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Agents, Interaction and Complexity

About us

We investigate the theory behind safe, verifiable, and trustworthy autonomous systems. Our work looks at their use from smart cities to disaster response.

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