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Browsing Mathematics and Computer Science Faculty Research by Subject "Bio-inspired approaches"

Browsing Mathematics and Computer Science Faculty Research by Subject "Bio-inspired approaches"

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  • Schrum, Jacob; Rollins, Alex C. (GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017-07)
    Previous research using evolutionary computation in Multi-Agent Systems indicates that assigning fitness based on team vs. individual behavior has a strong impact on the ability of evolved teams of artificial agents to ...
  • Schrum, Jacob; Gillespie, Lauren E.; Gonzalez, Gabriela R. (Proceedings of the Genetic and Evolutionary Computation Conference, 2017-07)
    Intelligent agents have a wide range of applications in robotics, video games, and computer simulations. However, fully general agents should function with as little human guidance as possible. Specifically, agents should ...
  • Schrum, Jacob; McDonnell, Tyler; Andoni, Sari; Bonab, Elmira; Cheng, Sheila; Goode, Jimmie; Moore, Keith; Sellers, Gavin; Choi, Jun-Hwan (GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference, 2018-07)
    Neuroevolution is a powerful and general technique for evolving the structure and weights of artificial neural networks. Though neuroevolutionary approaches such as NeuroEvolution of Augmenting Topologies (NEAT) have been ...
  • Schrum, Jacob (Proceedings of the Genetic and Evolutionary Computation Conference, 2018-07)
    Tetris is a challenging puzzle game that has received much attention from the AI community, but much of this work relies on intelligent high-level features. Recently, agents played the game using low-level features (10 X ...
  • Schrum, Jacob; Volz, Vanessa; Lucas, Simon M.; Smith, Adam; Liu, Jialin; Risi, Sebastian (Proceedings of the Genetic and Evolutionary Computation Conference, 2018-07)
    Generative Adversarial Networks (GANs) are a machine learning approach capable of generating novel example outputs across a space of provided training examples. Procedural Content Generation (PCG) of levels for video games ...
  • Schrum, Jacob; Tweraser, Isabel; Gillespie, Lauren E. (Proceedings of the Genetic and Evolutionary Computation Conference, 2018-07)
    Compositional Pattern Producing Networks (CPPNs) are a generative encoding that has been used to evolve a variety of novel artifacts, such as 2D images, 3D shapes, audio timbres, soft robots, and neural networks. This paper ...

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