October 4 – 9 , 2020, Dagstuhl Seminar 20411

CANCELLED Cognitive Robotics

Due to the Covid-19 pandemic, this seminar was cancelled.


Fredrik Heintz (Linköping University, SE)
Gerhard Lakemeyer (RWTH Aachen, DE)
Sheila McIlraith (University of Toronto, CA)

For support, please contact

Simone Schilke for administrative matters

Andreas Dolzmann for scientific matters


Cognitive Robotics is concerned with endowing robots or software agents with higher level cognitive functions that involve reasoning, for example, about goals, perception, actions, the mental states of other agents, collaborative task execution, etc. This research agenda has historically been pursued by describing, in a language suitable for automated reasoning, enough of the properties of the robot, its abilities, and its environment, to permit it to make high-level decisions about how to act. Such properties were typically encoded by a human, but with recent advances in machine learning, many of these properties, and the determination of how to act, can be learned or adapted through experience. This in turn raises the question of how we can ensure that robots, or other intelligent agents, can be constructed in a manner that is compatible with human values and modes of interactions.

The Cognitive Robotics workshop series has been running since 1998 and includes a Dagstuhl Seminar held in 2010. While progress in Cognitive Robotics has undoubtedly been made over the past twenty years, it is fair to say that we are still far away from creating truly cognitive robots. In particular, the years since the previous Dagstuhl Seminar have seen tremendous progress in many areas that touch on the realisation of cognitive robots such as advances in symbolic and motion planning, human-robot interaction, understanding causality, and of course machine learning.

The focus of this Cognitive Robotics Dagstuhl Seminar will be on putting these and other pieces together through the thematic lens of Human-Compatible Trustworthy Cognitive Robotics. Robots are increasingly moving out of controlled manufacturing settings and into domains where they will be residing or interacting, directly or indirectly, with humans. The goal of developing cognitive robots that can live and work alongside humans will present a unifying theme that drives discussion and technical advances. Some of the topics the seminar will investigate include:

Hybrid reasoning: Identify and discuss challenges related to combining symbolic reasoning techniques with quantitative forms of reasoning so that these methods can be put to use in cognitive robotics in a human-compatible way.

Machine learning: Identify and discuss challenges related to principled ways of integrating machine learning and reasoning and the role of end-to-end learning when building robots that are deliberative and trustworthy, while having the capacity to learn.

Human Interaction: Successful interaction and communication requires sufficient understanding of both the surroundings and the other agents. This raises the question of which KR&R methods are needed to support this understanding in a cognitive robot, often combined with learning.

AI Ethics: To realize human-compatible trustworthy AI there are many key concepts that directly relate to cognitive robotics and where methods developed in this community could be of value to a broader community. We will identify key technical problems that contribute towards the development of cognitive robots that can reside and interact with humans in an ethically acceptable manner.

The seminar aims for both a road map of research topics in cognitive robotics for the next five to ten years and to stimulate more interdisciplinary work where researchers from diverse subfields of AI, including knowledge representation and reasoning, machine learning, human computer interactions, and other cognate subfields collaborate to pursue this shared research agenda.

Motivation text license
  Creative Commons BY 3.0 DE
  Fredrik Heintz, Gerhard Lakemeyer, and Sheila McIlraith

Related Dagstuhl Seminar


  • Artificial Intelligence / Robotics
  • Semantics / Formal Methods
  • Verification / Logic


  • Cognitive robotics
  • Knowledge representation and reasoning
  • Machine learning
  • Cognitive science


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