%% Backward chaining

-module(backward).
-export([start/0,mainLoop/0,solveGoal/2,solveRule/2,collect/3]).

start() ->
    %% Initialize KB
    ets:new(rules, [bag, named_table]),
    ets:insert(rules, {g,[d,e,f,h,i,j],1.0}),
    ets:insert(rules, {g,[a,b,c],1.1}),
    ets:insert(rules, {a,[],0.1}),
    ets:insert(rules, {b,[],0.2}),
    ets:insert(rules, {c,[],0.3}),
    ets:insert(rules, {d,[],0.4}),
    ets:insert(rules, {e,[],0.5}),
    ets:insert(rules, {f,[],0.6}),
    ets:insert(rules, {h,[],0.7}),
    ets:insert(rules, {i,[],0.8}),
    ets:insert(rules, {j,[],0.9}),
    mainLoop().

mainLoop() ->
    Query = io:read("Enter query: "),
    solveGoal(element(2, Query), self()),
    receive
        {_, Truth} -> io:format("Answer is: ~w~n", [Truth])
    end,
    mainLoop().

solveGoal(Goal, Caller) ->
    %% Fetch rules...
    ApplicableRules = ets:match(rules,{Goal, '$1', '$2'}),
    lists:foreach(
        fun([RuleBody,Truth]) ->
        if
            %% If RHS is null
            RuleBody == [] -> Caller ! {Goal, Truth};
            %% If RHS contains subgoals
            true -> spawn(backward, solveRule, [RuleBody, self()])
        end end,
        ApplicableRules),
    receive
        %% Each message is of the form {goal,truth}
        %% Just accept the 1st answer
        {_, Truth} -> Caller ! {Goal, Truth}
    end.

solveRule(RuleTail, Caller) ->
    N = length(RuleTail),
    Collector = spawn(backward, collect, [[], N, Caller]),
    %% For each subgoal in Rule
    %% Spawn a process to solve each subgoal
    lists:foreach(
        fun(Subgoal) -> spawn(backward, solveGoal, [Subgoal, Collector]) end,
        RuleTail).

%% Accumulate results
collect(Truths, N, Caller) ->
    %% If we have N messages send back the answer
    %% Answer = min of truth values, equivalent to fuzzy-logic AND
    if length(Truths) == N -> Caller ! {dont_care, lists:min(Truths)};
       true -> true
    end,
    receive
        {_, Truth} -> collect([Truth | Truths], N, Caller)
    end.