为自主系统责任归属与预判提供可计算的逻辑框架
Computational Grounding of Responsibility Attribution and Anticipation in LTLf
- 基于LTLf逻辑构建责任分析的策略模型
- 揭示责任判定与反应式合成算法的深层关联
- 适合研究伦理机器与智能系统决策的学者
责任是机器伦理与自主系统中的核心概念，涉及对行为与策略的反事实推理。本文在LTLf逻辑框架下研究战略场景中责任的不同变体，揭示其与反应式合成中获胜策略、主导策略及尽力而为策略之间的联系。这一关联为责任归属与预判提供了计算基础，包括复杂度刻画以及责任分配与预测的可靠、完备且最优的算法。
原文摘要 · Abstract (English)
Responsibility is one of the key notions in machine ethics and in the area of autonomous systems. It is a multi-faceted notion involving counterfactual reasoning about actions and strategies. In this paper, we study different variants of responsibility in a strategic setting based on LTLf. We show a connection with notions in reactive synthesis, including synthesis of winning, dominant, and best-effort strategies. This connection provides the building blocks for a computational grounding of responsibility including complexity characterizations and sound, complete, and optimal algorithms for attributing and anticipating responsibility.
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