_:n3059af24cd0142988d00b550533faa2fxb28
<http://schema.org/description>
"In this paper, we investigate bounded action theories in the situation\ncalculus. A bounded action theory is one which entails that, in every\nsituation, the number of object tuples in the extension of fluents is bounded\nby a given constant, although such extensions are in general different across\nthe infinitely many situations. We argue that such theories are common in\napplications, either because facts do not persist indefinitely or because the\nagent eventually forgets some facts, as new ones are learnt. We discuss various\nclasses of bounded action theories. Then we show that verification of a\npowerful first-order variant of the mu-calculus is decidable for such theories.\nNotably, this variant supports a controlled form of quantification across\nsituations. We also show that through verification, we can actually check\nwhether an arbitrary action theory maintains boundedness."
<https://cdnjs.deepai.org/profile/fabio-patrizi>