Outputs (2)

Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples (2024)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2024, July). Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples. Presented at GECCO 2024, Melbourne, Australia

The choice of input-data used to train algorithm-selection models is recognised as being a critical part of the model success. Recently, feature-free methods for algorithm-selection that use short trajec-tories obtained from running a solver as input... Read More about Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples.

Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism (2018)
Presentation / Conference Contribution
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018, July). Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. Presented at The 2018 Conference on Artificial Life, Tokyo, Japan

Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders' decisions by aggregating their own and their neighbours' experience, and i... Read More about Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism.