To push this vision forward, we are building an open-source framework based on KAN to create interpretable, efficient, and flexible AI agents.
Applying KAN to Reinforcement Learning enables the creation of intelligent systems that adapt and evolve through dynamic engagement with their environments.
Our mission is to redefine the development of AI agents by leveraging KAN as a foundational architecture.
KAN Systems is the first DAO dedicated to accelerating the adoption of Kolmogorov-Arnold Networks (KAN), a promising alternative to traditional neural networks.
11. Mission
111. What is KAN?
Figure B. Kolmogorov–Arnold Theorem
KAN is a new type of neural network rooted in the Kolmogorov-Arnold representation theorem. Designed as an alternative to traditional models like Multi-Layer Perceptrons (MLPs), KAN replace fixed activation functions with learnable ones.
Figure A. KAN Architecture
Link 1V.II. Explore
1V. Сollaborative Movement
We aim to make future development decentralized through $KAN, fostering innovation and collective progress in creating AI agents powered by KAN. Members can contribute to various aspects of the project, including research, development, community engagement, and outreach.
Link 1V.I. Join the DAO
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