Christian Guckelsberger

PhD Student

EPSRC Centre for Doctoral Training in
Intelligent Games and Game Intelligence (IGGI)

About me

Hi, I’m Christian, a PhD student in the Computational Creativity Group. I’m also a member of IGGI, the EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence.

I am interested in how we can create artificial systems that would be deemed creative in their own right by unbiased observers. I address this challenge with formal models of intrinsic motivation. I show both theoretically and in applied studies that models of intrinsic motivation can give rise to more general, robust and adaptive creative systems. Video games make an ideal application domain for this work, as they represent arbitrarily complex, reliable abstractions of the real world, and a challenging, multi-faceted domain for designers.

I have a Magister Artium in Computer Science, History of Art and Business Studies and a BSc in Computer Science. For my theses, I worked on intrinsic motivation in multi-agent systems, and on algorithms for the serendipitous recommendation of art. During my studies, I gained industrial experience at the research department of SAP SE and worked as a research assistant at Technical University Darmstadt. I’m an open minded, passionate researcher and draw on an interdisciplinary approach. My general interests are in Computational Creativity and AI, Machine Learning and Information Theory.

My core research focusses on three different challenges. I employ formal models of intrinsic motivation to:

  • Realise intentional agency in General AI and Computational Creativity.
  • Create General Non-Player Characters which exhibit creative, companion-/enemy-like behaviour in an arbitrary video game.
  • Predict a player’s experience of video game content without involving a human player or designer.

Together with Christoph Salge and Tobias Mahlmann, I co-presented the first tutorial on Intrinsic Motivation in General Game Playing and NPCs at the Computational Intelligence and Games conference (CIG’16, Link).

I also contributed to STATSREP-ML, an open-source tool for automating the process of evaluating machine-learning results. You can find the code and instructions here.

You can contact me on .[at].., or find me on Twitter @CreativeEndvs.


Journal Articles

Schulz, Axel; Guckelsberger, Christian; Janssen, Frederik

Semantic Abstraction for Generalization of Tweet Classification: An Evaluation on Incident-Related Tweets (Journal Article)

In: Semantic Web, 2015.

(Abstract | Links | BibTeX)

Guckelsberger, Christian; Polani, Daniel

Effects of Anticipation in Individually Motivated Behaviour on Survival and Control in a Multi-Agent Scenario with Resource Constraints (Journal Article)

In: Entropy, 16 (6), pp. 3357–3378, 2014, ISSN: 1099-4300.

(Abstract | Links | BibTeX)


Guckelsberger, Christian; Salge, Christoph; Colton, Simon

Addressing the "Why?" in Computational Creativity: A Non-Anthropocentric, Minimal Model of Intentional Creative Agency (Inproceedings)

In: Proc. 8th Int. Conf. Computational Creativity, 2017 , 2017.

(Abstract | Links | BibTeX)

Denisova, Alena; Guckelsberger, Christian; Zendle, David

Challenge in Digital Games: Towards Developing a Measurement Tool (Inproceedings)

In: Proc. 35st ACM Conf. Human Factors in Computing Systems (CHI), ACM 2017.

(Links | BibTeX)

Guckelsberger, Christian; Salge, Christoph; Colton, Simon

Intrinsically Motivated General Companion NPCs via Coupled Empowerment Maximisation (Inproceedings)

In: Proc. IEEE Conf. Computational Intelligence in Games (CIG’16), IEEE, 2016.

(Abstract | Links | BibTeX)

Guckelsberger, Christian; Salge, Christoph

Does Empowerment Maximisation Allow for Enactive Artificial Agents? (Inproceedings)

In: Proc. 15th Int. Conf. Synthesis and Simulation of Living Systems (ALIFE), 2016.

(Abstract | Links | BibTeX)

Guckelsberger, Christian; Salge, Christoph; Saunders, Rob; Colton, Simon

Supportive and Antagonistic Behaviour in Distributed Computational Creativity via Coupled Empowerment Maximisation (Inproceedings)

In: Proc. 7th Int. Conf. Computational Creativity, 2016.

(Abstract | Links | BibTeX)

Llano, Maria Teresa; Guckelsberger, Christian; Hepworth, Rose; Gow, Jeremy; Corneli, Joseph; Colton, Simon

What If A Fish Got Drunk? Exploring the Plausibility of Machine-Generated Fictions (Inproceedings)

In: Proc. 7th Int. Conf. Computational Creativity, 2016.

(Abstract | Links | BibTeX)

Schulz, Axel; Guckelsberger, Christian; Schmidt, Benedikt

More Features Are Not Always Better: Evaluating Generalizing Models in Incident Type Classification of Tweets (Inproceedings)

In: Proc. Conf. Empirical Methods in Natural Language Processing (EMNLP), 2015.

(Abstract | Links | BibTeX)

Corneli, Joseph; Jordanous, Anna; Shepperd, Rosie; Llano, Maria Teresa; Misztal, Joanna; Colton, Simon; Guckelsberger, Christian

Computational Poetry Workshop: Making Sense of Work in Progress (Inproceedings)

In: Proc. 6th Int. Conf. Computational Creativity, 2015.

(Abstract | Links | BibTeX)

Llano, Maria Teresa; Cook, Michael; Guckelsberger, Christian; Colton, Simon; Hepworth, Rose

Towards the Automatic Generation of Fictional Ideas for Games (Inproceedings)

In: Experimental AI in Games (EXAG’14), a workshop collocated with the tenth annual AAAI conference on artificial intelligence and interactive digital entertainment (AIIDE’14). AAAI Publications, 2014.

(Abstract | Links | BibTeX)


Guckelsberger, Christian; Probst, Florian; Schulz, Axel

Patent: Recommender System Employing Subjective Properties (pending) (Miscellaneous)

US 20160132954 A1, 2016.

(Abstract | Links | BibTeX)

Grebner, Olaf; Bruchmann, Max; Guckelsberger, Christian; Probst, Florian; Schulz, Axel

Patent: Reporting and Managing Incidents (Miscellaneous)

US 8786433 B2, 2014.

(Abstract | Links | BibTeX)

Technical Reports

Guckelsberger, Christian; Schulz, Axel

STATSREP-ML: Statistical evaluation & reporting framework for machine learning results (Technical Report)

Telecooperation Group, Technical University Darmstadt 2014.

(Abstract | Links | BibTeX)

Invited Talks

I have been invited to give the following tasks. Please click on the accordion tab for details.

University of Hertfordshire, 2016

As part of the RAGS (Research in Adaptive systems Group Seminar) series

Collaboration in Co-Creative Scenarios via Coupled Empowerment Maximization: A Case-Study in Video Games

Recently, embodied and situated agents have become increasingly popular in co-creative systems (where humans and artificial agents jointly work on creative tasks). Intrinsically-motivated agents are particularly successful here, because of their capacity to act flexibly and adapt in open-ended interactions without clearly specified goals. Unfortunately, existing implementations do not manage to establish and maintain collaboration as a core mechanic in such systems without constraining the flexibility of the agents by means of explicitly specified interaction rules. This talk introduces the information-theoretic principle of coupled empowerment maximization as a means to establish a frame for both collaborative and antagonistic behaviour within which agents can interact with maximum flexibility. We study this mechanism in a dungeon-crawler video game testbed, to drive the behavior of an NPC supporting the human player. We demonstrate our progress, future challenges, and argue that the principle could eventually allow for the emergence of truly creative behavior.

Tungsten Centre for Intelligent Data Analytics, 2016

Does Empowerment Allow for Fully Enactive Artificial Agents?

The enactive AI framework wants to overcome the sense making limitations of embodied AI by drawing on the biosystemic foundations of enactive cognitive science. While embodied AI tries to ground meaning in sensorimotor interaction, enactive AI adds further requirements by grounding sensorimotor interaction in autonomous agency. At the core of this shift is the requirement for a truly intrinsic value function. We suggest that empowerment, an information-theoretic quantity based on an agent’s embodiment, represents such a function. We highlight the role of empowerment maximization in satisfying the requirements of enactive AI, i.e. establishing constitutive autonomy and adaptivity, in detail. We then argue that empowerment, grounded in a precarious existence, allows an agent to enact a world based on the relevance of environmental features in respect to its own identity.


My talk on “Addressing the “Why?” in Computational Creativity: A Non-Anthropocentric, Minimal Model of Intentional Creative Agency” at the 8th International Conference on Computational Creativity in Atlanta, Georgia, June 19 – June 23, 2017 (paper link).

This video showcases our research on intrinsically motivated, general companion NPCs (paper link).