Reasoning about Noisy Sensors in the Situation Calculus
Fahiem Bacchus, Joseph Y. Halpern, et al.
IJCAI 1995
We show that certain very different types of tasks can be modelled by one rule of abduction which we call coh(2), informally described as being able to go from the conclusions to the premises if the premises cohere, i.e. there is some semantic link between them. These tasks might come from the areas of natural language understanding, planning, perception, etc. Furthermore, there is a family of very closely related rules of coherence coh(n) that can do in one step what otherwise could require iteration of coh(2). More specifically, we formalize proximity-based reasoning as a kind of abduction; we show how it can be captured by such rules; and although we first present these rules informally, we later prove that their meaning can be made precise, and that it is possible to establish some formal properties of them. Of course, this requires a formalism for abduction, which is also sketched in the paper. All this leads to some mathematical results to the effect that certain natural strategies for using rules of coherence are sound and some others are not. Finally, we list some open problems that might be solvable by this approach. © 1994 Taylor & Francis Group, LLC.
Fahiem Bacchus, Joseph Y. Halpern, et al.
IJCAI 1995
Zijian Ding, Michelle Brachman, et al.
C&C 2025
Masami Akamine, Jitendra Ajmera
IEICE Trans Inf Syst
Rakesh Mohan, Ramakant Nevatia
IEEE Transactions on Pattern Analysis and Machine Intelligence