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Opportunistic reasoning

Opportunistic reasoning is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Opportunistic reasoning rather than just read about it. In short: Opportunistic reasoning is a method of selecting a suitable logical inference strategy within artificial intelligence applications. Specific reasoning methods may be used to draw conclusions from a set of given facts in a knowledge base, e.g. forward chaining versus backward chaining.

Key takeaways

  • Opportunistic reasoning belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Opportunistic reasoning to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Opportunistic reasoning from memory before moving on to harder problems.

Reference excerpt

Opportunistic reasoning is a method of selecting a suitable logical inference strategy within artificial intelligence applications. Specific reasoning methods may be used to draw conclusions from a set of given facts in a knowledge base, e.g. forward chaining versus backward chaining. However, in opportunistic reasoning, pieces of knowledge may be applied either forward or backward, at the "most opportune time". An opportunistic reasoning system may combine elements of both forward and backward reasoning. It is useful when the number of possible inferences is very large and the reasoning system must be responsive to new data that may become known. Opportunistic reasoning has been used in applications such as blackboard systems and medical applications.

References Marin D. Simina et al. "Opportunistic Reasoning: A Design Perspective" in Proceedings of the Seventeenth Annual Conference of Cognitive Science edited by Johanna D. Moore, 1995 ISBN 0-8058-2159-7, page 78

Notes

Worked examples

Example 1 — a first encounter with Opportunistic reasoning

Start with the simplest possible case. Write down what Opportunistic reasoning claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Opportunistic reasoning before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Opportunistic reasoning ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Opportunistic reasoning

In research
Opportunistic reasoning appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Opportunistic reasoning in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Opportunistic reasoning is common in secondary-school and first-year university syllabi. It links to neighbouring topics Artificial intelligence stubs, Automated reasoning, so understanding it makes those chapters shorter.
In everyday life
Look for Opportunistic reasoning outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Opportunistic reasoning in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Opportunistic reasoning means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Opportunistic reasoning out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Opportunistic reasoning in simple terms?

Opportunistic reasoning is a method of selecting a suitable logical inference strategy within artificial intelligence applications. Specific reasoning methods may be used to draw conclusions from a set of given facts in a knowledge base, e.g. forward chaining versus backward chaining.

Why does Opportunistic reasoning matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Opportunistic reasoning?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Opportunistic reasoning.

Tags

  • Artificial intelligence stubs
  • Automated reasoning

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