Modeling in the early stage of system analysis is critical for understanding stakeholders, their needs, problems, and different viewpoints. We advocate methods for early domain exploration which provoke iteration over captured knowledge, helping to guide elicitation, and facilitating early scoping and decision making. Specifically, we provide a framework to support interactive, iterative analys...

In this paper we discuss techniques for online generation of macro-actions as part of the planning process and demonstrate their use in a forwardchaining search planning framework. The macroactions learnt are specifically created at places in the search space where the heuristic is not informative. We present results to show that using macro-actions generated during planning can improve plannin...

In this paper, we address the problem of answering (unions of) conjunctive queries on Aboxes. We propose a backward-chaining query evaluation based on query expansion. Expanding a query consists of determining all the ways of deriving it from atoms built on some distinguished predicates.

In this paper we present a proof-of-concept implementation of Neural Theorem Provers (NTPs), end-to-end differentiable counterparts of discrete theorem provers that perform first-order inference on vector representations of symbols using function-free, possibly parameterized, rules. As such, NTPs follow a long tradition of neural-symbolic approaches to automated knowledge base inference, but di...

In many engineering problems, unknown parameters of a model are inferred in order to make predictions, to design controllers, or to optimize the model. When parameters are distributed (continuous) or very high-dimensional (discrete) and quantities of interest are low-dimensional, parameters need not be fully resolved to make accurate estimates of quantities of interest. In this work, we extend ...

of the Forest Management Advisory Systems Yousong Chang and Donald Nute Artificial Intelligence Programs University of Georgia Athens, GA 30602 E-mail:[email protected] Expert system technology is a powerful tool for enhancing the decision making capabilities of nonexperts with reasonable knowledge of a domain to expert level in that domain. U.S.D.A. Forest Service has been working on forest ma...

This paper presents a fuzzy knowledge-based system for turbomachinery diagnosis. Given symptoms associated with a vibration problem, the system can identify and rank possible causes by performing incremental forward chaining. The diagnostic system incorporates an attribute weighting component to reflect the relative significance of conditional attributes, thereby allowing the system to produce ...

In this paper we describe a purely declarative method for introducing modularity into forward-chaining, rule-based languages and its embodiment in the Venus rule language. The method is enforced by the syntax of the language and includes the ability to parameterize the rule groups. Drawing from two of three Venus applications developed to date, we illustrate how this form of modularity contribu...

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 ans...