Situated Conditional Reasoning
Giovanni Casini, Thomas Meyer, Ivan Varzinczak

TL;DR
This paper introduces situation-based conditionals that are more expressive than classical ones, capable of capturing nuanced information like expectations and counterfactuals, with a formal semantics and an efficient reasoning method.
Contribution
It formalizes situation-based conditionals, provides a semantics and representation theorem, and develops a computationally feasible entailment method called minimal closure.
Findings
Situation-based conditionals generalize classical conditionals.
A formal semantics and rationality postulates are established.
Minimal closure can be computed via propositional entailment checks.
Abstract
Conditionals are useful for modelling, but are not always sufficiently expressive for capturing information accurately. In this paper we make the case for a form of conditional that is situation-based. These conditionals are more expressive than classical conditionals, are general enough to be used in several application domains, and are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situation-based conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals, and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we proceed to define a form of…
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Taxonomy
TopicsSemantic Web and Ontologies · Logic, Reasoning, and Knowledge · Bayesian Modeling and Causal Inference
