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A Vision on Analysing Approaches for Knowledge Representation and Reasoning Using Computer Games

Artificial intelligences (AIs) that interact with their environment are difficult to compare and evaluate as their formal properties easily become incomparable due to fundamentally different knowledge representations, reaction schemes, approaches and the general, very dendritic field of AI research. Nonetheless, AI approaches are regularly proposed as solutions to complex “real world” problems in areas such as self-driving cars or providing care for the elderly. Thus, the need for a safe and controllable proving ground for different AI approaches with scalable complexity emerges. Many researchers have argued that this need can be fulfilled by using computer games as a testbed [17,16]. In this paper, we propose a benchmark that specifically targets areas in AI research that still pose great challenges in AI and human-computer interaction research: the coordination of and cooperation among agents. We thus introduce and present the platform game ZooOperation as well as the corresponding competition involving this game at the KI 2017 conference, and illustrate how ZooOperation can serve as testbed for the coordination and cooperation skills of various AI approaches. On top of this, we discuss how this game, and computer games in general, can be used in comparative AI research, e.g. in testing for robustness, generalisability and human-computer interaction.