Further information

Members of MMM collaborate closely with each other at the level of individual working groups, as well as in the context of larger projects and initiatives. Further information:

MMM Seed Grants:
Call for Proposals: MMM PI-Seed-Grants

The MMM Seed Grant Initiative is entering its third round of calls! This round introduces two separate funding lines: one for MMM PIs and one for MMM PostDocs. The current call for MMM PI Seed Grant applications aims to support scientific collaborations between established MMM members (MMM PIs) that go significantly beyond the goals of the previous two rounds. The MMM Seed Grant funding line for MMM PostDocs will be launched one month after the PI Seed Grant call.

The MMM PI Seed Grant is aimed at initiatives that want to conduct collaborative research on Minds, Media, and Machines in the thematic area of “Living Technologies 2.0”. The overarching goal of collaborative proposals in this funding line should therefore be related to our ongoing efforts to advance collaborative MMM research in artificial intelligence, robotics, machine learning, data science, human-computer interaction, social media, and mediatization. In keeping with our mission statement, proposals should consider these research areas in the context of key issues related to MMM technologies – such as the benefits and well-being of society, taking into account aspects such as usability, privacy, security, sustainability, and legality, as well as supporting aspects of human life ranging from raising children to supporting the elderly.

MMM Seed Grants are intended for teams of at least two AGs in MMM. Applications from MMM teams across disciplines are especially encouraged, but not required. The MMM Seed Grant amount for this round of calls is up to EUR 38,000 per AG per grant. The deadline for this round of calls is October 15, 2021. Relevant submissions should be sent to:

For further information to apply, please refer to this template.

Research Projects

MMM members are involved in a large number of exciting research projects relating to Minds, Media, and Machines. Here, we merely showcase a few of the most recent collaborative projects. For further information, please follow the respective links, and visit our member page.

  • MUHAI – Meaning and Understanding in Human-centric AI ( Responsible human-centric AI needs a way to deal with meaning. The MUHAI project tackles this foundational question by developing computational models of narrative construction. Creating or understanding narratives requires the integration of information coming from sensory-motor embodiment, measurement data, language,  semantic memory, mental simulation, and episodic memory.

    The outcome of MUHAI is twofold. It will push the state of the art in cognitive home robotics, particularly for food production and the management of food resources, and it will provide tools for social scientists to better understand social phenomena, as for example the persistence of inequality in our society. The MUHAI project has started in October 2020 and will finish 48 months later.
    Coordinator: Prof. Dr. Rainer Malaka
    Funded by: EU Horizon 2020 (No. 951846)

  • IntEL4CoRo – “Integrierte Lernumgebung für kognitive Robotik” (link).

    IntEL4CoRo follows the approach of skills-oriented teaching. This means that students are enabled to apply their knowledge and develop it autonomously. The researchers from the University of Bremen that are being led by Professor Michael Beetz and Dr. Yildiray Ogurol want to achieve this by integrating practical elements into their learning environment. For example, students are to work intensely with control systems for robots and physics-based simulations. Research teams from the Institute for Artificial Intelligence (IAI) and the Center for Multimedia in Higher Education (ZMML) have been combined for this purpose. They are being supported by the Center for Networks (ZfN) at the university, as well as the Cognitive Systems Lab (CSL), the Virtual Academy of Sustainability (VAN), the Public Health degree course and the Centre for Media, Communication and Information Research (ZeMKI).
    Coordinators: Prof. Dr. Michael Beetz, Dr. Yildray Ogurol
    Funded by: BMBF

  • Research Training Group π³ – Parameter Identification – Analysis, Algorithms, Implementations ( Mathematics can make even the most complex problems manageable by reducing them to the essential. For example, it develops high-dimensional and non-linear models to solve problems of parameter identification that occur in all areas of the natural sciences, life sciences and engineering as well as in industrial and economic applications. In the graduate program “π³: Parameter Identification – Analysis, Algorithms, Implementations”, PhD students concentrate on the interface between applied mathematics and computer science on questions of parameter identification, which are essentially formulated as high-dimensional minimization problems for suitable functionals.
    Speaker:Prof. Dr. Peter Maaß
    MMM-PIs: Prof. Dr. Christof Büskens, Prof. Dr. Thorsten Dickhaus
    Funded by
    : DFG (Research Training Group)

  • KD²school Decision & Design – Designing Adaptive Systems for Economic Decision-Making (

    Economic decisions in business and in everyday life are increasingly supported by IT-based systems. As a result, these systems effectively operate as “cast in code” institutions and processes, and their design influences decision makers’ interactions and behaviors. The interplay between economic decision making and system design is at the core of the KD²School as it lays the foundations for the transformation of static systems into dynamic, adaptive systems.
    As a publicly sponsored and neutrally coordinated program, the KD²School opens up a research field that is at present primarily “investigated” with profit-oriented or political goals.
    Speakers: Prof. Dr. Christof Weinhard (KIT), Prof. Dr. Tanja Schultz
    Funded by: DFG (Research Training Group)

  • AI4HRI – Artificial Intelligence for Human-Robot Interaction (link). Europe and Japan both face problems of shrinking and aging population, and using social robots is seen as a possible way of alleviating demographic issues. Robots need to be able to interact with people and this is studied in the field of Human-Robot Interaction (HRI). But dealing with humans is difficult, and HRI is still not making enough use of AI technologies. The goal of the AI4HRI project will be to both develop and integrate several AI methods which will allow social robots to appropriately deal with humans around them. This includes 3 abilities that we believe are currently missing in HRI: knowledge management and reasoning, learning of social skills, and planning and executing joint human-robot actions. Each partner in the project is a leading expert in one of these fields and the project will benefit from their synergy. Importantly, the above abilities will be combined into a single open-source architecture and shared with other researchers.
    MMM-PI: Prof. Dr. Michael Beetz
    Funded by: DFG (French-Japanese-German Trilateral call on Artificial Intelligence)