AI Research Group

This is the website for the Artificial Intelligence Research Group at the University of St Andrews. Find out who our members are on the People page. Have a look at some of our Research Projects. Or take a look at all the papers published by our members on the Publications page.

The Artificial Intelligence Research Group’s work in artificial intelligence and symbolic computing is concerned with how we can make use of computers to augment human mathematical and logical capabilities and in investigating how to automate human capabilities such as face recognition. We are very active in the field of Constraint Programming, where our interests are constraint modeling and design of efficient constraint solvers – such of Minion.

News and Events

The latest AI Research Group posts from the School of Computer Science blog.

Seminar: Propagation and Reification: SAT and SMT in Prolog (continued)


Jacob Howe, City University, London

Abstract: This talk will recap how a watched literal DPLL based SAT solver can be succinctly coded in 20 lines of Prolog. The focus of the talk will be the extension of this solver to an SMT solver which will be discussed with a particular focus on the case where the theory is that of rational-tree constraints, and its application in a reverse engineering problem.
[Note change of time from that previously advertised]

Success in the Laidlaw Undergraduate Internship Programme in Research and Leadership


Congratulations to Patrick Schrempf and Billy Brown who have been successful in their applications for a Laidlaw Undergraduate Internship in Research and Leadership for 2017. You can read further details about Billy and Patrick below.

Billy Brown:

I’m a fourth year Computer Science student from Belgium with too much interest for the subject. I play and referee korfball for the university, and I am fascinated by Old English and Norse history and mythology. I plan on using the Laidlaw Internship programme to get into the field of Computer Science research.

Project summary:

The Essence Domain Inference project aims to improve automated decision making by optimising the understanding of the statements used to define a problem specification. As part of the compilation of the high level Essence specification language, this project would tighten the domains to which a specified problem applies, with a domain inference algorithm.

The work is very much in the context of the recently-announced EPSRC grant working on automated constraint modelling in an attempt to advance the state of the art in solving complex combinatorial search problems. The modelling pipeline is akin to a compiler in that we refine a specification in the Essence language Billy mentions down to a number of powerful solving formalisms. The work Billy plan is to improve the refinement process and therefore the performance of the solvers, leading to higher quality solutions more quickly.

Patrick Schrempf:
I am currently a third year Computer Science student from Vienna. After enjoying doing research with the St Andrews Computer Human Interaction (SACHI) group last year, I am looking forward to the Laidlaw Internship Programme. Apart from research and studying, I enjoy training and competing with the Triathlon Club and the Pool Society.
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