- Lua supports argument passing by reference, which results in more elegant code, and the stack suffers less during function calls.
- Lua is a highly embeddable language, from embedded systems to games.
- Lua is much faster (the breadth-first search unit test with Octave takes 34ms, while with Lua it takes 0.073ms).
- Lua is darn lightweight (see the amount of RAM used by the respective live interpreters: Octave 15.1MB, Lua 523kB, measured with ps_mem.py).
- Lua provides a means for code encapsulation (modules and classes) and thus paves the way better organisation.
Apparently, the only common aspect between Octave and Lua is the array indexation starting at 1. Octave is a great numerical platform for scientific computing, Matlab is the evidence of such interest, but Lua seems to be the least risky strategic approach due to its broader applicability. Moreover, Lua is a language that pushes the tools beyond its limits. There’s a lot of going on about this recently at the Facebook AI Research centre with deep learning.
Doing AI in Lua is definitely a clever deed. There is an incipient predecessor of this approach, the aima-lua project, developed by James Graves. James kindly warned me about the difficulty of structuring it, so I’m talking his piece of advice by delaying such a decision, and now I’m defaulting to a plain function-based organisation. Eventually, my goal is to switch to speech and language processing when I get to “communicating, perceiving and acting” (AIMA book, part 4), so this even increases the uncertainty about the adequate module structure at this moment. Time will tell. Wish me luck