Example

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# Example

As last week, use the skiing knowledge base. A simple set of rules to infer which resort a skier should go to, given his purpose (to have fun or to practise serious skiing), the number of lessons he's had so far, and the number of press-ups he can do without collapsing.

```1 Resort = st sartre if
Rating = beginner and
Purpose = fun.

2 Resort = schloss heidegger if
Rating = beginner and
Purpose = serious.

3 Resort = chateau derrida if
Purpose = serious.

4 Resort = wittgenstein gladbach if
Purpose = fun.

5 Rating = beginner if
Lessons < 30.

6 Rating = beginner if
Lessons >= 30 and
Fitness = poor.

Lessons >= 30 and
Fitness = good.

8 Fitness = poor if
Pressups < 10.

9 Fitness = good if
Pressups >= 10.```

Start by assuming that STM contains these facts:

```Pressups = 15.
Lessons = 178.
Purpose = fun.```

We now repeat the recognise-resolve-act cycle as follows:

Recognise 1. Only rule 9 matches, so the conflict set is 9.

Resolve 1. Rather trivial, this! Pick rule 9.

Act 1. Add `Fitness = good` to STM.

Recognise 2. Rule 7 matches. Note that rule 9 also does - the new data doesn't contradict its conditions. So the conflict set consists of rules 7 and 9.

Resolve 2. Do we pick 7 or 9? There are various heuristics for conflict resolution. In this example, I'll use refractoriness, saying that if possible, we pick a rule that hasn't fired before. The justification behind this to to keep attention focussed on new things, and prevent the system getting into a loop. So pick 7.

Act 2. Add `Rating = advanced` to STM.

Recognise 3. Rules 4,7 and 9 match, so put all three into the conflict set.

Resolve 3. Do we pick 4, 7, or 9? Use refractoriness again, so pick 4.

Act 3. Add `Resort = wittgenstein gladbach` to STM.

Recognise 4. Rules 4,7 and 9 match, so put all three into the conflict set.

Resolve 4. Do we pick 4, 7, or 9? Well, none of the rules would tell us anything new, so we might as well stop.

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Jocelyn Ireson-Paine
Wed Feb 14 23:40:08 GMT 1996