Abstract
This article presents an overview on Ipseity [1], an opensource rich-client platform developed in C++ with the Qt [2] framework. Ipseity facilitates the synthesis of artificial cognitive systems in multi-agent systems. The current version of the platform includes a set of plugins based on the classical reinforcement learning techniques like Q-Learning and Sarsa. Ipseity is targeted at a broad range of users interested in artificial intelligence in general, including industrial practitioners, as well as machine learning researchers, students and teachers. It is daily used as a course support in Artificial Intelligence and Reinforcement Learning and it has been used successfully to manage power flows in simulated microgrids using multi-agent reinforcement learning [4].
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Gaud, N., Galland, S., Hilaire, V., Koukam, A.: An organisational platform for holonic and multiagent systems. In: Hindriks, K.V., Pokahr, A., Sardina, S. (eds.) ProMAS 2008. LNCS, vol. 5442, pp. 104–119. Springer, Heidelberg (2009)
Lauri, F., Basso, G., Zhu, J., Roche, R., Hilaire, V., Koukam, A.: Managing Power Flows in Microgrids using Multi-Agent Reinforcement Learning. In: Agent Technologies in Energy Systems (ATES) (2013)
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Lauri, F., Gaud, N., Galland, S., Hilaire, V. (2013). Ipseity – A Laboratory for Synthesizing and Validating Artificial Cognitive Systems in Multi-agent Systems. In: Blockeel, H., Kersting, K., Nijssen, S., Železný, F. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2013. Lecture Notes in Computer Science(), vol 8190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40994-3_45
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DOI: https://doi.org/10.1007/978-3-642-40994-3_45
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