What Role Can Ontologies Play to Improve the Performance of Intelligent Systems?

Craig Schlenoff

Intelligent Systems Division

National Institute of Standards and Technology

There are at least three overarching questions

that one may ask regarding the role of ontologies

in performance evaluation. They are:

1. How can an ontology play a role in

evaluating intelligent systems?

2. How can an ontology within an intelligent

system be evaluated?

3. How can ontologies play a role in helping an

intelligent system perform at a higher level

of performance?

This write-up focuses on this third question.

When most people think about the role of

ontologies in performance evaluation, they often

ask question such as:

• What will be the purpose of the ontology?

• How formal of an ontology does one need?

• How does one create such ontologies?

To attempt to answer these questions, one can

imagine introducing an ontology (or set of

ontologies) into an autonomous vehicular

system’s knowledge base. Let’s assume that the

ontology consisted of various objects that the

vehicle expected to encounter in its environment,

as well as the important characteristics of each

object. This ontology would help to answer

question such as:

• Based upon the data we get from our

sensors, what are the objects we perceive in

the environment at the given time, with

appropriate levels of confidence?

• What characteristics of those objects do I

need to be most concerned about?

With the introduction of ontologies representing

factors that effect the motion of objects (such as

an ontology representing the “rules of the road”,

motion limitation of certain vehicles, the

network of roads in the environment), we could

answer questions such as:

• Where do we expect an object to be at a time

in the future?

• What is our risk of colliding with the object

assume the motion patterns do not change?

Assuming the ontology has clearly defined

semantics, we can use the ontology to

unambiguously exchange information among

different autonomous vehicles (or between a

vehicle and a human) that are working together

to jointly accomplish a goal.

With the introduction of an ontology of actions

that an autonomous vehicle is able to perform,

we could answer questions such as:

• How can the overall goal of the vehicle be

decomposed into actionable items?

• What are the appropriate actions in a given

situation?

Based on these ontologies, if the entire

environment around the vehicle at any given

time could be completed modeled, we could

evaluate the planner by answering questions such

as:

• Has the planner identified all possible plans?

• Does the chosen plan truly accomplish the

stated goal?

Therefore, I contend that ontologies can play a

role in improving the performance of almost

every part of autonomous vehicular systems, and

most likely in intelligent systems as a whole.

However, that is not to say that there aren’t

various technical challenges that have to be

addressed before ontologies can be used in this

context. Some of the questions that need to be

address include:

• How can ontologies be linked to other types

of representations, including sensor data?

• Can ontologies respond quickly enough to

be useful in a real-time environment?

• Are ontologies reusable in intelligent

systems, and if so, what is the best

mechanism to share them with each other?

• How can one evaluate the performance of

the ontology?