M.Sc thesis ideas on the intersection: Artificial intelligence, Category theory, and Programming languages.

Hello all

I am searching for M.Sc thesis ideas on the intersection: Artificial intelligence, Category theory, and Programming languages. References to relevant papers will be appreciated.


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Probability monad

It seems to me that the topic of probability monads fits your bill. The top few Google hits are good, such as Norman Ramsey and Avi Pfeffer's POPL 2002 paper and sigfpe, Eric Kidd, and Martin Erwig's work.

Some of these were discussed

Gal, some of these were discussed here over the years. Check the archives.

You might also enjoy reading on backtracking monad transformers (see here and here)

Sergei Artemov

I would pay particular attention to the work of Sergei Artemov and his colleagues. You might wish to begin with this post here on LtU, and follow the links to the various papers. I do have the sense that both the logic/AI communities and the PLT communities should be pursuing this material aggressively.


To expand a bit Gal's question let me raise the question of what AI is these days. I am fairly sure it is difficult to give a satisfactory answer to this question without some effort.

On the contrary...

...it's as it was in the beginning, is now, and ever shall be, world without end, amen: that which we do not yet know how to compute. :-)

Yeah, right. So let me

Yeah, right.

So let me rephrase: What is the state of AI research these days? What are the central topics people actually work on?


This is also my main interest in relation to CT at the moment. If I am seeing a huge banana going 100 km/h on the highway, how is it that I can classify it as some sort of vehicle? still, some might classify it as a missile maybe? a child will probably see it as a huge banana. We have no *internal* view of that particular banana, so what *external* "forces" led one to make that analogy? or how does the mentioned banana compose into our mental image of reality? Why some "prefer" one analogy over another?

What about reduction and proof? Can we somehow code theorems in some formalism, and automate a search for a reduction based on our current knowledge base? I am talking about much larger steps then inference rules.

Can we explain learning via analogy ?

Well, well well... You

Well, well well...

You really should read a bit about Douglas Hofstadter's work on analogies. An easy place to start is his book Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought.

Book on its way :-)

This is getting way

This is getting way off-topic, but you might enjoy browsing Polya's books about the role of analogy in mathematics.

When I first saw your

When I first saw your quesiton I had a feeling that what you have in mind is more closely related to bisimulation that to logic programming. I see that I was right. Thinking about analogies and bisimulations may lead you in interesting directions...