This paper investigates strategies to generate levels for action-adventure games. For this genre, level design is more critical than for rule-driven genres such as simulation or rogue-like role-playing games, for which procedural level generation has been successful in the past. The approach outlined by this article distinguishes between missions and spaces as two separate structures that need to be generated in two individual steps. It discusses the merits of different types of generative grammars for each individual step in the process. Notably, the approach acknowledges that the online generation of levels needs to be tailored strictly to the actual experience of a player. Therefore, the approach incorporates techniques to establish and exploit player models in actual play.
Now that collaborative robots are becoming more widespread in industry, the question arises how we can make them better co-workers and team members. Team members cooperate and collaborate to attain common goals. Consequently they provide and receive information, often non-linguistic, necessary to accomplish the work at hand and coordinate their activities. The cooperative behaviour needed to function as a team also entails that team members have to develop a certain level of trust towards each other. In this paper we argue that for cobots to become trusted, successful co-workers in an industrial setting we need to develop design principles for cobot behaviour to provide legible, that is understandable, information and to generate trust. Furthermore, we are of the opinion that modelling such non-verbal cobot behaviour after animal co-workers may provide useful opportunities, even though additional communication may be needed for optimal collaboration. Marijke Bergman, Elsbeth de Joode, +1 author Janienke Sturm Published in CHIRA 2019 Computer Science
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