Projects

Co-adaptive learning systems involve decomposition by definition:  concurrent learning algorithms working on different aspects of a problem, game, or simulation imply (explicitly or implicitly) a division in representation of some kind.  For many such systems, this partitioning is performed explicitly and a priori (e.g., traditional compositional co-evolutionary approaches). The representational issues surrounding how to choose…

Along with the Adaptive Systems section at the NCARAI and the Distributed Robotics lab at the University of Wyoming, we have been involved in developing a principled method for constructing modular, heterogeneous swarms.  The NCCS lab uses this method for developing high-level modular designs of multi-agent teams. The method generalizes Dr. Spears’ artificial physics based…

Once humans are a part of a multi-agent team, many issues become much more complex.  Machine learning methods for multi-agent systems typically employ simulations for some portion of the learning process; however, in mixed-agent teams (teams with both humans and machine agents) simulated agents will not simply include those over which learning methods have control…

Human cognition can be viewed as a non-linear dynamical system receiving inputs and produces outputs that vary over time. Chaos theory describes the behavior of certain non-linear dynamic systems that may appear to proceed according to chance even though their behavior is determined by precise laws and is highly sensitive to initial conditions.  Tom Clarke…