Title | ||
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Accelerating progress in Artificial General Intelligence: Choosing a benchmark for natural world interaction. |
Abstract | ||
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A benchmark in the field of Artificial General Intelligence (AGI) would allow evaluation and comparison of the many computational intelligence algorithms that have been developed. In this paper I propose that an ideal benchmark for natural world interaction would possess seven key characteristics: fitness, breadth, specificity, low cost, simplicity, range, and task focus. I also describe two benchmarks that meet most of these criteria well. In the first, the direction task, a human coach directs a machine to perform a novel task in an unfamiliar environment. The direction task is extremely broad and may be suitable as a long-term benchmark. In the second, the AGI battery, AGI candidates are evaluated based on their performance on a collection of more specific tasks. The AGI battery is designed to be appropriate to the capabilities of currently existing systems and may be a better near-term benchmark. The paper concludes with a description of a task that might be included in the AGI battery: the search and retrieve task. |
Year | DOI | Venue |
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2010 | 10.2478/v10229-011-0005-5 | J. Artificial General Intelligence |
Keywords | Field | DocType |
natural world interaction,roadmap,direction task,metrics,breadth,agi battery,benchmark | Computer science,Artificial general intelligence,Artificial intelligence,Machine learning | Journal |
Volume | Issue | Citations |
2 | 1 | 5 |
PageRank | References | Authors |
0.53 | 9 | 1 |
Name | Order | Citations | PageRank |
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Brandon Rohrer | 1 | 60 | 8.93 |