arXiv subjects

Simon Colton

Publications and source records attributed to Simon Colton.

23 records · Page 2Linked to original sources

arXiv2019

Camera Obscurer: Generative Art for Design Inspiration

We investigate using generated decorative art as a source of inspiration for design tasks. Using a visual similarity search for image retrieval, the \emph{Camera Obscurer} app enables rapid searching of tens of thousands of generated abstract images of various types. The seed for a visual similarity search is a given image, and the retrieved generated images share some visual similarity with the seed. Implemented in a hand-held device, the app empowers users to use photos of their surroundings to search through the archive of generated images and other image archives. Being abstract in nature, the retrieved images supplement the seed image rather than replace it, providing different visual stimuli including shapes, colours, textures and juxtapositions, in addition to affording their own interpretations. This approach can therefore be used to provide inspiration for a design task, with the abstract images suggesting new ideas that might give direction to a graphic design project. We describe a crowdsourcing experiment with the app to estimate user confidence in retrieved images, and we describe a pilot study where Camera Obscurer provided inspiration for a design task. These experiments have enabled us to describe future improvements, and to begin to understand sources of visual inspiration for design tasks.

cs.MM↗

arXiv2018

Exploring Novel Game Spaces with Fluidic Games

With the growing integration of smartphones into our daily lives, and their increased ease of use, mobile games have become highly popular across all demographics. People listen to music, play games or read the news while in transit or bridging gap times. While mobile gaming is gaining popularity, mobile expression of creativity is still in its early stages. We present here a new type of mobile app -- fluidic games -- and illustrate our iterative approach to their design. This new type of app seamlessly integrates exploration of the design space into the actual user experience of playing the game, and aims to enrich the user experience. To better illustrate the game domain and our approach, we discuss one specific fluidic game, which is available as a commercial product. We also briefly discuss open challenges such as player support and how generative techniques can aid the exploration of the game space further.

cs.AI↗

arXiv2017

Off The Beaten Lane: AI Challenges In MOBAs Beyond Player Control

MOBAs represent a huge segment of online gaming and are growing as both an eSport and a casual genre. The natural starting point for AI researchers interested in MOBAs is to develop an AI to play the game better than a human - but MOBAs have many more challenges besides adversarial AI. In this paper we introduce the reader to the wider context of MOBA culture, propose a range of challenges faced by the community today, and posit concrete AI projects that can be undertaken to begin solving them.

cs.AI↗

arXiv2016

The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity

We introduce a new artificial intelligence (AI) approach called, the 'Digital Synaptic Neural Substrate' (DSNS). It uses selected attributes from objects in various domains (e.g. chess problems, classical music, renowned artworks) and recombines them in such a way as to generate new attributes that can then, in principle, be used to create novel objects of creative value to humans relating to any one of the source domains. This allows some of the burden of creative content generation to be passed from humans to machines. The approach was tested in the domain of chess problem composition. We used it to automatically compose numerous sets of chess problems based on attributes extracted and recombined from chess problems and tournament games by humans, renowned paintings, computer-evolved abstract art, photographs of people, and classical music tracks. The quality of these generated chess problems was then assessed automatically using an existing and experimentally-validated computational chess aesthetics model. They were also assessed by human experts in the domain. The results suggest that attributes collected and recombined from chess and other domains using the DSNS approach can indeed be used to automatically generate chess problems of reasonably high aesthetic quality. In particular, a low quality chess source (i.e. tournament game sequences between weak players) used in combination with actual photographs of people was able to produce three-move chess problems of comparable quality or better to those generated using a high quality chess source (i.e. published compositions by human experts), and more efficiently as well. Why information from a foreign domain can be integrated and functional in this way remains an open question for now. The DSNS approach is, in principle, scalable and applicable to any domain in which objects have attributes that can be represented using real numbers.

cs.AI↗

arXiv2016

Semi-Automated Design Space Exploration for Formal Modelling

Refinement based formal methods allow the modelling of systems through incremental steps via abstraction. Discovering the right levels of abstraction, formulating correct and meaningful invariants, and analysing faulty models are some of the challenges faced when using this technique. Here, we propose Design Space Exploration, an approach that aims to assist a designer by automatically providing high-level modelling guidance in real-time. More specifically, through the combination of common patterns of modelling with techniques from automated theory formation and automated reasoning, different design alternatives are explored and suitable models that deal with faults are proposed.

cs.SE↗