An Active Inference approach to the multi-agent lost target search problem
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2022-03-11
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en
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Abstract
Active Inference is nowadays more often used in a search-related environ-
ment, thus this research tests whether it is as e ective as other algorithms
such as a No Detection algorithm. This is tested in a 10 by 10 grid, where
it tries to nd a target most optimally by minimizing the Variational Free
Energy (VFE) and Expected Free Energy (EFE). Bayesian Inference will be
applied to solve these minimization problems. The agent uses a momentum-
cone in order to choose the most optimal action. Results show a de cit in
information gain for the Active Inference compared to the No Detection
algorithm. This could be due to an error made in computing the VFE
for the agent, as well as an optimization error in the computation for the
momentum-cone. Further research can be helpful in nding whether xing
these errors will improve the algorithm.
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Faculteit der Sociale Wetenschappen