History

The DMIP team began in 1997, and consolidated as a group in 2000, with the initial goal of extending ILP to other declarative languages. Since then, the group has been acquiring a broader view of the field, exploring different techniques and applications, focussing on the evaluation of machine learning and machine intelligence systems, spanning in many areas of machine learning, data mining and AI. 

Research areas

Artificial Intelligence, Machine Learning, Data Mining, Data Science, Intelligence measurement, Predictable AI, XAI, Knowledge Discovery, Multi-paradigm Inductive Programming, ROC analysis, ML Robustness, AI Fairness, cost-sensitive learning and model evaluation for decision support, Agreement Technologies, Agent Intelligence Evaluation, MML induction and Solomonoff prediction, Probabilistic (inductive) programming, Inductive Debugging, Universal Psychometrics, ...