Abstract
We present Cedar, a software framework for the implementation and simulation of embodied cognitive models based on Dynamic Field Theory (DFT). DFT is a neurally inspired theoretical framework that integrates perception, action, and cognition. Cedar captures the power of DFT in software by facilitating the process of software development for embodied cognitive systems, both artificial and as models of human cognition. In Cedar, models can be designed through a graphical interface and interactively tuned. We demonstrate this by implementing an exemplary robotic architecture.
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Lomp, O., Zibner, S.K.U., Richter, M., Rañó, I., Schöner, G. (2013). A Software Framework for Cognition, Embodiment, Dynamics, and Autonomy in Robotics: Cedar . In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_60
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DOI: https://doi.org/10.1007/978-3-642-40728-4_60
Publisher Name: Springer, Berlin, Heidelberg
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