Imitation of honey bees' concept learning processes using Vector Symbolic Architectures

The system is showcased through the functional imitation of concept learning in honey bees. Data from real-world experiments with honey bees (Avarguès-Weber et al., 2012) are used for benchmarking. It is demonstrated that the proposed pipeline features a similar learning curve and accuracy of generalization to that observed for the living bees. The main claim of this article is that there is a class of simple artificial systems that reproduce the learning behaviors of certain living organisms without requiring the implementation of computationally intensive cognitive architectures. Consequently, it is possible in some cases to implement rather advanced cognitive behavior using simple techniques.