AbstractThis paper integrates logical and probabilistic approaches to the representation of planning problems by developing a first-order logic of time, chance, and action. We start by making explicit and precise commonsense notions about time, chance, and action central to the planning problem. We then develop a logic, the semantics of which incorporates these intuitive properties. The logical language integrates both modal and probabilistic constructs and allows quantification over time points, probability values, and domain individuals. Probability is treated as a sentential operator in the language, so it can be arbitrarily nested and combined with other logical operators. The language can represent the chance that facts hold and events...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...
We propose a wide-ranging knowledge representation formalism designed expressly to support many diff...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...
AbstractThis paper integrates logical and probabilistic approaches to the representation of planning...
As the limitations of traditional AI plan representations have become apparent, researchers have tur...
This paper describes a formalism, Statistical Event Logic (SEL), that adds statistical reasoning to ...
Automated planning is a major topic of research in artificial intelligence, and enjoys a long and di...
When agents devise plans for execution in the real world, they face two forms of uncertainty " ...
The temporal propositional logic of linear time is generalized to an uncertain world, in which rando...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
This paper shows how to combine decision theory and logical representations of actions in a manner t...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
A formal language for representing and reasoning about time, actions and plans in a uniform way is p...
The purpose of this paper is to give a formal account of a kind of agency so far neglected in the fi...
A formal language for representing and reasoning about time, actions and plans in a uniform way is p...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...
We propose a wide-ranging knowledge representation formalism designed expressly to support many diff...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...
AbstractThis paper integrates logical and probabilistic approaches to the representation of planning...
As the limitations of traditional AI plan representations have become apparent, researchers have tur...
This paper describes a formalism, Statistical Event Logic (SEL), that adds statistical reasoning to ...
Automated planning is a major topic of research in artificial intelligence, and enjoys a long and di...
When agents devise plans for execution in the real world, they face two forms of uncertainty " ...
The temporal propositional logic of linear time is generalized to an uncertain world, in which rando...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
This paper shows how to combine decision theory and logical representations of actions in a manner t...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
A formal language for representing and reasoning about time, actions and plans in a uniform way is p...
The purpose of this paper is to give a formal account of a kind of agency so far neglected in the fi...
A formal language for representing and reasoning about time, actions and plans in a uniform way is p...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...
We propose a wide-ranging knowledge representation formalism designed expressly to support many diff...
We focus on the aspect of sensing in reasoning about actions under qualitative and probabilistic unc...