The shortest path problem is solved by many methods. Heuristics offer lower complexity in expense of accuracy. There are many use cases where the lower accuracy is acceptable in return of lower consumption of computing resources. Learning Automata (LA) are adaptive mechanisms requiring feedback from the executing environment to converge to certain states. In the context of network routing, LA residing at intermediate nodes along a path, exploit feedback from the destination node for reducing, e.g., path's length. According to topology’s resources like the node and edge numbers, the proper number of iterations must be used. More iterations lead to paths with higher probability of being optimal but more computing resources are consumed.

Development takes place at https://github.com/zfoxer/LaPath

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Categories

Artificial Intelligence, Router

License

GNU General Public License version 3.0 (GPLv3)

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Intended Audience

Developers

Programming Language

C++

Related Categories

C++ Artificial Intelligence Software, C++ Router Firmware

Registered

2020-11-10
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