A Framework for Reasoning Precisely with Vague Concepts

نویسندگان

  • Nita Goyal
  • Yoav Shoham
  • Nils J. Nilsson
  • Patrick J. Hayes
  • Nils Nilsson
  • Surajit Chaudhuri
چکیده

Many knowledge-based systems need to represent vague concepts such as \old" and \tall". The practical approach of representing vague concepts as precise intervals over numbers (e.g., \old" as the interval [70,110]) is well-accepted in Arti cial Intelligence. However, there have been no systematic procedures, only ad hoc methods, to delimit the boundaries of intervals representing the vague predicates. A key observation is that the vague concepts and their interval boundaries are constrained by the underlying domain knowledge. Therefore, any systematic approach to assigning interval boundaries must take the domain knowledge into account. In this dissertation, we introduce a framework to represent the domain knowledge and use it to reason about the interval boundaries via a query language. This framework is comprised of a constraint language to represent logical constraints on the vague concepts, as well as numerical constraints on the interval boundaries; a query language to request information about the interval boundaries; and an algorithm to answer the queries. The algorithm preprocesses the constraints by extracting the numerical information from the logical constraints and then combines them with the given numerical constraints. We have implemented the framework and applied it to two domains to illustrate its usefulness.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Vague Concepts: A Rough Set Approach

The approximation space definition has evolved in rough set theory over the last 15 years. The aim was to build a unified framework for concept approximations. We present an overview of this evolution together with some operations on approximation spaces that are used in searching for relevant approximation spaces. Among such operations are inductive extensions and granulations of approximation...

متن کامل

Rough Sets and Higher Order Vagueness

We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in searching for concept approximation is emphasized. Boundary regions of approximated concepts within the adaptive learning framework are satisfying the higher order vagueness condition, i.e., the boundary regions of vague concepts...

متن کامل

A Fuzzy Description Logic

Description Logics (DLs, for short) allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with crisp, well defined concepts. That is, concepts for which the problem whether an individual is an instance of it is a yes/no question. More often than not, the concepts encountered in the real world do not have a precisely...

متن کامل

Reasonin recis - ItS

Many knowledge-based systems need to represent vague concepts. Although the practical approach of representing vague concepts as precise intervals over numbers is well-accepted in AI, there is no systematic method to delimit the boundaries of intervals, only ad hoc methods. We present a framework to reason precisely with vague concepts based on the observation that the vague concepts and their ...

متن کامل

Vague size predicates

Vague predicates such as heap, tall, bald, near to, nicer than, etc. are characterized by their Sorites susceptibility and the existence of borderline cases. In attempting to develop a general theory, diverse vague predicates are often analyzed in rather broad natural language settings. Because this has proven to be rather difficult, the phenomenon of vagueness is studied here in a narrower and...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998