Simulating Football Players’ Decision-Making Process

The goal of this project was to build an assistive tool that could help Football coaches to simulate the actions of an “optimally behaving” defensive team. We developed a cost function that optimizes both Pitch Control and Pass Interceptions for the defensive team.

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Learning Where to Park by Active Inference

In order to assess the feasibility of active inference as a framework for synthetic agents in a real-world setting, we developed a ground-based robot that needs to learn to navigate to an undisclosed parking location. The robot can only learn where to park through situated interactions with a human observer who is aware of the target location.

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ForneyLab: a Julia Toolbox for Factor Graph-Based Probabilistic Programming

ForneyLab is a novel Julia package that allows the user to specify a probabilistic model as an FFG and pose inference problems on this FFG. ForneyLab is especially potent when applied to time-series data, where it attains comparable performance to Stan and Edward in significantly less computation time.

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