SICSA CSE: Self-Adaptive Autonomous Bio-Inspired Systems Workshop Series (SEABIS)

Date/Time
Date(s) - 17/09/2013
All Day

Location
IET Glasgow Teacher Building, Glasgow, G1 4DB


Workshop organised by Emma Hart e.hart@napier.ac.uk
Register @ http://seabis-edinburgh.eventbrite.com

All SEABIS researchers are warmly invited to attend the third in the series of three workshops in the SEABIS subtheme. Each workshop will consist of a keynote talk, a poster session presenting current ideas from SEABIS researchers and a panel session discussion on research trends in SEABIS areas.

We invite posters for this workshop. PhD students are particularly welcome to contribute. We welcome posters outline work-in-progress, position statements and new ideas as well as those presenting more detailed results.

All topics in the SEABIS scope are relevant including, but not limited to: Evolutionary algorithms, Hyper-heuristics, Self-adaptive Systems, Machine Learning, Particle Swarm Optimisation, Ant Colony Optimisation, Artificial Immune Systems, Artificial Life, Theory and Applications, Swarm Robotics.

PROGRAMME
12:30 – 13.30 Lunch available
13.30-14.30 Dr William Langdon, University College London: Genetic Improvement Programming
14:30 – 15:30 Poster Session (coffee available)
15:30 – 15:45 Refreshment Break
15:45 – 16:45 Panel Discussion: “Bridging the Gap: Bio-Inspired Computing in the Real World”
17:00 CLOSE

Please send a brief email to Emma Hart e.hart@napier.ac.uk if you intend to bring a poster so we can provide sufficient poster boards.

Invited Speaker:
Title: Genetic Improvement Programming

Abstract
Genetic programming can optimise software, including:
evolving test benchmarks, generating protocols, composing web services, generating improved hashing and garbage collection algorithms, redundant programming, and even automatically fixing bugs. There may be many ways to balance functionality with resource consumption (such as time, memory, energy). Human programmers cannot try them all. Also the Pareto optimal trade off may be different on each hardware platform and dynamic, e.g. changes in user behaviour or business expectations. It may be genetic programming can automatically suggest different trade offs for each new market. Recent results include substantial speed up by evolving a new version of a program customised for a special case.

Biography: W. B. Langdon was research officer for the Central Electricity Research Laboratories and project manager and technical coordinator for Logica before becoming a prolific, internationally recognised researcher (working at UCL, Birmingham, CWI and Essex). He has written two books, edited six more, and published over 80 papers in international conferences and journals. He is the resource review editor for Genetic Programming and Evolvable Machines and a member of the editorial board of Evolutionary Computation. He has been a co-organiser of eight international conferences and workshops, and has given nine tutorials at international conferences. He was elected ISGEC Fellow for his contributions to EC. Dr Langdon has extensive experience designing and implementing GP systems, and is a leader in both the empirical and theoretical analysis of evolutionary systems. He also has broad experience both in industry and academic settings in biomedical engineering, drug design, and bioinformatics.

Panel Discussion: Bridging the Gap: Bio-Inspired Computing in the Real World (suggestions only):
• Is there a gap between the research undertaken by academics and the
problems people care about in the real world?
• (if so) What steps can we take to alleviate this?
• What are the current barriers to uptake of our research by industry?
• What do we need to do to convince more people to use our algorithms?
• What kind of real-world problems should we be tackling?
• What kind of benchmarks should we be using to test and evaluate our
algorithms?

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