This paper describes an interactive planning system that was developed inside an Intelligent Decision Support System aimed at supporting an operator when planning the initial attack to forest res. The planning architecture rests on the integration of case-based reasoning techniques with constraint reasoning techniques exploited, mainly, for performing temporal reasoning on temporal metric infor...

Temporal reasoning problems arise in many areas of AI, including planning, natural language understanding, and reasoning about physical systems. The computational complexity of continuous-time temporal constraint reasoning is fairly well understood. There are, however, many different cases where discrete time must be considered; various scheduling problems and reasoning about sampled physical s...

Temporal reasoning is an important topic in AI and Computer Science, comprising well-practiced problems such as planning and scheduling; more recently, also hardware verification problems have been cast in this framework. Efficient decision procedures for Temporal Reasoning are, therefore, strongly needed; at the same time, more and more expressivity is required. In this paper we present the te...

* supported by NSF Award CNS-0959958 Abstract The ability to reason about the spatial relationships between objects in the environment is a core requirement of mobile robots and many other types of intelligent systems. However, since objects frequently change their location, the representation of spatial location critically depends on time. Thus, what is really required is spatiotemporal reason...

Specifying, reasoning, and proving desirable properties of a concurrent system are important formal techniques to achieve the reliability of the system. The logic system that is widely used in the current approaches to specifying, reasoning, and proving properties of a concurrent system is temporal classical logic. This paper proposes a novel research direction, i.e., reasoning about dynamics o...

This paper demonstrates how a model for temporal context reasoning can be implemented. The approach is to detect temporally related events in natural language text and convert the events into an enriched logical representation. Reasoning is provided by a first order logic theorem prover adapted to text. Results show that temporal context reasoning boosts the performance of a Question Answering ...

Few attempts have been made to investigate the utility of temporal reasoning within machine learning frameworks for temporal relation classification between events in news articles. This paper presents three settings where temporal reasoning aids machine learned classifiers of temporal relations: (1) expansion of the dataset used for learning; (2) detection of inconsistencies among the automati...

In the ubiquitous computing environment, context reasoning is an important issue of context-awareness. It is used to deduce desired or higher-level context and then to provide suitable services automatically. The previous context-reasoning approaches are mainly non-temporal. The reasoning is according to the real-time contexts without time information. However, temporal contexts are very import...