Situation calculus has been applied widely in artificial intelligence to model and reason about actions and changes in dynamic systems. Since actions carried out by agents will cause constant changes of the agents’ beliefs, how to manage these changes is a very important issue. Shapiro et al. [22] is one of the studies that considered this issue. However, in this framework, the problem of noisy...

This paper presents a logical approach to formalization of some aspects of multi-agent systems in an incompletely known world. The contribution on this regard is as follows. We formalized reasoning about concurrent actions inside the situation calculus framework which has the suuciently clear and well-understood semantics to express diierent aspects of agent theory. Conclusions can be drawn by ...

We propose a simple relaxation of Reiter’s basic action theories, based on fluents without successor state axioms, that accommodates incompleteness beyond the initial database. We prove that fundamental results about basic action theories can be fully recovered and that the generalized framework allows for natural specifications of various forms of incomplete causal laws. We illustrate this by ...

Obligation change raises the “frame problem” which is to characterise what obligations remain unchanged after an action has been performed. Many general solutions have been proposed but even if they are attractive from a thoretical point of view they have practical draw-

This paper examines the semantics of a group of logical techniques, used by the Artificial Intelligence community, and which are fundamental for circumscriptionbased approaches to the situation calculus. At first sight, this calculus appears to be an operationalised version of David Lewis’ account of causal reasoning: there are items – here called ‘situations’ – which are analogous to Lewis’ po...

We design a representation based on the situation calculus to facilitate development, maintenance and elaboration of very large taxonomies of actions. This representation leads to more compact and modular basic action theories (BATs) for reasoning about actions than currently possible. We compare our representation with Reiter’s BATs and prove that our representation inherits all useful propert...

This article considers defeasible beliefs in dynamic settings. In particular, we examine the belief projection problem: what is believed after performing an action and/or receiving new information? The approach is based on an epistemic variant of Reiter’s situation calculus, where actions not only have physical effects but may also provide new information to the agent. The preferential belief s...

When Lin and Reiter introduced the progression of basic action theories in the situation calculus, they were essentially motivated by long-lived robotic agents functioning over thousands of actions. However, their account does not deal with probabilistic uncertainty about the initial situation nor with effector or sensor noise, as often needed in robotic applications. In this paper, we obtain r...

Fundamental to reasoning about actions and beliefs is the projection problem: to decide what is believed after a sequence of actions is performed. Progression is one widely applied technique to solve this problem. In this paper we propose a novel framework for computing progression in the epistemic situation calculus. In particular, we model an agent’s preferential belief structure using condit...