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 ...
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...
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...
Simulating Dynamic Vehicle Routing Problems with Athos
Conference Proceeding
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019)
Simulating Dynamic Vehicle Routing Problems with Athos. In Proceedings of the 33rd International ECMS Conference on Modelling and Simulation ECMS 2019, (296-302). https://doi.org/10.7148/2019-0296
Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human ex...
Finding feasible timetables using group-based operators.
Journal Article
Lewis, R. M. R. & Paechter, B. (2007)
Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation. 11, 397-413. doi:10.1109/TEVC.2006.885162. ISSN 1089-778X
This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there a...
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