ASSISIbf / University of Graz (AT), Universite Paris Diderot (FR), Ecole Polytechnique Federale de Lausanne, University of Zagreb, FCiencias.ID (DE)
University of Graz — Artificial Life Lab (Project coordination) (AT), Universite Paris Diderot — LIED (FR), Ecole Polytechnique Federale de Lausanne — LSRO (CH), University of Zagreb — LARICS (HR), FCiencias.ID — Associacao para a Investigacao e Desen, Cybertronica Research (DE)
Bees, fish and robots solve difficult network problems together
Networks are ubiquitous in our world today and are growing and complexifying at a global scale, from traffic and logistics to social networks and the “Internet of Things.” Optimal design of such networks is a difficult task, exploding in complexity with network size and connectivity. Thus, smart heuristics are a key technology – using randomized guessing as a form of provoked error is central to their functionality.
In ASSISIbf we aim for a radically different approach towards network optimization of this kind: We use “fuzzy” swarms of honeybees and fish, in association with autonomous robot swarms. These novel bio-hybrid “computational symbioses” efficiently search for optimal, or near-optimal, network configurations.
Credit: tom mesic
ASSISIbf / University of Graz (AT), Universite Paris Diderot (FR), Ecole Polytechnique Federale de Lausanne, University of Zagreb, FCiencias.ID (DE)
University of Graz — Artificial Life Lab (Project coordination) (AT), Universite Paris Diderot — LIED (FR), Ecole Polytechnique Federale de Lausanne — LSRO (CH), University of Zagreb — LARICS (HR), FCiencias.ID — Associacao para a Investigacao e Desen, Cybertronica Research (DE)
Bees, fish and robots solve difficult network problems together
Networks are ubiquitous in our world today and are growing and complexifying at a global scale, from traffic and logistics to social networks and the “Internet of Things.” Optimal design of such networks is a difficult task, exploding in complexity with network size and connectivity. Thus, smart heuristics are a key technology – using randomized guessing as a form of provoked error is central to their functionality.
In ASSISIbf we aim for a radically different approach towards network optimization of this kind: We use “fuzzy” swarms of honeybees and fish, in association with autonomous robot swarms. These novel bio-hybrid “computational symbioses” efficiently search for optimal, or near-optimal, network configurations.
Credit: tom mesic