Thomas Schmickl


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From 2001-2006 I started to found a research group working in the national and international research grants we acquired. After my stay in the U.S. (ETSU) in 2007, I founded  the Artificial Life Laboratory as a part (research lab) of the Department for Zoology. Since then, I act as lab supervisor in this lab.

I am currently affiliated associate professor at the Department for Zoology at the University of Graz (Austria). Within this lab, I founded the Artificial Life Lab Graz in 2007. 

This publication list below shows publications since 2007. For seeing the previous ones, look into the PDF of the C.V., it includes a full publication list.

Click here to see my C.V. and my teaching statement.

Main Achievements:

  • FloraRobotica: Creating an interacting society of plants and robots, thus forming a bio-hybrid cyborg by closing the behavioral feedback loops.
  • subCULTron: Invention of the aMUSSEL, a novel type of autonomous bio-inspired underwater robot, inspired by mussels and clams.
  • ASSISIbf: First time that robots evolved to communicate/interact with living animals.
  • ASSISIbf: Self-adaptive merging of real honeybees swarms with autonomous robots and of a real fish swarm with an autonomous robot swarm.
  • ASSISIbf: Evolving robots to translate between honeybees and fish.
  • Jasmine-Swarm: From 2005 to 2014 I participated in the world’s largest landbased  autonomous robot swarm (350+ robots).
  • CoCoRo: Since 2013 the world’s largest autonomous underwater swarm with 41 underwater vehicles.
  • CoCoRo: First time in the world that a robot swarm passes (collectively!) the famous mirror test.
  • BEECLUST: World’s simplest swarm algorithm (derived from honeybees, implemented on many robot swarms). Implementable almost everywhere, generating collective cognition in a swarm of poorly controllable, poorly sensing, memoryless and communicationless robots/agents.
  • Common Stomach (with I. Karsai): A mechanism to regulate division of labour decent rally without a global (central) component as an alternative hypothesis for threshold-based mechanisms, auctioneering-based mechanisms and foraging-for-work mechanisms. Mathematical models published for wasps, honeybees and ants.
  • AHHS: Artificial Homeostatic Hormone System: A hormone-inspired control algorithm for reconfigurable modular robots.
  • HoPoMo: A sophisticated mathematical model of honeybees’ population dynamics and resource allocation.

Other achievements:

  • FireSlime Algorithm (with R. Thenius, P. Zahadat, A. Campo): An algorithm for allowing each swarm member to estimate the size of the swarm based on coupled oscillators without a central coordinating unit.
  • Wolfpack Evolution Algorithm: A novel, very simple but powerful, evolutionary algorithm exploiting a social hierarchy of agents, inspired by wolves.
  • EMANN (with R. Thenius): A model of an „emotional artificial neural networks, which is a combination of an ANN and a hormone-emulating algorithm.
  • Social Inhibition (with P. Zahadat): A honeybee-derived decentralized mechanisms for task allocation in a colony/swarm/group of workers (robots, animals) implemented in underwater robots.
  • Virtual embryogenesis (with R. Thenius): An EvoDevo-inspired algorithm for growing modular robot organisms and structured neural networks.
  • Ecological sex-ratio model: A model that demonstrated for the first time how sex-ratio, density-independent mortality, male fidelity, and sex-dependent mortality can affect the population dynamics of biological organisms.
  • TaskSelSim: First agent-based model of task-selection (foraging, storing, nursing) and population dynamics (adults, brood) of a honeybee colony.
  • HoFoSim and HoFoReSim (with R. Thenius): First agent based model of a foraging honeybee colony incorporating the material flow of nectar and the physiological expenditures of energy in foraging, storing and colony maintenance.
  • Bubbleworld.evo: An evolving agent-based predator prey model, including the evolution of behaviour and an emrgent nutrient flow.
  • SalmonMigration (with I. Karsai and J. Knisley): A mathematical model of migrating salmon populations in a river system.
  • Pond model (with I. Karsai): An agent based model of an 3-layered ecosystem in a pond or a lake.


My research fields are:


  • Bio-inspired artificial collective intelligence within robot swarms.

  • Application and re-embodiment of  self-organized animal behavior  in autonomous robots.

  • Study of animal behavior, with strong emphasis on social insects (honeybees).

  • Investigating the phenomena of self-organization and of swarm intelligence.

  • Creating multi-agent models and simulations.

Please visit my modeling site with a lot of online-simulations of self-organized animal behavior here.

In addition to the topics mentioned above, I am also working on the following topics:

  • Evolution (especially on the evolutionary aspects of animal behavior)

  • Artificial life

  • Ecological modeling

One of my favorite tasks is education. I give the following courses at the University of Graz (Austria) and at the University of Applied Sciences St. Poelten (Austria):

Spring semester:

  • "Biological modeling" (self-organization, behavior, ecology and evolution) [3 hours/week]

  • "Methods in the analysis of social systems" [1.5 hours/week]

  • "Specific chapters of simulation I and II" [2 hours/week]

Fall semester:

  • "Self-organization of biological systems" [2 hours/week]

  • "Modelling the environment  and the effects of civilization" [2 hours/week]

  • "Methods in the analysis of social systems" [1.5 hours/week]

  • "Specific chapters of simulation III and IV" [2 hours/week]



Supervisor of student works: