Research explorer tool

6 results

Learning to solve bin packing problems with an immune inspired hyper-heuristic.

Conference Proceeding
Sim, K., Hart, E., & Paechter, B. (2013)
Learning to solve bin packing problems with an immune inspired hyper-heuristic. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL 2013, 856-863. https://doi.org/10.7551/978-0-262-31709-2-ch126
Motivated by the natural immune system's ability to defend the body by generating and maintaining a repertoire of antibodies that collectively cover the potential pathogen spa...

Towards self-aware PerAda systems.

Conference Proceeding
Hart, E., & Paechter, B. (2010)
Towards self-aware PerAda systems. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010 Proceedings, 314-216. https://doi.org/10.1007/978-3-642-14547-6_28
Pervasive Adaptation (PerAda) refers to massive-scale pervasive information and communication systems which are capable of autonomously adapting to highly dynamic and open tec...

Revisiting the Central and Peripheral Immune System

Conference Proceeding
McEwan, C., Hart, E., & Paechter, B. (2006)
Revisiting the Central and Peripheral Immune System. In Artificial Immune Systems. ICARIS 2007, 240-251. doi:10.1007/978-3-540-73922-7_21
The idiotypic network has a long and chequered history in both theoretical immunology and Artificial Immune Systems. In terms of the latter, the drive for engineering applicat...

A Lifelong Learning Hyper-heuristic Method for Bin Packing.

Journal Article
Hart, E., Sim, K., & Paechter, B. (2015)
A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121
We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics ...

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication.

Conference Proceeding
Hart, E., Steyven, A., & Paechter, B. (2015)
Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15, (169-176). https://doi.org/10.1145/2739480.2754688
Ensuring the integrity of a robot swarm in terms of maintaining a stable population of functioning robots over long periods of time is a mandatory prerequisite for building mo...

The Cost of Communication: Environmental Pressure and Survivability in mEDEA

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2015)
The Cost of Communication: Environmental Pressure and Survivability in mEDEA. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15, 1239-1240. doi:10.1145/2739482.2768489
We augment the mEDEA algorithm to explicitly account for the costs of communication between robots. Experimental results show that adding a costs for communication exerts envi...