Artificial Intelligence Research Group

Brain image on a circuit board © Shutterstock

What is the AI research group?

The AI research group is interested in a variety of algorithms that mimic aspects of human intelligence or other biological systems. This includes:

  • Machine learning (including statistical learning and connectionism)
  • Biologically-inspired computation
  • Artificial life (in particular open-ended evolution)
  • Combinatorial search (in particular meta-heuristic and hyper-heuristic approaches)

For more information on the UC AI Research Group please visit their website.

The courses that relate to the Artificial Intelligence Research Group are:

The main contributing members of the Artificial Intelligence Research Group can be seen below:

  • Kourosh Neshatian: machine learning
  • Thomas Young: computational open-ended evolution, emergence, and complexity
  • Shinichi Yamada [PhD candidate]: model and variable selection through statistical learning and support vector machines
  • Hayden Jackson [MSc 2015-2016]: Learning in Spiking Artificial Neural Networks
  • Andy Bell [Honours 2016]: Mary had a little lambda: implementing a minimal lisp for assisting with education
  • Dillon George [Honours 2016]: Statistical BSP trees for density estimation
  • Aaron Stockdill [Honours 2016]: Neuromorphic Computing with Reservoir Neural Networks on Memristive Hardware
  • Jonathan Avery [Honours 2015]: Developing a similarity measure for Python programs
  • Cain Cresswell-Miley [Honours 2014]: Parallel swarm optimization and learning
  • Jill de Jong [research assistance 2012--2013]: Automatic construction of cost-sensitive discriminant functions
  • Barry Kanigel [research assistance 2012--2013]: Ensemble learning, boosting

ToyWorld is an artificial chemistry system developed for simulation of open-ended evolution.

For advice

Kourosh Neshatian

Senior Lecturer Above the Bar
Jack Erskine 212
Internal Phone: 92455

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