10 results

Algorithm selection using deep learning without feature extraction

Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...

Optimising an evolutionary algorithm for scheduling

Conference Proceeding
Urquhart, N. B., Chisholm, K., & Paechter, B. (2000)
Optimising an evolutionary algorithm for scheduling. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Proceedings. , (307-318). https://doi.org/10.1007/3-540-45561-2_30
This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. ...

Street-based routing using an evolutionary algorithm

Conference Proceeding
Urquhart, N. B., Paechter, B., & Chisholm, K. (2001)
Street-based routing using an evolutionary algorithm. In E. J. W. Boers, J. Gottlieb, P. L. Lanzi, R. E. Smith, S. Cagnoni, E. Hart, …H. Tijink (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Proceedings. , (495-504). https://doi.org/10.1007/3-540-45365-2_51
Much research has been carried out into solving routing problems using both Evolutionary Techniques and other methods. In this paper the authors investigate the usage of an Ev...

Improving street based routing using building block mutations.

Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Improving street based routing using building block mutations. In J. Gottlieb, E. Hart, & S. Cagnoni (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN Kinsale, Ireland, April 3–4, 2002 Proceedings. , (189-202). https://doi.org/10.1007/3-540-46004-7_33
Street based routing (SBR) is a real-world inspired routing problem that builds routes within an urban area for mail deliveries. The authors have previously attempted to solve...

A role for immunology in 'next generation' robots.

Conference Proceeding
Hart, E., Ross, P., Webb, A., & Lawson, A. (2003)
A role for immunology in 'next generation' robots. In J. Timmis, P. Bentley, & E. Hart (Eds.), Artificial Immune Systems. ICARIS 2003, 46-56. https://doi.org/10.1007/978-3-540-45192-1_5
Much of current robot research is about learning tasks in which the task to be achieved is pre-specified, a suitable technology for the task is chosen and the learning process...

A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution.

Conference Proceeding
Sim, K., Hart, E., & Paechter, B. (2012)
A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution. In Parallel Problem Solving from Nature: PPSN XII, (348-357). https://doi.org/10.1007/978-3-642-32964-7_35
A hyper-heuristic for the one dimensional bin packing problem is presented that uses an Evolutionary Algorithm (EA) to evolve a set of attributes that characterise a problem i...

Controlling a simulated Khepera with an XCS classifier system with memory.

Conference Proceeding
Webb, A., Hart, E., Ross, P. & Lawson, A. (2003)
Controlling a simulated Khepera with an XCS classifier system with memory. ISBN 9783540200574
Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of act...

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems.

Conference Proceeding
Ross, P., Schulenburg, S., Marin-Blazquez, J. G. & Hart, E. (2002)
Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. ISBN 1558608788
Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They...

Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics.

Conference Proceeding
Ross, P., Marin-Blazquez, J. G., Schulenburg, S. & Hart, E. (2003)
Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics
The idea underlying hyper-heuristics is to discover some combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be wo...

Requirements for getting a robot to grow up.

Conference Proceeding
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P. & Morgavi, G. (2003)
Requirements for getting a robot to grow up. ISBN 9783540200574