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A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

机译：使用人工智能测试两个人工智能系统的效用的表征

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An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response), this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP) is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.
机译：专为在现实环境中运行而设计的人工智能系统面临着几乎无限的可能的性能场景。因此，设计人员和开发人员面临着在可预见和不可预见的条件下验证适当性能的挑战，特别是当人工智能正在控制将接近人类操作或可能对人类构成危险的机器人时。尽管手动创建测试用例可以进行有限的测试（可能确保一组可预见的条件触发适当的响应），但这可能不足以完全表征和验证安全的系统性能。提出了一种使用简单的人工智能测试用例生成器（AITCP）来验证人工智能系统性能的方法。 AITCP允许创建和模拟预期的操作方案，其速度远远超出了人工测试人员可能的速度。提出了用于测试自主导航控制系统的四种方案：二维空间中的单个角色，二维空间中的多个角色，三维空间中的单个角色以及三维空间中的多个角色。在每种情况下，将使用AITCP的效用与人工测试人员的效用进行了比较。

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