EU FET-project: Animal and robot Societies Self-organise and Integrate by Social Interaction (bees and fish)






Integration of robots into honeybee and fish swarms


In February 2013 the largest project of the recent EU call „FOCAS“ (Fundamentals of Collective Adaptive Systems) has started.

The main goal of ASSISIbf is to establish a robotic society that is able to develop communication channels to animal societies (honeybees & fish swarms) on its own.

These robots will adapt by evolutionary algorithms until they have learned to interact with animals in a desired way. This new technology is aimed to lay new foundations on the way how humans can interfere with animal societies in order to manage the environment. The researchers expect their work to have impact on agriculture, live stock management and environmental protection. In parallel, the mixed societies of animals and robots will represent a novel kind of bio-hybrid ICT system, as the animals will enrich the capabilities of the machines and vice versa.



The research is conducted by six European institutions from Austria, Croatia, France, Germany, Portugal and Switzerland. The project is coordinated by Univ. Prof. Thomas Schmickl

1. Develop robots that can influence the collective behaviours of animals (bees and fish).
2. Establishing an adaptive and self-organising society build by robots and animals.
3. Enable the robots to autonomously „learn“ the social language of the animals.
4. Establish mixed societies that pursue a common goal which can be defined by human ,users‘ of the system.
5. Allow the robots to gain novel skills by incorporating the capabilities of the animals (sensors, cognition).


Emergence of collective decision-making between honeybees and zebrafish mediated by robots


>>> Public Open Access link to the Science Robotics article describing the experiment: Robots mediating interactions between animals for interspecies collective behaviors



During the last decade, it has been shown that groups of robots can be socially accepted by animals and can participate in their collective decision making. It works, for example, with cockroaches, honeybees, various fish species and rats. If robots can become social companions of animals, can they go further and even enhance the collective behaviors of animals? Can robots allow the animals to do things that the animals cannot do by themselves alone? For example, can animals communicate over long distances via telecommunication systems like the Internet? Can the animals communicate and interact with species that they would never encounter in their natural ecosystem?

The members* of the European Future and Emerging Technologies (FET) project ASSISIbf have been working on the creation of ICT systems that can interface with groups of animals. In particular, two types of robots that can integrate groups of honeybees and zebrafish respectively have been designed, and the interaction and decision-making mechanisms within these groups have been studied. Physical models of collective behavior have also been created. These models are implemented on the robots to create mixed groups in which robots and animals can interact in closed loop and in a parsimonious way, demonstrating how collective decision-making can emerge through self-organisation.

These two robotic systems have allowed us to set up an experiment that is a first of its kind: a long distance interspecies collective behavior. Indeed, the study published in the journal Science Robotics shows how the two types of robots connected and sharing information through the Internet, allow the two groups of animals – zebrafish and honeybees – with different behaviors and evolving in completely different environments to interact remotely and make decisions together.

This experiment shows that self-organized systems are not limited to confined space, but that, by using current technological tools, such as robots and the Internet, we can study how complex self-organized systems can take place on a small- and/or large-scale, in greater detail than before. We can consider local scales of some particular species in their ecosystem, long distance scales through the telecom networks, or interspecies scales from water, land and air.

Here, we performed the experiments in laboratories but one can envision, in the future, being able to insert such robots within groups of animals in the wild. On the one hand, we could exploit the unrivaled perception capabilities of the living systems, their rich behavioral repertoires and their ease to move in the wild. On the other hand, we could influence their choices and add new physical properties like telecommunication and other robotic capacities. This approach could also provide a way to studying information flow in ecosystems and natural phenomena such as cascade effects among groups or species.

This approach could also be generalized to other living species, such as plants, fungi or even microorganisms, to allow systems to interact at very different scales. Some examples already exist with robots interacting with a single species, for example, with plants or yeast cells that are linked to intelligent systems running on computers or robots.

Using the framework that was developed during the FET ASSISIbf project, one can envision future capabilities in which the robotic systems would be able to learn and to adapt their behavior to animal species. We have already begun to explore these possibilities in the two separate bio-hybrid systems. We produced some preliminary results by using continuous real-time adaptation of multi-level behavioural models by evolutionary algorithms. We envision robotic systems that can, by themselves, discover new properties of bio-hybrid artificial intelligence towards building mixed living and computing devices, where robots could autonomously evolve among animals. These mixed groups could be put to work for environmental monitoring and interacting with organisms in the wild. The animals could also help robots to collectively solve problems.



Consortium-wide publication list:



  • Mariano, P., Salem, Z., Mills, R., Schnwetter-Fuchs-Schistek, S., Correia, L. and Schmickl, T. (2018)
    Evolving robot controllers for a bio-hybrid system.
    In Arti cial Life Conference Proceedings, pp. 155-162. One Rogers Street, Cambridge, MA 02142-1209 USA journalsinfo@mit. edu: MIT Press.


  • Cazenille, L., Chemtob, Y., Bonnet, F., Gribovskiy, A., Mondada, F., Bredeche, N. and Halloy, J. (2017)
    Automated calibration of a biomimetic space-dependent model for zebrafi sh and robot collective behaviour in a structured environment,
    In Conference on biomimetic and biohybrid systems, pp. 107-118. Springer, Cham.
  • Stefanec, M., Szopek, M., Schmickl, T. and Mills, R. (2017)
    Governing the swarm: Controlling a bio-hybrid society of bees & robots with computational feedback loops,
    In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1-8. IEEE.
  • Kengyel, D., Zahadat, P., Wotawa, F. and Schmickl, T. (2017)
    Towards Swarm Level Optimisation: The Role of Different Movement Patterns in Swarm Systems,
    The International Journal of Parallel, Emergent and Distributed Systems, pp. 1-19
  • Salem, Z., Radspieler, G., Griparic, K., and Schmickl, T. (2017)
    Estimating dynamics of honeybee population densities with machine learning algorithms,
    The 3rd International Conference on Machine Learning, Optimization & big Data - MOD 2017. LNCS 2017, 13.
  • Stefanec, M., Szopek, M., Thenius, R., Radspieler, G. and Schmickl, T. (2017)
    Robotic oligarchy: How a few members can control their whole society by doing almost nothing,
    International Conference on Bio-inspired Information and Communications Technologies (BICT 2017)
  • Szopek, M., Stefanec, M., Bodi, M., Radspieler, G. and Schmickl, T. (2017)
    A cellular model of swarm intelligence in bees and robots,
    International Conference on Bio-inspired Information and Communications Technologies (BICT 2017)
  • Silva, F., Correia, L. and Christensen, A.L. (2017)
    Evolutionary online learning in multirobot systems,
    AI Matters, 3(1), pp.23-24


  • Mills, R., Szopek, M., Bodi, M., Schmickl, T. and Correia L. (2016)
    On the timescale of interactions in bio-hybrid systems,
    In C. Gershenson, T. Froese, J.M. Siqueiros, W. Aguilar, E.J. Izquierdo, and H. Sayama, eds., Late Breaking Abstracts booklet Artificial Life Conference 2016.


  •  Bodi, M., Szopek, M., Zahadat, P. and Schmickl T. (2015)
    Evolving Mixed Societies: A one-dimensional modelling approach,
    In BICT '15: Proceedings of the 9th International Conference on Bioinspired Information and Communications Technologies.
  • Karlo Griparic, Tomislav Haus, Damjan Miklic, Stjepan Bogdan (2015)
    Combined Actuator Sensor Unit for Interaction with Honeybees.
    In Proc. of. IEEE Sensors Applications Symposium (SAS 2015)
  • Pedro Mariano, Rob Mills, Luís Correia, Damjan Milkić and Stjepan Bogdan (2015)
    ASSISI Playground: A simulation tool for collective bio-hybrid system research.
    In Procs Eurosis Simulation and Modelling Conference, Eurosis-ETI., 91-98
  • Rob Mills and Luís Correia (2015)
    The influence of topology in coordinating collective decision-making in bio-hybrid societies.
    In Procs EPIA, Springer. 250-261
  • Pedro Mariano & Luís Correia (2015)
    Partner selection delays extinction in cooperative and coordination dilemmas.
    In Grimaldo, F. & Norling, E. editors, Multi-Agent-Based Simulation XV, Lecture Notes in Computer Science, Springer International Publishing, 88-103
  • Fernando Silva, Luís Correia, Anders Lyhne Christensen (2015)
    Modelling Synchronisation in Mulitrobot Systems with Cellular Automata: Analysis of Update Methods and Topology Perturbations.
    In Sirakuoulis, G. & Adamatzky, A. editors, Robots and Lattice Automata. Emergence, Complexity and Computation 13, Springer International Publishing, 267-293



  • Tomislav Haus, Ivana Palunko, Domagoj Tolic, Stjepan Bogdan, Frank L. Lewis, Dariusz G. Mikulski (2014)
    Trust-based self-organising network control.
    IET Control Theory & Applications 8, 2126-2135
  • Sibylle Hahshold, Renate Ploder, Gerald Radspieler, Thomas Schmickl, Karl Crailsheim (2014)
    Temperature preferendum of single, young honeybees.
    Abstract in Entomologica Austriaca  21, 240
  • Martina Szopek, Sibylle Hahshold, Ronald Thenius, Michael Bodi, Karl Crailsheim, Thomas Schmickl (2014)
    ASSISIbf: Honeybees and robots form a bio-hybrid society.
    Abstract in Entomologica Austriaca 21, 242-243


  • José Halloy, Francesco Mondada, Serge Kernbach, Thomas Schmickl (2013)
    Towards Bio-hybrid Systems Made of Social Animals and Robots
    In: N.F. Lepora et al. (eds.): Living Machines 2013, Lecture Notes In Artificial Intelligence, LNAI 8064, 384-386




Project is coordinated by University of Graz, in the following University of Graz specific information is given:






Project Leader: Thomas Schmickl
Project Management: Gerald Radspieler
Team: Ronald Thenius, Martina Szopek, Martin Stefanec, Payam Zahadat, Sarah Schönwetter-Fuchs, Stefan Schönwetter-Fuchs-Schistek, Thomas Schmickl, Ziad Salem, Asya Ilgün, Nikolaus Sabathiel, Valerin Stokanic
Duration: 01.02.2013 to 31.07.2018
Budget: 6 Mio. Euro
Granted By: EU - 601074


Université Paris Diderot - Paris 7


University of Zagreb, Faculty of Electrical Engineering and Computing, LARICS - Laboratory for Robotics and Intelligent Control Systems

Ecole Polytechnique Fédérale de Lausanne - The Laboratoire de Systémes Robotiques

Fundação da Faculdade de Ciências da Universidade de Lisboa (FFCUL)





Publication list Artificial Life Lab:









Student Work: