Event-Based and Scenario-Based Causality for Computational Ethics

Abstract : This paper makes use of high-level action languages to investigate aspects of causality that are central to ethical reasoning. We identify properties that causal relations assume and that determine how, as well as to what extent, we may ascribe ethical responsibility on their basis. The paper is structured in three parts. First, we present an extension of the Event Calculus that enables the agent to generate plans of actions, with the particularity that they integrate both actions and omissions. Second, we present an account of event-based causality that is grounded in the architecture of event preconditions and effects, and that distinguishes four types of causal relations contingent on the nature of the entities that compose them. Namely, it discriminates actions and omissions from automatic events, and produced outcomes from avoided ones. Third, we examine notions of scenario-based causality whose role it is to scrutinise and buttress the causal relations previously identified. Inquiring into the other possible versions of modelled scenarios, we account for simple counter-factual validity ("Had I not acted so, would this outcome still be true?"), criticality ("Could anything else have led to this outcome?"), extrinsic necessity ("Had I not produced it, was this outcome even avoidable?"), and elicited necessity ("Have I made this outcome unavoidable?"). The model is implemented in Answer Set Programming.
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Fiona Berreby, Gauvain Bourgne, Jean-Gabriel Ganascia. Event-Based and Scenario-Based Causality for Computational Ethics. AAMAS 2018 - 17th International Conference on Autonomous Agents and Multiagent Systems, Jul 2018, Stockholm, Sweden. pp.147-155. ⟨hal-01982090⟩

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