Our research
We address:
- models of safety
- responsibility and optimisation for artificial intelligence (AI) systems
- reinforcement learning
- game theory and negotiation
- mechanism design
- reasoning and learning under uncertainty
- ethical and responsible AI
Human-in-the-loop interaction
Research challenges in this area include exploring how to build better human-in-the-loop AI systems which use AI o support and augment human performance. This both enhances interaction experiences for humans and uses human expertise to enhance AI performance.
Our research includes:
- human-system/robot interaction
- natural language processing
- machine listening
- human-agent collaboration
- citizen centric AI
Autonomous systems
This area of research involves looking at how systems evolve, learn and adapt enable us to better understand complex networks of individual actors. Our research in this area spans:
- evolutionary computation and evolutionary biology
- complex economic systems and social networks
- and complex multi-robot systems