Sam Kriegman

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Different subsystems of organisms adapt over many time scales, such as rapid changes in the nervous system (learning), slower morphological and neurological change over the lifetime of the organism (postnatal development), and change over many generations (evolution). Much work has focused on instantiating learning or evolution in robots, but relatively(More)
Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the machine learning process, yielding regional model(More)
In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties,(More)
In evolutionary robotics, evolutionary methods are used to optimize robots to different tasks. Because using physical robots is costly in terms of both time and money, simulated robots are generally used instead. Most physics engines are written in C++ which can be a barrier for new programmers. In this paper we present two Python wrappers, Pyrosim and(More)
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