This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically modelling and merging information under uncertainty in some real world systems where the state of a system evolves over time and the transition through states depends on uncertain conditions. We provide forward and backward reasoning algorithms which, respectively, support simulation and query answering. These algorithms are then explained through several examples based on Smart Homes applications
For modelling and verifying agent systems, many researchers have proposed different logical systems....
In this paper we describe a general way of formalizing reasoning behaviour. Such a behaviour may be ...
Temporal reasoning is recognized as an essential issue in Artificial Intelligence. In this work, the...
This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically m...
This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically m...
Decision-making on uncertain and dynamic domains is still a challenging research area. This paper ex...
Decision-making on uncertain and dynamic domains is still a challenging research area. This paper ex...
Integrating logical and probabilistic reasoning and integrating reasoning over observations and pred...
International audienceThis paper presents a framework to build home automation systems reactive to v...
This paper demonstrates how a model for temporal context reasoning can be implemented. The approach ...
The paper is devoted to a problem of temporal reasoning for (among others) managerial tasks. It show...
Most of AI research on temporal reasoning has been devoted to either exploring constraint-based temp...
Time is one of the most relevant topics in AI. It plays a major role in several areas, ranging from ...
One of the most important challenges of the creation of intelligent environments is the specificatio...
Stream reasoning can be defined as incremental reasoning over incrementally-available information. T...
For modelling and verifying agent systems, many researchers have proposed different logical systems....
In this paper we describe a general way of formalizing reasoning behaviour. Such a behaviour may be ...
Temporal reasoning is recognized as an essential issue in Artificial Intelligence. In this work, the...
This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically m...
This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically m...
Decision-making on uncertain and dynamic domains is still a challenging research area. This paper ex...
Decision-making on uncertain and dynamic domains is still a challenging research area. This paper ex...
Integrating logical and probabilistic reasoning and integrating reasoning over observations and pred...
International audienceThis paper presents a framework to build home automation systems reactive to v...
This paper demonstrates how a model for temporal context reasoning can be implemented. The approach ...
The paper is devoted to a problem of temporal reasoning for (among others) managerial tasks. It show...
Most of AI research on temporal reasoning has been devoted to either exploring constraint-based temp...
Time is one of the most relevant topics in AI. It plays a major role in several areas, ranging from ...
One of the most important challenges of the creation of intelligent environments is the specificatio...
Stream reasoning can be defined as incremental reasoning over incrementally-available information. T...
For modelling and verifying agent systems, many researchers have proposed different logical systems....
In this paper we describe a general way of formalizing reasoning behaviour. Such a behaviour may be ...
Temporal reasoning is recognized as an essential issue in Artificial Intelligence. In this work, the...