On Thursday, September 3, 2015 at 10:29:33 AM UTC-4, Linh Chi Nguyen wrote: > Dear All, > I'm a complete newbie in racket and need help in coding finite state > machine/automata. Please pardon any of my ignorance. > > Thanks to this post of Tim Thornton, I see a very good way to code FSM: > http://timthornton.net/blog/id/538fa6f2f09a16ba0674813d > > I'd summarise it as following: > A finite state automaton has a number of states and each state has a name > plus many transition rules. He structures it in racket as following: > > (struct automaton (current-state states)) > (struct state (name actions)) > (struct action (event result)) > > A simple automaton can be like this: > (define simple-fsm (fsm 'A > (list (fstate 'A (list (action 0 'A) > (action 1 'B))) > (fstate 'B (list (action 0 'B) > (action 1 'A)))))) > > The automaton is in state A which has 2 transition rules: > - if event 1 happens, the automaton jumps to state B, > - if event 0 happens, it stays in state A. > > Then he writes some functions to update the automaton after each event (in > the post). Plus this function he omits (I guess): > (define fsm-update-state old-fsm new-state) > (struct-copy automaton old-fsm [current-state new-state])) > > HERE IS THE QUESTION: > > Using this way, after each event, there'd be a NEW automaton created. So I'm > worried about scaling. I'd like to generate 100 automata. In each cycle, I'd > pair the automata to interact for 50 times. Which means that there'd be 100 > new automata created for every single cycle. And I'd like to run at least > 1000 cycles. > > Would there be any problem with scaling? If yes, is there a way around this? > > Any kind of comments and suggestions are welcomed and appreciated, > Thank you really much, > Chi
You might want to take a look at https://github.com/mromyers/automata specifically, https://github.com/mromyers/automata/blob/master/examples.rkt and https://github.com/mromyers/automata/blob/master/machines.rkt I more or less just use the definition that was in my textbook: you provide a transition function, and the DFA or NFA just uses stream-fold to get the extended transition. I used a bunch of generics stuff to try to generalize everything past the point of practicality, but it's still reasonably fast. It's not documented, but use (in-machine? M seq) to check for acceptance, (extended-transition M start seq) for final state(s). There's also a minimization function and nfa->dfa conversion in there, but they might have some bugs. -- You received this message because you are subscribed to the Google Groups "Racket Users" group. To unsubscribe from this group and stop receiving emails from it, send an email to racket-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
