149 lines
3.6 KiB
Prolog
149 lines
3.6 KiB
Prolog
%
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%
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%
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:- module(clpbn_evidence,
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[store_evidence/1,
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incorporate_evidence/2,
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check_stored_evidence/2,
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add_stored_evidence/2,
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put_evidence/2
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]).
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:- use_module(library(clpbn)).
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:- use_module(library('clpbn/dists'),
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[get_dist/4]).
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:- use_module(library(rbtrees),
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[rb_new/1,
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rb_lookup/3,
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rb_insert/4
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]).
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:- meta_predicate store_evidence(:).
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:- dynamic node/3, edge/2, evidence/2.
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%
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% new evidence storage algorithm. The idea is that instead of
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% redoing all the evidence every time we query the network, we shall
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% keep a precompiled version around.
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%
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% the format is as follows:
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% evidence_store:parent(Key,ParentList,[EvidenceChildren])
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%
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%
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store_evidence(G) :-
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clpbn_flag(solver,PreviousSolver, graphs),
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compute_evidence(G, PreviousSolver).
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compute_evidence(G, PreviousSolver) :-
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catch(get_clpbn_vars(G, Vars), Ball, evidence_error(Ball,PreviousSolver)), !,
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store_graph(Vars), !,
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set_clpbn_flag(solver, PreviousSolver).
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compute_evidence(_,PreviousSolver) :-
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set_clpbn_flag(solver, PreviousSolver).
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get_clpbn_vars(G, Vars) :-
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% attributes:all_attvars(Vars0),
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once(G),
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attributes:all_attvars(Vars).
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evidence_error(Ball,PreviousSolver) :-
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set_clpbn_flag(solver,PreviousSolver),
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throw(Ball).
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store_graph([]).
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store_graph([V|Vars]) :-
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clpbn:get_atts(V,[key(K),dist(Id,Vs)]),
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\+ node(K, Id, _), !,
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translate_vars(Vs,TVs),
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assert(node(K,Id,TVs)),
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( clpbn:get_atts(V,[evidence(Ev)]) -> assert(evidence(K,Ev)) ; true),
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add_links(TVs,K),
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store_graph(Vars).
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store_graph([_|Vars]) :-
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store_graph(Vars).
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translate_vars([],[]).
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translate_vars([V|Vs],[K|Ks]) :-
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clpbn:get_atts(V, [key(K)]),
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translate_vars(Vs,Ks).
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add_links([],_).
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add_links([K0|TVs],K) :-
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edge(K,K0), !,
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add_links(TVs,K).
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add_links([K0|TVs],K) :-
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assert(edge(K,K0)),
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add_links(TVs,K).
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incorporate_evidence(Vs,AllVs) :-
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rb_new(Cache0),
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create_open_list(Vs, OL, FL, Cache0, CacheI),
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do_variables(OL, FL, CacheI),
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extract_vars(OL, AllVs).
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create_open_list([], L, L, C, C).
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create_open_list([V|Vs], [K-V|OL], FL, C0, CF) :-
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clpbn:get_atts(V,[key(K)]),
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add_stored_evidence(K, V),
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rb_insert(C0, K, V, CI),
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create_open_list(Vs, OL, FL, CI, CF).
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do_variables([], [], _) :- !.
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do_variables([K-V|Vs], Vf, C0) :-
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check_for_evidence(K, V, Vf, Vff, C0, Ci),
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do_variables(Vs, Vff, Ci).
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extract_vars([], []).
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extract_vars([_-V|Cache], [V|AllVs]) :-
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extract_vars(Cache, AllVs).
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%make sure that we are consistent
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check_stored_evidence(K, Ev) :-
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evidence(K, Ev0), !,
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Ev0 = Ev.
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check_stored_evidence(_, _).
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add_stored_evidence(K, V) :-
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evidence(K, Ev), !,
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put_evidence(Ev, V).
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add_stored_evidence(_, _).
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check_for_evidence(_, V, Vf, Vf, C, C) :-
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clpbn:get_atts(V, [evidence(_)]), !.
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check_for_evidence(K, _, Vf0, Vff, C0, Ci) :-
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findall(Rt,edge(Rt,K),Rts),
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add_variables(Rts, _, Vf0, Vff, C0, Ci).
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add_variables([], [], Vf, Vf, C, C).
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add_variables([K|TVs], [V|NTVs], Vf0, Vff, C0, Cf) :-
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rb_lookup(K, V, C0), !,
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add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
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add_variables([K|TVs], [V|NTVs], [K-V|Vf0], Vff, C0, Cf) :-
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rb_insert(C0, K, V, C1),
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create_new_variable(K, V, Vf0, Vf1, C1, C2),
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add_variables(TVs, NTVs, Vf1, Vff, C2, Cf).
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create_new_variable(K, V, Vf0, Vff, C0, Cf) :-
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node(K, Id, TVs),
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writeln(add:K:Id),
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get_dist(Id,_,Dom,CPT), !,
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{ V = K with p(Dom, CPT, NTVs) },
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add_stored_evidence(K, V),
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add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
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create_new_variable(K, V, Vf0, Vff, C0, Cf) :-
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node(K, Id, TVs),
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Id =.. [Na,Dom],
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Dist =.. [Na,Dom,NTVs],
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{ V = K with Dist },
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add_stored_evidence(K, V),
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add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
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put_evidence(Ev, V) :-
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clpbn:put_atts(V, [evidence(Ev)]).
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