In this paper we describe a general way of formalizing reasoning behaviour. Such a behaviour may be described by all the patterns which are valid for the behaviour. A pattern can be seen as a sequence of information states which describe what has been derived at each time point. A transition from an information state at a point in time to the state at the (or a) next time point is induced by one or more inference steps. We choose to model the information states by partial models and the patterns either by linear time or branching time temporal models. Using temporal logic one can define theories and look at all models of that theory. For a number of examples of reasoning behaviour we have been able to define temporal theories such that its ...
A class of interval-based temporal languages for uniformly representing and reasoning about actions ...
The paper is devoted to a problem of temporal reasoning for (among others) managerial tasks. It show...
Modelling, reasoning about and integrating knowledge based on multiple time granularities in knowled...
Meta-level architectures for dynamic control of reasoning processes are quite powerful. In the liter...
To model the dynamics of cognitive processes, often the dynamical systems theory (DST) is advocated....
To model the dynamics of cognitive processes, often the Dynamical Systems Theory (DST) is advocated....
Abstract. In this paper we formalize default reasoning using branching time temporal models, in whic...
Much previous work in artificial intelligence has neglected representing time in all its complexity....
By explicitly identifying the temporal aspect of a default rule as it is used in a reasoning process...
The representation and manipulation of natural human understanding of temporal phenomena is a fundam...
Most of AI research on temporal reasoning has been devoted to either exploring constraint-based temp...
A temporal logic is presented for reasoning about propositions whose truth values might change as a ...
The topic of this thesis is temporal logical inference in atemporal models of time. The thesis prese...
This paper is concerned about the way humans reason about time in the light of reasoning theories an...
In this paper we describe a framework for reasoning about temporal explanation problems, which is b...
A class of interval-based temporal languages for uniformly representing and reasoning about actions ...
The paper is devoted to a problem of temporal reasoning for (among others) managerial tasks. It show...
Modelling, reasoning about and integrating knowledge based on multiple time granularities in knowled...
Meta-level architectures for dynamic control of reasoning processes are quite powerful. In the liter...
To model the dynamics of cognitive processes, often the dynamical systems theory (DST) is advocated....
To model the dynamics of cognitive processes, often the Dynamical Systems Theory (DST) is advocated....
Abstract. In this paper we formalize default reasoning using branching time temporal models, in whic...
Much previous work in artificial intelligence has neglected representing time in all its complexity....
By explicitly identifying the temporal aspect of a default rule as it is used in a reasoning process...
The representation and manipulation of natural human understanding of temporal phenomena is a fundam...
Most of AI research on temporal reasoning has been devoted to either exploring constraint-based temp...
A temporal logic is presented for reasoning about propositions whose truth values might change as a ...
The topic of this thesis is temporal logical inference in atemporal models of time. The thesis prese...
This paper is concerned about the way humans reason about time in the light of reasoning theories an...
In this paper we describe a framework for reasoning about temporal explanation problems, which is b...
A class of interval-based temporal languages for uniformly representing and reasoning about actions ...
The paper is devoted to a problem of temporal reasoning for (among others) managerial tasks. It show...
Modelling, reasoning about and integrating knowledge based on multiple time granularities in knowled...