Abstract
Teaching Artificial Intelligence in higher education develops critical thinking, problem-solving, and computational skills. Negotiation is a crucial aspect of multi-agent systems, enabling agents to achieve their goals through communication and collaboration. In this area, simulation platforms provide a flexible and safe way to experiment, leading to improvements in negotiation and decision-making in a wide range of scenarios. Board games, which include interaction and negotiation between players, provide a low-cost and low-risk way to experiment with different negotiation strategies. In this context, we present a novel simulation platform based on the rules of Catan, a popular boardgame that entails both strategic thinking and negotiation. This platform is oriented to teach negotiation in artificial intelligence and multi-agent systems. The platform allows students to develop and program intelligent agents to play autonomously, improving their technical skills and applying their understanding of Artificial Intelligence concepts.
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Acknowledgements
This work is supported by DIGITAL-2022 CLOUD-AI-02 funded by the European Comission and grant PID2021-123673OB-C31 funded by MCIN/AEI/ 10.13039/501100011033 and by ”ERDF A way of making Europe.
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Heras, A., Alberola, J.M., Sánchez-Anguix, V., Julián, V., Botti, V. (2023). A Simulation Platform for Testing Negotiation Strategies and Artificial Intelligence in Higher Education Courses. In: García Bringas, P., et al. International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023). CISIS ICEUTE 2023 2023. Lecture Notes in Networks and Systems, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-031-42519-6_24
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DOI: https://doi.org/10.1007/978-3-031-42519-6_24
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