Collective Exploration / Search

2011–2013  |  ongoing 

Early in my PhD, I conducted a series of experiments to examine how groups of fish navigate complex environments, using schools of Golden Shiners.

Groups of fish were trained to the general location of a food reward in an empty tank, then I inserted a complex labyrinth into the tank, so they needed to explore to find a path to the reward. I tested different group sizes and compositions to see which performed best.


After groups learned to associate the location of the purple ring (above) with a consistent food reward, a novel complex environment was introduced into the tank, and the performance of different group sizes was assessed in this collective search task. Preliminary results suggested that intermediate-sized groups seemed to perform better than much larger or smaller groups.

I hope to continue this work in the future, expanding on these preliminary experiments along with theoretical work using an approach combining deep multi-agent reinforcement learning and game theory to assess when schools stay together, and under what conditions individuals tend to split off, either alone or in subgroups. I am curious to examine the potential role of free riders in the fission/fusion dynamics seen in these experiments, and whether there are consistent strategies that emerge within groups in terms of exploration and exploitation (following).

A consistent strategy of following the crowd could allow some individuals to devote their attention to close observation of the environment, which may ultimately lead to their discovering novel routes, and their sudden departure from the group as they speed towards a (possible) reward. In addition to these questions regarding individual strategies and inter-group dynamics, I am also interested in analyzing this process of group exploration as a multi-agent form of Novelty Search, which may provide insights for the design of AI systems focused on collective search (either physical or virtual).

Algorithmic Design Research

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North Atlantic Server Farm

The North Atlantic Server Farm (NSAF) was a speculative proposal for a free-floating archipelago of autonomous robotic swimming, wave-powered, and seawater-cooled server units, linked together at hubs with undersea cable connections. The network would be constantly growing to keep up with computing needs, and as it scales, the reflectivity of its white surfaces could begin to offset the reduced albedo of Earth from the melting of polar sea ice. Developed as Lutz/Koltick in collaboration with Nicole Koltick, and presented at the symposium INPUT-OUTPUT: Adaptive Materials and Mediated Environments at Temple University in 2010.

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