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Development of Digital Game Environments Stimulating Creativity in Engineering Education

Development of Digital Game Environments Stimulating Creativity in Engineering Education

Alexander Alimov, Olga Shabalina, David C. Moffat
Copyright: © 2019 |Pages: 11
ISBN13: 9781522533955|ISBN10: 1522533958|EISBN13: 9781522533962
DOI: 10.4018/978-1-5225-3395-5.ch031
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MLA

Alimov, Alexander, et al. "Development of Digital Game Environments Stimulating Creativity in Engineering Education." Handbook of Research on Engineering Education in a Global Context, edited by Elena V. Smirnova and Robin P. Clark, IGI Global, 2019, pp. 368-378. https://doi.org/10.4018/978-1-5225-3395-5.ch031

APA

Alimov, A., Shabalina, O., & Moffat, D. C. (2019). Development of Digital Game Environments Stimulating Creativity in Engineering Education. In E. Smirnova & R. Clark (Eds.), Handbook of Research on Engineering Education in a Global Context (pp. 368-378). IGI Global. https://doi.org/10.4018/978-1-5225-3395-5.ch031

Chicago

Alimov, Alexander, Olga Shabalina, and David C. Moffat. "Development of Digital Game Environments Stimulating Creativity in Engineering Education." In Handbook of Research on Engineering Education in a Global Context, edited by Elena V. Smirnova and Robin P. Clark, 368-378. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-3395-5.ch031

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Abstract

Teaching for creativity is one of the most challenging problems in engineering education. Two approaches are mostly applied in teaching creative skills: using creative problem-solving exercises and emerging people into a creative environment for stimulating their creativity. One of the most important requirements to creative digital environment is creativity of its non-player characters (NPC). The chapter discusses the advantages of applying a multi-agent (MA) approach to achieve creative behavior of the NPCs. The agent architecture is based on a behavior tree model, extended with three additional classes of nodes, implementing agent reactions and adaptive action planning according to agent priorities. The proposed agent architecture is implemented in a typical survival action game where all players, represented as agents, should explore the world to find resources. The assessment of the quality of agents' behavior shows that all the agents successfully demonstrate rational and adaptive behavior in the complex dynamical environment.

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