Reasoning about change: time and causation from the standpoint of artificial intelligence
Reasoning about change: time and causation from the standpoint of artificial intelligence
Embracing causality in fault reasoning
Artificial Intelligence
Formal theories of action (preliminary report)
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Reified temporal theories and how to unreify them
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
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Causal reasoning is an essential part of a number of tasks that have been central to many endeavours in AI--notably planning and prediction, diagnosis and explanation. Recently it has become an object of study in its own right, drawing inspiration from the work of philosophers and logicians as well as more immediately AI-oriented concerns. In this paper I shall examine just one approach to causal reasoning, that advocated by Yoav Shoham in a recent book and article. In particular, I shall try to lay bare a number of assumptions underlying Shoham's work, all of which I shall call into question. Key assumptions are that causality is an epistemic notion, that causal reasoning is inherently non-monotonic, and that epistemic reasoning should be handled by means of modal logic. While arguing against these assumptions, I do not offer a specific causal theory of my own, but shall conclude with some suggestions as to the general lines which I feel such a theory ought to follow.