Peake, J., Amos, M., Costen, N., Masala, G. & LLoyd, H. (2022) PACO-VMP: Parallel Ant Colony Optimization for
Virtual Machine Placement. Future Generation Computer Systems 129, 174-186. doi:10.1016/j.future.2021.11.019.
Lloyd, H., Crossley, M., Sinclair, M. & Amos, M. (2022) J-POP: Japanese Puzzles as Optimization Problems.
IEEE Transactions on Games 14:3, 391-402. doi: 10.1109/TG.2021.3081817.
Lloyd, H. & Amos, M. (2020) Solving Sudoku with Ant Colony Optimization. IEEE Transactions on Games 12:3, p.p. 302-311.
doi: 10.1109/TG.2019.2942773.
Peake, J., Amos, M., Yiapanis, P. & Lloyd, H. (2019) Scaling techniques for parallel Ant Colony Optimization on large problem instances. Proc.
Genetic and Evolutionary Computation Conference (GECCO), Prague, July 13th-17th 2019, pp. 47-54. doi: 10.1145/3321707.3321832.
Amos, M., Crossley, M. & Lloyd, H. (2019) Solving Nurikabe using Ant Colony Optimization. Genetic and Evolutionary Computation Conference (GECCO) Companion, Prague,
July 13th-17th 2019, pp. 129-130. doi: 10.1145/3319619.3338470.
(An extended version of this paper, containing further details of the algorithm and experimental results, is available
here, but the GECCO paper is the "official" version.)
Eliot, N., Kendall, D., Moon, A., Brockway, M. & Amos, M. (2019) Void reduction in self-healing swarms. Proc. Conference on Artificial Life (ALIFE), Newcastle upon Tyne,
July 29-August 2 2019, pp. 87-94. doi: 10.1162/isal_a_00146.
Peake, J., Amos, M., Yiapanis, P. & Lloyd, H. (2018).
Vectorized candidate selection for parallel ant colony optimization.
Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan,
pp. 1300-1306. doi: 10.1145/3205651.3208274.
Lloyd, H. & Amos, M. (2017). Analysis of independent roulette selection in parallel ant colony optimization.
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '17), July 15-19 2017, Berlin, Germany, pp. 19-26. doi: 10.1145/3071178.3071308.
(nominated for a Best Paper Award).
Richards, D. & Amos, M. (2016c). Shape optimization with surface-mapped CPPNs. IEEE Transactions
on Evolutionary Computation 21:3, 391-407. doi: 10.1109/TEVC.2016.2606040.
LLanes, A., Cecilia, J., Sanchez, A., Garcia, J.M., Amos, M. & Ujaldon, M. (2016). Dynamic load balancing
on heterogenous clusters for parallel ant colony optimization. Cluster Computing 19:1, 1-11.
doi: 10.1007/s10586-016-0534-4.
LLoyd, H. & Amos, M. (2016). A highly parallelized and vectorized implementation of Max-Min Ant System on Intel Xeon Phi.
IEEE Symposium Series on Computational Intelligence (SSCI), December 6-9 2016, Athens, Greece. doi: 10.1109/SSCI.2016.7850085.
Richards, D. & Amos, M. (2016b). Regulatory representations in architectural design.
In Iba, H. & Noman, N. (Eds.),
Evolutionary Computation in Gene
Regulatory Network Research, pp. 362-397, Wiley.
Richards, D. & Amos, M. (2016a). Encoding multi-materiality. In Grigoriadis, K. (Ed.), Mixed Matter: A Multi-Material Design Compendium, pp. 40-49, Jovis.
Guerrero, G.D., Cecilia, J.M., Llanes, A., Garcia, J.M.,
Amos, M. & Ujaldon, M. (2014)
Comparative evaluation of platforms for parallel Ant Colony
Optimization. Journal of Supercomputing 69:1, 318-329. doi: 10.1007/s11227-014-1154-5.
Richards, D. & Amos, M. (2014a)
Evolving morphologies with CPPN-NEAT and a dynamic substrate. In
Proceedings of ALIFE 14, the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, July 30-August 2, 2014, New York, USA.
Edited by Hiroki Sayama, John Rieffel, Sebastian Risi, René Doursat and Hod Lipson, p.p. 255-262, MIT Press. doi: 10.7551/978-0-262-32621-6-ch042.
Richards, D. & Amos, M. (2014b)
Designing with gradients: bio-inspired computation for digital fabrication. In Proceedings of
the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA 14: Design Agency), October 23-25, 2014,
University of Southern California, Los Angeles, USA, p.p. 101-110.
Cecilia, J.M., Nisbet, A., Amos, M., Garcia, J.M. & Ujaldon, M. (2013) Enhancing GPU parallelism in
nature-inspired algorithms. Journal of Supercomputing 63:3, p.p. 773-789. doi:10.1007/s11227-012-0770-1.
Cecilia, J.M., Garcia, J.M., Nisbet, A., Amos, M. & Ujaldon, M. (2013) Enhancing data
parallelism for ant colony optimisation on GPUs. Journal of Parallel and
Distributed Computing 73:1, p.p. 42-51. doi:10.1016/j.jpdc.2012.01.002.
Crossley, M., Nisbet, A. & Amos, M. (2013)
Quantifying the impact of parameter tuning on nature-inspired algorithms.
In Advances in Artificial Life, ECAL2013,
September 2-6, 2013, Taormina, Italy, p.p. 925-932. MIT Press.doi: 10.7551/978-0-262-31709-2-ch138
Crossley, M., Nisbet, A. & Amos, M. (2013) Fitness landscape-based characterisation of nature-inspired algorithms.
In Proceedings of the 11th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA’13),
Lausanne, Switzerland, April 4-6, 2013. Tomassini, M., Antonioni, A., Daolio, F. & Buesser, P. (Eds.) Lecture
Notes in Computer Science (LNCS), Volume 7824, p.p. 110-119, Springer.
Amos, M. & Coldridge, J. (2012) A genetic algorithm for the Zen Puzzle Garden game.
Natural Computing 11:3, p.p. 353-359. doi:10.1007/s11047-011-9284-7.
Richards, D., Dunn, N. & Amos, M. (2012) An evo-devo approach to architectural design.
Proc. Genetic and Evolutionary Computation Conference (GECCO), July 7-11 2012, Philadelphia, USA, p.p.
569-576. ACM Press.
Crossley, M. & Amos, M. (2011) SimZombie: a case-study in agent-based simulation construction.
In Agent and Multi-Agent Systems: Technologies and Applications,
Lecture Notes in Artificial Intelligence (LNAI) Vol. 6682, Springer, 2011, p.p. 514-523. doi:10.1007/978-3-642-22000-5_53.
Cecilia, J.M., Garcia, J.M, Ujaldon, M., Nisbet, A. & Amos, M. (2011) Parallelization strategies for ant colony optimization
on GPUs. Proceedings of the 25th IEEE/ACM International Parallel and Distributed Processing Symposium (IPDPS 2011),
Anchorage, Alaska, USA, 16-20 May 2011, p.p. 334-341.
Coldridge, J. & Amos, M. (2010) Genetic algorithms and the art of Zen. Proceedings of the
IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA),
p.p. 1417-1423. doi: 10.1109/BICTA.2010.5645284.
Amos, M. & Don, O. (2008) Swarm-based spatial sorting.
International Journal of Intelligent Computing and Cybernetics 1:3, p.p. 454-473. doi: 10.1108/17563780810893491.
Xiao, R-B., Xu, Y-C. & Amos, M. (2007) Two hybrid compaction algorithms for the layout optimization problem.
BioSystems 90:2, p.p. 560--567. doi: 10.1016/j.biosystems.2006.12.007.
Amos, M. & Don, O. (2007) An ant-based algorithm for annular sorting.
Proc. IEEE Congress on Evolutionary Computation (CEC'07), Singapore, September 25-28, 2007, p.p.
142-148, IEEE Press.
Xu, Y-C., Xiao, R-B. & Amos, M. (2007) A novel genetic algorithm for the layout
optimization problem. Proc. IEEE Congress on Evolutionary Computation (CEC'07), Singapore,
September 25-28, 2007, p.p. 3938-3942, IEEE Press.
Xu, Y-C., Xiao, R-B. & Amos, M. (2007a) Particle swarm algorithm for weighted rectangle
placement. Proc. Third International Conference on Natural Computation (ICNC'07), Haikou, China,
August 24-27, 2007, Volume 4, p.p. 728-732, IEEE Press.
Timmis, J., Amos, M., Banzhaf, W. & Tyrrell, A. (2006) "Going back to our roots":
Second generation biocomputing. International Journal of Unconventional Computing 2:4,
p.p. 349-378.
Devine, P., Paton, R. & Amos, M. (1997)
Adaptation of evolutionary agents in
computational ecologies. Proc. Bio-computing and Emergent Computation (BCEC97), University of
Skovde, Sweden, 1-2 Sep. 1997. Lundh, Olsson & Narayanan (Eds.) p.p. 66-75, World Scientific.
