Action Languages Based Actual Causality for Computational Ethics: a Sound and Complete Implementation in ASP
Although moral responsibility is not circumscribed by causality, they are both closely intermixed. Furthermore, rationally understanding the evolution of the physical world is inherently linked with the idea of causality. Thus, the decision-making applications based on automated planning inevitably have to deal with causality, especially if they consider imputability aspects or integrate references to ethical norms. The many debates around causation in the last decades have shown how complex this notion is and thus, how difficult is its integration with planning. As a result, much of the work in computational ethics relegates causality to the background, despite the considerations stated above. This paper's contribution is to provide a complete and sound translation into logic programming from an actual causation definition suitable for action languages, this definition is a formalisation of Wright's NESS test. The obtained logic program allows to deal with complex causal relations. In addition to enabling agents to reason about causality, this contribution specifically enables the computational ethics domain to handle situations that were previously out of reach. In a context where ethical considerations in decision-making are increasingly important, advances in computational ethics can greatly benefit the entire AI community.
Code (0)
등록된 구현이 없습니다.
Tasks
Decision MakingEthicsSimilar Papers 제목 키워드 기반
Formalizing Kantian Ethics: Formula of the Universal Law Logic (FULL)
The field of machine ethics aims to build Artificial Moral Agents (AMAs) to better understand morality and make AI agents safer. To do so, many approaches encode human moral intuition as a set of axioms on actions e.g., …
Counterfactual Causality from First Principles?
In this position paper we discuss three main shortcomings of existing approaches to counterfactual causality from the computer science perspective, and sketch lines of work to try and overcome these issues: (1) causality…
counterfactualPositionActual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes
Actual causality and a closely related concept of responsibility attribution are central to accountable decision making. Actual causality focuses on specific outcomes and aims to identify decisions (actions) that were cr…
Decision MakingDecision Making Under UncertaintySequential Decision MakingFrom Checking to Inference: Actual Causality Computations as Optimization Problems
Actual causality is increasingly well understood. Recent formal approaches, proposed by Halpern and Pearl, have made this concept mature enough to be amenable to automated reasoning. Actual causality is especially vital …
counterfactualEmbracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach
This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual ca…