A new module has appeared on the University of Manchester CS horizon, and it’s temping me away from wrapping up the taught course with my previous front-runner ‘Ontology Engineering for the Semantic Web‘.
Yep, COMP61032 ‘Optimization for Learning, Planning and Problem Solving‘ has appeared in my field of vision and it looks a bit hardcore. It’s part of the ‘Learning from Data’ theme – I guess optimisation is a natural partner to machine learning approaches, owing to the need to chew up a whole lot of information as quickly as possible.
Why is it tempting? Lots of algorithms and computational complexity going on – it’s one of those modules that’s shouting “Bet you can’t pass me”. More than that though, it’s modules with that computational theory slant that have shown me moments of catch-your-breath clarity in the way that messy practicality distils to elegant mathematical beauty. It’s a great sense of satisfaction when you persevere and get to see it.
So – Ontology engineering, or Optimisation? Hey, I warned you it was geeky.
Optimization for learning, planning and problem-solving
crossedstreams.com 