Towards A Logical Account of Epistemic Causality

Reasoning about observed effects and their causes is important in multi-agent contexts. While there has been much work on causality from an objective standpoint, causality from the point of view of some particular agent has received much less attention. In this paper, we address this issue by incorporating an epistemic dimension to an existing formal model of causality. We define what it means for an agent to know the causes of an effect. Then using a counterexample, we prove that epistemic causality is a different notion from its objective counterpart. 1 Introduction Research on actual causality involves finding in a given narrative (trace) the event that caused an effect. Pearl [25, 26] was a pioneer to lead a computational enquiry in actual causality. The research was later continued by Halpern and Pearl [12, 15] and others [8, 17, 18, 13, 14]. Unfortunately, as argued by Glymour et al. [9], most of these accounts are developed by analyzing a handful of simple examples, and then validated relative to our intuition for these examples, a process which G oßler et al. [11] referred to as TEGAR (i.e. As such, even after multiple revisions, these definitions continue to suffer from various conceptual problems such as the early preemption problem and the over-determination problem. For instance, despite claims to the contrary, the definitions given in [14] suffer from the problem of preemption, which occurs when two competing events try to achieve the same effect and the latter of these fails to do so as the earlier one has already achieved the effect (see [31] and [4] for a discussion). In an attempt to address these issues, Batusov and Soutchanski [2, 3] recently proposed a new definition of actual causality that is based on a well developed and expressive formalization of actions and change, namely the situation calculus [23, 27]. The definition is derived from first principles and does not follow a TEGAR scheme.