We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitne...

| Delta coding is an iterative genetic search strategy that sustains search by periodically re-initializing the population. This helps to avoid premature convergence during genetic search. Delta coding also remaps hyper-space with each iteration in an attempt to locate \easier" search spaces with respect to genetic search. Here, the optimization ability of delta coding is compared against the C...

We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples the joint probability distribution of triplets of instructions (or 3-grams) at the same time as it is learning and sampling a program length distribution. We have tested N-gram GP on symbolic regressions problems where the target function is a polynomial ...

In this study, we developed an appropriate calorie tracking algorithm for children and compared it with the current commercial product. The results of the developed algorithm showed 94.2% accuracy in the classification of intermittent activities: sitting down, standing up, turning around and jumping; and 92.9% accuracy in the classification of continuous activities: walking, running, stair clim...

Combinations of metaheuristics to solve highly constrained combinatorial optimisation problems have recently become a promising research area. Some combinations emerge from integrating evolutionary algorithms and local based algorithms to strike the right balance between global exploration of the search region and local exploitation of promising regions. This study presents hybridization betwee...

Classification Association Rule Mining (CARM) systems operate by applying an Association Rule Mining (ARM) method to obtain classification rules from a training set of previously-classified data. The rules thus generated will be influenced by the choice of ARM parameters employed by the algorithm (typically support and confidence threshold values). In this paper we examine the effect that this ...

We present a hill-climbing algorithm to solve planning problems with temporal uncertainty. First an optimistic plan that is valid when all actions complete quickly is found. Then temporal reasoning techniques are used to determine when the plan may fail. At time points that cause an unsafe situation, contingency branches are inserted. We describe our planner PHOCUS-HC, give preliminary results,...