Intelligent Systems Research Group

The Intelligent Systems Group pursues internationally-leading research in a wide range of Intelligent Systems, with strengths in theory and applications in

• Evolutionary Algorithms, Optimisation and Learning.  The group is a world-leader in evolutionary computation and has a major presence in numerical optimisation and information theory. More information
   
• Brain-Computer Interfaces.  The group works in the rapidly growing area of detecting and then converting brain responses into control signals for a computer. More information
   
• Computational Finance and Economic Agents.  The group has become a world-leader in the area of Computational Finance. A Centre for Computational Finance and Economic Agents (CCFEA) was established (2004) by the group and staff in Economics, in Accountancy, Finance and Management, and in Mathematics. More information

Current interests

• population-based and probabilistic search methods
• swarm-intelligence and principled swarm-engineering design methodologies
• non-linear multi-step conjugate-gradient methods
• interdisciplinary integration of evolutionary computation constraint-satisfaction techniques in computational finance and economics
• exploiting statistical mechanics/stochastic-control theory for the better understanding of intelligent systems
• developing features and classifiers that maximize BCI reliability and speed
• experimental protocols for BCIs based on psychophysics and neuroscience
• ab-initio game strategy learning
• improving modelling and model selection in finance and financial econometrics;
• wind-tunnel testing for financial theory as well as policy, strategy and institutional design;
• improved (automated) trading and bargaining systems
• negotiation, auctions and trading agents

Group Members

Maria Fasli
Simon Lucas
Dietmar Maringer (CCFEA)
Nigel Newton
Palaniappan Ramaswamy
Riccardo Poli
Francisco Sepulveda
Edward Tsang
Qingfu Zhang