framework for universal, anytime intelligence tests is introduced in (Hernández-Orallo and Dowe, 2010), where a class of environment is carefully chosen to be discriminative.”
- Artificial General Intelligence: Concept, State of the Art, and Future Prospects (2009, background): “Work by Hernandez-Orallo and Dowe pursues a similar concept with different technical details(Hernández-Orallo and Dowe, 2010).”
- The Measure of Intelligence (2019, unknown): “This idea is similar to the “anytime intelligence test” proposed in [38] and to the POET system proposed in [96].”
- An Approximation of the Universal Intelligence Measure (2011, methodology): “To do this we have randomly sampled programs from a simple universal Turing machine, drawing inspiration at points from [4], and the related work in [6].”