We present and demonstrate a particle filtering approach to data fusion and situation assessment for military operations in urban environments. Our approach views such an environment as a physical system whose state vector is composed of a large number of both discrete and continuous variables representing properties of tracked entities. Inferencing on such vector-based models exploits both cau...

Rbstract In the AI community, there is an ongoing debate as to the most appropriate theory of inferencing under uncertainty. This paper explores the problem of inference from a different perspective. It is suggested that an inferencing system should reflect an inference policy that is tailored to the domain of problems to which it is applied -and furthermore that an inference polic y need not c...

In this paper, an Integrated C-Object Tool, namely ICOT, is proposed for knowledge-based programming. A major drawback of current rule-based expert system languages is that they have difficulty in handling composite objects as a unit of inference. An object-oriented model is a powerful alternative to complement the drawback. Each of these alone cannot capture all the semantics of knowledge, par...

A core research concern in conversational case-based reasoning (CCBR) is how to select the most discriminative and natural questions to ask the user in the conversational process. There are two ways to realize this task: one is to remove the questions whose answers can be inferred from the information a user has provided, which is called dialogue inferencing; the other is to rank the questions ...

O'Brien, Shank, Myers, and Rayner (1988) reported that readers generated elaborative inferences only when a text contained characteristics that virtually eliminated the possibility of an inference being disconfirmed. We reanalyzed the data of O'Brien et al. (1988) and also conducted an experiment in which we varied (a) whether or not there was an anaphoric relation between a target word and its...

In recent years, knowledge-based systems have become one of the most popular approaches for solving engineering problems. Along with the rising complexity of the problem, knowledge management, acquisition, representation, inferencing, and refinement become increasingly difficult. Conventionally, tasks of knowledge acquisition and representation are accomplished separately and sequentially. Know...

There are a number of obstacles to successful operationalization of clinical practice guidelines, including the difficulty in accurately representing a statement's decidability or an action's executability. Both require reasoning with incomplete and imprecise information, and we present one means of processing such information. We begin with a brief overview of fuzzy set theory, in which elemen...

The Artificial Neural Networks (ANN) were widely and successfully used in the automatic speech recognition (ASR) field, but many limitations inherent to their learning style remain. In an attempt to overcome these limitations, we combine in a speech recognition hybrid system the pattern processing of the ANNs and the logical inferencing of the symbolic approaches. In particular, we are interest...

The Demonstrational Interfaces Project at CMU has been investigating various aspects of demonstrational interfaces for the last eight years. During this time, we have created six interactive software building tools that use demonstrational techniques, as well as an architecture to support demonstrational programming in general. In addition, we have created a demonstrational Visual Shell (iconic...

One of the main ways to acquire unfamiliar words is to make guesses about words meaning. This study investigates the comparative effects of pictorial annotations and morphological instructions on Iranian EFL learners’ lexical inferencing ability. Considering homogeneity issues using PET (Preliminary English Test), the researchers assigned the participants into two experimental and one control g...