From: Arun-Kumar Tripathi (
Date: 01/21/00

Dear Org Learners,

I have tried to write some snippets on the relationship of scientific
reasoning in AI and Philosophy of science..

Many types of scientific reasoning have long been identified and
recognised as supplying important methodologies for science, but many
questions regarding their logical and computational properties still
remain controversial.

These styles of reasoning include abduction, induction, model-based
reasoning, explanation and confirmation, all of them intimately related to
problems of belief revision and theory development, knowledge
assimilation, discovery and learning. Although these types of reasoning
have been studied both in artificial intelligence and in the philosophy of

Now some questions..
1) What are typical AI problems to which scientific reasoning can be
applied? How can these problems be characterised? Can these
characteristics be formalised?

2) What are typical problems in scientific methodology to which AI
techniques for ampliative reasoning (abduction, induction, confirmation,
etc) can be applied? How can these problems be characterised? Can these
characteristics be formalised?
3) What logical frameworks are appropriate for reasoning about the
differences and similarities among types of scientific reasoning? Is the
question of distinguishing or identifying them merely dependent on the
level of abstraction?
4) Is there a substantial difference between scientific reasoning as
conceived in the philosophy of science and in artificial intelligence?

5) What are the computational challenges for implementing processes such
as scientific discovery, theory development and truth approximation?

I would like to know your ideas, thoughts and references on the above
themes! Thank you!

Arun Tripathi


Arun-Kumar Tripathi <>

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