> > > > Now, what I say above is "easy to say" but is "hard to do" -- implementing > what I suggest is a large project. But then, in software, nothing is free. > facebook and google and amazon employ thousands of engineers because > writing good software is hard. Imagining that you can create a new planner > out of thin air in a few months is not a realistic dream. Don't repeat > history; learn from it. > >
Linas, I am sure that writing a commercial-grade scalable planner is a lot of work and would take a team of competent developers more than a few months On the other hand, exploring and prototyping new planning algorithms/approaches is a perfectly sensible and feasible thing for a smart student to do over a few months, and I think URE and/or PLN could be reasonable tools for this... As I understand what is being proposed here is a student research project not a large-scale engineering project... I note that a lot of the large-scale engineering projects being done at Google and Amazon are based on algorithms developed by grad students via experimentation w/ non-scalable "throwaway code" ... (and ofc many of those grad students then get hired by the tech behemoths and may become engineers working on scalable systems, or may remain algo-focused researchers...) Exploring constraint-satisfaction-based planning makes sense, but for some planning domains this approach may not be best. E.g. if you're planning in a highly dynamic environment (as faced say by robots moving around in a house or on the street) then I'm not sure the available constraint satisfaction algos can deal well w/ the needed real-time plan updating...? My 2 tokens worth... ben -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CACYTDBf_G7o7%2BFDWU_aN307znungm6xje18%3DKP2_seEh3Y8h_A%40mail.gmail.com.
