We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
It is challenging to support the timeliness of realtime data service requests in data-intensive real-time applications such as online auction or stock trading, while maintaining t...
Abstract. We study the problem of dynamic load-balancing on hierarchical platforms. In particular, we consider applications involving heavy communications on a distributed platform...
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
We show how and why using genetic operators that are applied with probabilities that depend on the fitness rank of a genotype or phenotype offers a robust alternative to the Sim...