Building and Testing a General Intelligence Embodied in a Humanoid Robot
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Abstract (arXiv)
Machines with human-level intelligence should be able to do most economically valuable work. This aligns a major economic incentive with the scientific grand challenge of building a human-like mind. Here we describe our approach to building and testing such a system. Our approach comprises a physical humanoid robotic system; a software based control system for robots of this type; a performance metric, which we call g+, designed to be a measure of human-like intelligence in humanoid robots; and an evolutionary algorithm for incrementally increasing scores on this performance metric. We introduce and describe the current status of each of these. We report on current and historical measurements of the g+ metric on the systems described here.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 1 of its 44 references that are in the map. First posted on arXiv 26 Jul 2023.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 1.
4 papers.
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- 2024Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving24 May 2024
- 2024Temporal-Spatial Object Relations Modeling for Vision-and-Language Navigation23 Mar 2024
- 2023Towards Knowledge-driven Autonomous Driving7 Dec 2023