Abstract
The project MASIVE (Multi-Agent Systems Interactive Virtual Environments) is the multi-agent extension of our Interactivist-Expectative Theory on Agency and Learning (IETAL). The agents in the environment learn expectations from their interactions with the environment. In addition to that, they are equipped with special sensors for sensing akin agents, and interchange their knowledge of the environment (their intrinsic representations) during their imitation conventions. In this paper we discuss the basics of the theory, and the social consequences of such an environment from the perspective of learning, knowledge dissemination, and emergence of language.
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Trajkovski, G. (2002). MASIVE: A Case Study in Multiagent Systems. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_41
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DOI: https://doi.org/10.1007/3-540-45675-9_41
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