Research Projects
Interactive Visual Methods for Partitioning Multidimensional Spatial Data KEDS: Knowledge-Enhanced discovery Systems Organizational Learning POIROT: Plan-Order-Induction by Reasoning From One Trial MATES: Making Agent Teams Evoke Synergy
Developing methods for dynamic organization (combinatorial strategy selection and task allocation) in multi-agent systems Studying the effect of social graph structures on large-scale multi-agent systems Developing constraint satisfaction methods for planning and scheduling that take into account the cost of checking constraints Incorporating background knowledge into machine learning techniques Interactive methods for planning, scheduling, and machine learning
VisARD: Visualizing dynamic relational models in complex domains Virtual Telescopes in Education
Online and active learning methods for text classification Applying AI planning techniques to perform service composition for the Semantic Web Applying genetic algorithms to learning game playing strategies |
