AI Article Synopsis
- The paper differentiates between algorithm performance (how well the algorithm works in practice) and algorithm competence (the range of problems it can theoretically address).
- The authors analyze a bio-inspired collective construction algorithm based on paper wasp behavior, highlighting its theoretical capabilities while pointing out its practical performance limitations.
- They enhance this algorithm by incorporating pheromone-mediated behavior from termites, leading to a new hybrid called the waspmite algorithm that maintains generality but shows better performance and scalability.
Article Abstract
We introduce a distinction between algorithm performance and algorithm competence and argue that bio-inspired computing should characterize the former rather than the latter. To exemplify this, we explore and extend a bio-inspired algorithm for collective construction influenced by paper wasp behavior. Despite its being provably general in its competence, we demonstrate limitations on the algorithm's performance. We explain these limitations, and extend the algorithm to include pheromone-mediated behavior typical of termites. The resulting hybrid waspmite algorithm shares the generality of the original wasp algorithm, but exhibits improved performance and scalability.
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| http://dx.doi.org/10.1162/artl_a_00065 | DOI Listing |
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