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The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World

Conference Proceeding
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019)
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147
The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the ...

Use of machine learning techniques to model wind damage to forests

Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

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...

Idiotypic networks for evolutionary controllers in virtual creatures.

Conference Proceeding
Capodieci, N., Hart, E., & Cabri, G. (2014)
Idiotypic networks for evolutionary controllers in virtual creatures. In H. Sayama, J. Rieffel, S. Risi, R. Doursat, & H. Lipson (Eds.), Artificial Life 14: Proceedings of ALife, 14th International Conference on the Synthesis and Simulation of Living Systems, (192-199). https://doi.org/10.7551/978-0-262-32621-6-ch032
We propose a novel method for evolving adaptive locomotive strategies for virtual limbless creatures that addresses both functional and non-functional requirements, respective...

Artificial Immune System driven evolution in Swarm Chemistry.

Conference Proceeding
Capodieci, N., Hart, E., & Cabri, G. (2014)
Artificial Immune System driven evolution in Swarm Chemistry. In Proceedings of IEEE SASO 2014, (40-49). https://doi.org/10.1109/SASO.2014.16
Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behavio...

Exploiting the analogy between immunology and sparse distributed memory.

Conference Proceeding
Hart, E., & Ross, P. (2001)
Exploiting the analogy between immunology and sparse distributed memory. In J. Timmis, & P. J. Bentley (Eds.), ICARIS 2002 : 1st International Conference on Artificial Immune Systems, 59-67
The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for...

Clustering Moving Data with a Modified Immune Algorithm

Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...

An immune system approach to scheduling in changing environments.

Conference Proceeding
Hart, E., & Ross, P. (1998)
An immune system approach to scheduling in changing environments. In W. Banzhaf, J. M. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, & R. E. Smith (Eds.), GECCO-99 : proceedings of the genetic and evolutionary computation conference. Volume 2, 1559-1566
This paper describes the application of an artificial immune system, (AIS), model to a scheduling application, in which sudden changes in the scheduling environment require th...