Christian Guckelsberger

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Social media is a rich source of up-to-date information about events such as incidents. The sheer amount of available information makes machine learning approaches a necessity to process this information further. This learning problem is often concerned with regionally restricted datasets such as data from only one city. Because social media data such as(More)
Challenge is arguably the most important experience that players seek in digital games. However, without a measure of how challenged players feel during the act of play, it is hard to design games that are neither too easy nor too hard and, therefore, truly enjoyable. Especially in industry, challenge is dominantly assessed by means of manual play testing(More)
Creativity cannot exist in a vacuum; it develops through feedback, learning, reflection and social interaction with others. However, this perspective has been relatively under-investigated in computational creativity research, which typically examines systems that operate individually. We develop a thought experiment showing how structured dialogues can(More)
Drawing on well-known examples of serendipity in scientific discovery, we develop a set of criteria that can be applied to model and evaluate serendipity in computational settings. We use design patterns, and the growth of a pattern language, as a way to describe the processes of discovery and invention that comprise serendipitous encounters. We show how(More)
The invention of fictional ideas is often a central process in the creative production of artefacts such as poems, music, paintings and games. Currently, fictional ideation is being studied by the Computational Creativity community within the WHIM European project. The aim of WHIM is to develop the What-If Machine, a software system capable of inventing,(More)
Self-organization and survival are inextricably bound to an agent’s ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent’s peers in the(More)
Non-player characters (NPCs) in games are traditionally hard-coded or dependent on pre-specified goals, and consequently struggle to behave sensibly in ever-changing and possibly unpredictable game worlds. To make them fit for new developments in procedural content generation, we introduce the principle of Coupled Empowerment Maximisation as an intrinsic(More)
There has been a strong tendency in distributed computational creativity systems to embrace embodied and situated agents for their flexible and adaptive behaviour. Intrinsically motivated agents are particularly successful in this respect, because they do not rely on externally specified goals, and can thus react flexibly to changes in open-ended(More)
A key challenge of procedural content generation (PCG) is to evoke a certain player experience (PX), when we have no direct control over the content which gives rise to that experience. We argue that neither the rigorous methods to assess PX in HCI, nor specialised methods in PCG are sufficient, because they rely on a human in the loop. We propose to(More)
Within the WHIM project, we study fictional ideation: processes for automatically inventing, assessing and presenting fictional ideas. Here we examine the foundational notion of the plausibility of fictional ideas, by performing an empirical study to surface the factors that affect judgements of plausibility. Our long term aim is to formalise a(More)