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Full-Text Articles in Physical Sciences and Mathematics
Attracting Human Attention Using Robotic Facial Expressions And Gestures, Venus Yu
Attracting Human Attention Using Robotic Facial Expressions And Gestures, Venus Yu
Honors Theses
Robots will soon interact with humans in settings outside of a lab. Since it will be likely that their bodies will not be as developed as their programming, they will not have the complex limbs needed to perform simple tasks. Thus they will need to seek human assistance by asking them for help appropriately. But how will these robots know how to act? This research will focus on the specific nonverbal behaviors a robot could use to attract someone’s attention and convince them to interact with the robot. In particular, it will need the correct facial expressions and gestures to …
Effective Ann Topologies For Use As Genotypes For Evaluating Design And Fabrication, John R. Peterson
Effective Ann Topologies For Use As Genotypes For Evaluating Design And Fabrication, John R. Peterson
Honors Theses
There is promise in the field of Evolutionary Design for systems that evolve not only what to manufacture but also how to manufacture it. EvoFab is a system that uses Genetic Algorithms to evolve Artificial Neural Networks (ANNs) which control a modified 3d-printer with the goal of automating some level of invention. ANNs are an obvious choice for use with a system like this as they are canonically evolvable encodings, and have been successfully used as evolved control systems in Evolutionary Robotics. However, there is little known about how the structural characteristics of an ANN affect the shapes that can …
An Alternative Approach To Training Sequence-To-Sequence Model For Machine Translation, Vivek Sah
An Alternative Approach To Training Sequence-To-Sequence Model For Machine Translation, Vivek Sah
Honors Theses
Machine translation is a widely researched topic in the field of Natural Language Processing and most recently, neural network models have been shown to be very effective at this task. The model, called sequence-to-sequence model, learns to map an input sequence in one language to a vector of fixed dimensionality and then map that vector to an output sequence in another language without any human intervention provided that there is enough training data. Focusing on English-French translation, in this paper, I present a way to simplify the learning process by replacing English input sentences by word-by-word translation of those sentences. …