NCRA researchers David Lynch, David Fagan and Michael O’Neill, along with their collaborators from Nokia Bell Labs (Holger Claussen and Stepan Kucera), and NCRA alumnus Michael Fenton, have won the 2019 HUMIES Gold Award for a result demonstrating Human Competitive Artificial Intelligence using Evolutionary Computation. The underlying research was published recently in the leading journal in wireless communications networks and demonstrates a doubling to tripling of data rates on cellular networks. The HUMIES Gold Award was presented at the ACM GECCO Conference in Prague on 17 July 2019.
This is the second occasion that NCRA research has been recognised in the HUMIES. In 2017 their research on Innovative Truss Design using Grammatical Evolution won the HUMIES Bronze Award.
A collaboration between the UCD Natural Computing Research and Applications Group and STATSports has resulted in a journal publication introducing a novel method for mathematically optimising team sport training models using evolutionary computation.
Congratulations to Prof Michael O’Neill who was awarded the Lero Director’s Prize for Research Excellence 2021. The annual awards recognise the enormous commitment and contribution of Lero members to the research centre’s success.
On receiving the award Prof O’Neill said “Thank You to Lero, and thank you to everyone who contributed to our shared research success these 20+ years, especially all past and present members of the UCD Natural Computing Research and Applications Group, especially Tony Brabazon, the UCD School of Business, UCD School of Computer Science, UL School of Computer Science and Information Systems, and co-inventors of Grammatical Evolution, Conor Ryan and J.J. Collins who are joint winners of this award“.
10 years on from hosting GECCO 2011 in Dublin, Ireland, Mark Connor and Michael O’Neill presented an approach to optimising the Banister Dose-Response Fitness-Fatique model used in athlete training management (arxiv draft) at GECCO 2021…
Do you use the Banister Dose-Response/ Fitness-Fatigue Model? Well, chances are you might have been using it wrong all this time… we’ve just published some new research, so let’s talk ‘Parameters’ pic.twitter.com/AlNhk9Xbc5
Michael presented an invited talk on “Grammars, Evolutionary Computation and Intepretability” in a special session on Grammatical Evolution at DSSV-ECDA 2021 (7-9 July, 2021). The session was organised by Andreas Geyer-Schulz who spoke on “Architectural Design of a Unified GA/GP Package for R”, and Franz Rothlauf gave a talk on “Program Synthesis with Grammatical Evolution”.
Handcrafting mixed-integer linear programming (MILP) models can be a time-consuming and error-prone task. A novel algorithm, Grammatical Evolution for Constraint Synthesis (GECS), has been proposed which produces well-formed MILP models in the ZIMPL modelling language. GECS outperform state-of-the-art algorithms, and appears resistant to the curse of dimensionality. The research collaboration between Dr Tomasz Pawlak (Poznan University of Technology) and Prof Michael O’Neill (UCD Natural Computing Research & Applications Group) has been published in the journal Swarm and Evolutionary Computation.
Stefano Mauceri and co-authors (James Sweeney, Miguel Nicolau and James McDermott) have published their latest research on a data-driven approach to feature extraction from time series for one-class classification in the journal Genetic Programming & Evolvable Machines. The approach, which uses Grammatical Evolution to automatically select both the features to extract and the sub-sequences from which to extract them, is demonstrated to lead to problem understanding and improved performance.
David Lynch and Michael O’Neill with NCRA alumnus James McDermott have been nominated for the Best Paper Award at the PPSN 2020 conference to be held in Leiden in September. The paper brings together the use of grammars and autoencoders in a novel approach to program synthesis.
Lynch D., McDermott J., O’Neill M. (2020). Program Synthesis in a Continuous Space using Grammars and Variational Autoencoders. The Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN XVI). Springer LNCS.
Miguel Nicolau with NCRA alumnus Alexandros Agapitos have published their latest research on function sets, generalisation and symbolic regression in the Genetic Programming & Evolvable Machines journal.
Nicolau, M., Agapitos, A. (2020). Choosing function sets with better generalisation performance for symbolic regression models. Genetic Programming and Evolvable Machines. https://doi.org/10.1007/s10710-020-09391-4
NCRA researchers (Róisín Loughran, Tony Brabazon and Michael O’Neill) have published three articles in the 20th Anniversary issue of the journal Genetic Programming & Evolvable Machines. Two articles provide an overview of research in application areas we have been focusing on as a group for sometime, Finance & Economics (https://rdcu.be/b4KkQ), and Computational Creativity (https://rdcu.be/b4KkT). The third article, “Automatic Programming: The Open Issue?” (https://rdcu.be/b4KkV) follows on from an article by O’Neill et al that appeared in the 10th Anniversary issue highlighting Open Issues in the field of GP, and raises a challenge to the community to re-ignite a focus on Automatic Programming, the open issue, which we previously referred to as the “elephant in the room”.