Artificial Intelligence Research Group
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 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.
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