Abstract
Cognitive approaches to complex systems modeling are currently limited by the lack of flexible, composable, tractable simulation frameworks. Here, we present Active Blockference, an approach for cognitive modeling in complex cyberphysical systems that uses cadCAD to implement multiagent Active Inference simulations. First, we provide an account of the current state of Active Inference in cognitive modeling, with the Active Entity Ontology for Science (AEOS) as a particular example of Active Inference applied to decentralized science communities. We then give a brief overview of Active Blockference and the initial results of simulations of Active Inference agents in grid environments (Active Gridference). We conclude by sharing some preferences and expectations for further research, development, and applications. The open source package can be found at https://github.com/ActiveInferenceLab/ActiveBlockference.
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Smékal, J., Choudhury, A., Singh, A.K., Damaty, S.E., Friedman, D.A. (2023). Active Blockference: cadCAD with Active Inference for Cognitive Systems Modeling. In: Buckley, C.L., et al. Active Inference. IWAI 2022. Communications in Computer and Information Science, vol 1721. Springer, Cham. https://doi.org/10.1007/978-3-031-28719-0_10
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DOI: https://doi.org/10.1007/978-3-031-28719-0_10
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