Qualitative Reasoning (QR) is an area of research within
Artificial Intelligence (AI) that automates
reasoning about continuous aspects of the physical world, such as space, time, and quantity, for the purpose of
problem solving
Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business an ...
and
planning
Planning is the process of thinking regarding the activities required to achieve a desired goal. Planning is based on foresight, the fundamental capacity for mental time travel. The evolution of forethought, the capacity to think ahead, is consi ...
using
qualitative
Qualitative descriptions or distinctions are based on some quality or characteristic rather than on some quantity or measured value.
Qualitative may also refer to:
*Qualitative property, a property that can be observed but not measured numericall ...
rather than
quantitative
Quantitative may refer to:
* Quantitative research, scientific investigation of quantitative properties
* Quantitative analysis (disambiguation)
* Quantitative verse, a metrical system in poetry
* Statistics, also known as quantitative analysis ...
information. Precise numerical values or quantities are avoided, and qualitative values are used instead (e.g., high, low, zero, rising, falling, etc.).
Purpose
Qualitative reasoning creates non-numerical descriptions of physical systems and their behavior, preserving important behavioral properties and qualitative distinctions.
The goal of qualitative reasoning research is to develop representation and reasoning methods that enable computer programs to reason about the behavior of physical systems, without precise quantitative information. An example is observing pouring rain and the steadily rising water level of a river, which is sufficient information to take action against possible flooding without knowing the exact water level, the rate of change, or the time the river might flood.
Principles
The principles used are motivated by human
cognition
Cognition refers to "the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, ...
.
The principles of qualitative reasoning include:
* Discrete values
** Represent continuous quantities using discrete entities for reasoning
** Example: Instead of using a numerical value for rate of change, consider whether it is increasing, decreasing or constant
* Relevant values
** Choose qualitative values based on relevance to a task
** Example: If the temperature is changing, the boiling point may be important, but if the temperature is constant, the boiling point may be irrelevant
* Ambiguous values or results
** Instead of providing one answer, provide a range of answers
** Example: Instead of computing a numeric level or quantity of water, provide two answers: low or zero
* Modeling a process
** Represent the states
** Represent the transitions between states
** For quantities, determine landmarks and use inequality reasoning
** Example:
If the temperature of water is below the boiling point, then the water level is constant or slowly decreasing;
if the temperature of water is above the boiling point, then the water level is rapidly decreasing;
if water has a temperature that changes from below the boiling point to above the boiling point, then the water level will change to rapidly decreasing;
if water is above the boiling point for a specified length of time, the water level will be low or zero
Uses
The techniques which have been developed for qualitative reasoning permit the simulation of quantitative systems which are subject to multiple constraints in the form of inequalities as well as equalities. It can permit the simulation of certain important systems, such as ecosystems, which might otherwise be too complex to model. Qualitative reasoning provides a method for modeling with quantitative inequalities in addition to qualities.
Successful application areas include
process control
An industrial process control in continuous production processes is a discipline that uses industrial control systems to achieve a production level of consistency, economy and safety which could not be achieved purely by human manual control. I ...
, system verification, explanation,
autonomous spacecraft support, simulation and explanation of the behavior of structures,
[{{cite journal , last1=Salvaneschi , first1=Paolo , last2=Cadei , first2=Mauro , last3=Lazzari , first3=Marco , date=1997 , title=A causal modelling framework for the simulation and explanation of the behaviour of structures , journal=Artificial Intelligence in Engineering , volume=11 , issue=3 , pages=205–216 , doi=10.1016/S0954-1810(96)00040-4] failure analysis and on-board diagnosis of vehicle systems, automated generation of control software for photocopiers, conceptual knowledge capture in ecology, and intelligent aids for human learning.
See also
*
Spatial-temporal reasoning
*
Qualitative Reasoning Group (QRG)
References
External links
Qualitative Reasoning and Modelling (QRM) portal of the University of Amsterdam
Reasoning