The AI seminar on 7th Dec 2023 will feature Prof Simon Dobson who will be talking about “Some stuff about sheaves”.
The seminar will be at 11am in JCB1.33a.
If you would like to join online, please email rh347@st-andrews.ac.uk for a link to the call.
A fully-funded PhD scholarship is available to support an exceptional student wishing to undertake doctoral research in health informatics, in particular looking at analysing and predicting disease trajectories of multimorbidity. This prestigious PhD scholarship is awarded by St Leonard’s Postgraduate College at the University of St Andrews and will be supervised by Dr Areti Manataki, Dr Katherine Keenan, Prof Colin McCowan and Dr Michail Papathomas. Applications must be received by 12 June 2023.
Further information, including how to apply, can be found at: https://www.st-andrews.ac.uk/study/fees-and-funding/scholarships/scholarships-catalogue/postgraduate-scholarships/world-leading-scholarship-04-computer-science-medicine-geography/
Jacob Howe, Senior Lecturer at City University London, and sabbatical visitor, will be giving a seminar to the AI Research Group at 2pm on Thursday 15th December in JC 1.33a.
The title and abstract are:
Propagation and Reification: SAT and SMT in Prolog
This talk will describe how a watched literal DPLL based Satisfiability (SAT)
solver can be succinctly coded in 20 lines of Prolog. The extension of
this solver to an Satisfiability Modulo Theories (SMT) solver 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.
Alice Toniolo, a new lecturer in Computer Science at St Andrews, will be giving a seminar to the Artificial Intelligence Research Group on Thursday 1st December 2016, 2pm, in JC 1.33a. All are welcome.
Computational argumentation: an overview of current reasoning and dialogue models and their applications
Abstract: Argumentation is the process of arriving at a decision for a controversial standpoint. Computational models of argumentation aim to imitate the human decision-making process by modelling reason for or against certain decisions and extract justifiable options. This talk will draw from philosophical studies to present the core concepts of argumentation theory in AI through a range of abstract, logical and dialogical models. I will focus on the potential of argumentation-based models employed by software agents to support reasoning and dialogue in the presence of incomplete, inconsistent and uncertain information. An application of argumentation-based reasoning is presented in the context of intelligence analysis. The agent-based tool discussed, called CISpaces (Collaborative Intelligence Spaces), employs argumentation to help analysts make sense of information in collaboration and provenance to establish the credibility of hypotheses.
