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Abstract: "Abstract Game developers spend a large portion of their time developing and tweaking the articial intelligence in video games. Problems related to productivity in the development of AI have been solved using various modeling techniques in the eld of AI, language design and easier to use editors. Using a domain specic language to assist in describing AI can increase productivity in this area. In addition to this, game developers can be relieved from irrelevant tasks such as worrying about performance, correctness of the implementation, memory management and optimiza- tion data structures and focus on the high level description of the game play. In this thesis, we focus on real-time video games and we investigate the development of a domain-specic language containing the necessary elements to describe and execute strategies to achieve goals in a real-time video game. We develop a domain-specic language to express strategies for computer controlled actors using techniques commonly found in em- bedded domain-specic languages, and in particular embedded domain- specic languages in Haskell. To demonstrate this language we have developed a prototype of a real-time strategy game that uses strategies implemented using the domain-specic language developed in this thesis"

Abstract: "We propose a powerful new tool for conducting research on computational intelligence and games. 'PyVGDL' is a simple, high-level description language for 2D video games, and the accompanying software library permits parsing and instantly playing those games. The streamlined design of the language is based on defining locations and dynamics for simple building blocks, and the interaction effects when such objects collide, all of which are provided in a rich ontology. It can be used to quickly design games, without needing to deal with control structures, and the concise language is also accessible to generative approaches. We show how the dynamics of many classical games can be generated from a few lines of PyVGDL."

Abstract: "ARTigo is a Game with a Purpose platform whose goal is to collect tags for artworks, which can be used for retrieval. The ARTigo gam es form a tagging ecosystem, where the games cooperate in order to gather a wide range of information. Description games create initial tags, in order to enable other games to be played and collect semantically shallow surface tags. Dissemination games sp read existing data to other artworks or languages, and do not create new information. Diversification games feed on data produced by other games and guide the players to entering more specific tags. Finally, integration games create higher - order tags with deep semantic meanings, describing emotions for example. All these different types of tags have different semantic depths, and are present in different quantities. Together, they create a pool of complementary tags accurately describing artworks, which can be processed for data mining."