This thesis develops a framework, automated by a toolchain, to address the problem of operationalizing actual causality for purposes related to accountability. The framework tackles the efficiency, and scalability of different notions of automated causal reasoning. It considers the effectiveness of this reasoning through practical domain-specific approaches to causal modeling and contextualization. The framework diminishes the barrier to embedding causality in new domains because it promotes reuse. On the one hand, it contributes a set of general algorithms to automate reasoning so that it can be reused among different domains. It supports, on the other hand, the reuse of domain-specific methodologies to operationalize modeling and contextualization.
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This thesis develops a framework, automated by a toolchain, to address the problem of operationalizing actual causality for purposes related to accountability. The framework tackles the efficiency, and scalability of different notions of automated causal reasoning. It considers the effectiveness of this reasoning through practical domain-specific approaches to causal modeling and contextualization. The framework diminishes the barrier to embedding causality in new domains because it promotes reu...
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