Safe goal-directed autonomy and the need for sound abstractions

Research output: Contribution to conferencePaperpeer-review

Abstract

The field of sequential decision making (SDM) captures a range of mathematical frameworks geared towards the synthesis of goal-directed behaviors for autonomous systems. Abstract benchmark problems such as the blocks-world domain have facilitated immense progress in solution algorithms for SDM. there is some evidence that a direct application of SDM algorithms in real-world situations can produce unsafe behaviors. This is particularly apparent in task and motion planning in robotics. We believe that the reliability of today’s SDM algorithms is limited because SDM models, such as the blocks-world domain, are unsound abstractions (those that yield false inferences) of real world situations. This position paper presents the case for a focused research effort towards the study of sound abstractions of models for SDM and algorithms for efficiently computing safe goal-directed behavior using such abstractions.

Original languageEnglish (US)
Pages591-594
Number of pages4
StatePublished - 2018
Event2018 AAAI Spring Symposium - Palo Alto, United States
Duration: Mar 26 2018Mar 28 2018

Conference

Conference2018 AAAI Spring Symposium
Country/TerritoryUnited States
CityPalo Alto
Period3/26/183/28/18

ASJC Scopus subject areas

  • Artificial Intelligence

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