Constantin Berzan

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Laying out the network of power cables between wind turbines and substations incurs a significant cost when building a wind farm. For small farms, an expert can often identify a good layout by hand, or by simulating all the possible layouts. But for larger farms, these approaches are no longer applicable. We present some initial work towards automating the(More)
We present an improved estimation of distribution (EDA) genetic programming (GP) algorithm which does not rely upon a prototype tree. Instead of using a prototype tree, Operator-Free Genetic Programming learns the distribution of ancestor node chains, "n-grams", in a fit fraction of each generation's population. It then uses this information, via sampling,(More)
Previous experiments with low dimensional data sets have shown that Gabriel graph methods for instance-based learning are among the best machine learning algorithms for pattern classification applications. However, as the dimensionality of the data grows large, all data points in the training set tend to become Gabriel neighbors of each other, bringing the(More)
In 2012 a federal mandate was imposed that required the FAA to integrate unmanned aerial systems (UAS) into the national airspace (NAS) by 2015 for civilian and commercial use. A significant driver for the increasing popularity of these systems is the rise in open hardware and open software solutions which allow hobbyists to build small UAS at low cost and(More)
We propose graphical models as a new means of understanding genetic programming dynamics. Herein, we describe how to build an unbiased graphical model from a population of genetic programming trees. Graphical models both express information about the conditional dependency relations among a set of random variables and they support probabilistic inference(More)
Infrastructures for implementing agent architectures are currently unaware of what tasks the implemented agent is performing. Such knowledge would allow the infrastructure to improve the agent’s autonomy and reliability. For example, the infrastructure could detect abnormal system states, predict likely faults and take preventive measures ahead of time, or(More)
We work towards solving the Simultaneous Localization and Mapping (SLAM) problem using a Probabilistic Programming System (PPS). After surveying existing SLAM methods, we choose FastSLAM as the most promising candidate. FastSLAM uses ad-hoc methods for data association, and does not enforce mutual exclusion between observations arriving at the same(More)
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