% Zeus Large Scale Demonstrator rules in the language of JavaAS v0.4.
% created-by: mjs (matthew.south @ cancer.org.uk)
% created-on: 27th September 2006
%------------------------------------------------------------------------------------------------------
% customer data
%------------------------------------------------------------------------------------------------------

% All customer data is represented using binary terms where the first argument is the Company ID

customer(1, new).       % customer status : {new, existing}
business(1, existing).  % business status : {new, existing}
lmto(1, 250).           % last month turnover (1000's EUR)
smto(1, 1500).          % six month turnover (1000's EUR)
oyto(1, 3500).          % one year turnover (1000's EUR)
capital(1, 9).          % starting capital (1000's EUR)

customer(2, new).
business(2, existing).
lmto(2, 450).
smto(2, 750).
capital(2, 60).
history(2, bad).        % credit history : { good, average, bad }

customer(3, existing).
business(3, new).
lmto(3, 300).
capital(3, 5).
history(3, bad).

customer(4, existing).
business(4, new).
lmto(4, 125).
smto(4, 800).
oyto(4, 4500).
capital(4, 8).
history(4, good).
limit(4, 25).           % credit limit (1000's EUR)

customer(5, existing).
business(5, new).
lmto(5, 500).
smto(5, 600).
capital(5, 65).
history(5, bad).
limit(5, 400).

customer(6, existing).
business(6, new).
lmto(6, 90).
capital(6, 3).
history(6, good).

customer(7, new).
business(7, new).
lmto(7, 115).
smto(7, 500).
oyto(7, 1200).
capital(7, 4).
history(7,bad).
limit(7, 104.5).

customer(8, new).
business(8, new).
lmto(8, 105).
smto(8, 1900).
capital(8, 56).
history(8, average).

business(9, new).
lmto(9, 95).
capital(9, 75).
history(9, good).

customer(10, existing).
business(10, existing).
lmto(10, 310).
smto(10, 600).
oyto(10, 3200).
capital(10, 80).
history(10, good).

customer(11, existing).
business(11, existing).
lmto(11, 100).
smto(11, 500).
oyto(11, 1600).
capital(11, 30).
history(11, average).
limit(11, 56).

customer(12, existing).
business(12, existing).
lmto(12, 100).
smto(12, 300).
oyto(12, 1500).
capital(12, 65).
history(12, bad).
limit(12, 70).

customer(13, existing).
business(13, existing).
lmto(13, 140).
smto(13, 900).
oyto(13, 2000).
capital(13, 11).
history(13, average).

%------------------------------------------------------------------------------------------------------
% status rules
%------------------------------------------------------------------------------------------------------

% qlmto - qualitative last month turnover : {bad, average, good}
[qlmto1(Company)] qlmto(Company, good) <- lmto(Company, LMTO), >=(LMTO, 250).
[qlmto2(Company)] qlmto(Company, average) <- lmto(Company, LMTO), <(LMTO, 250), >(LMTO, 125).
[qlmto3(Company)] qlmto(Company, bad) <- lmto(Company, LMTO), =<(LMTO, 125).

% qsmto - qualitative six month turnover : {bad, average, good}
[qsmto1(Company)] qsmto(Company, good) <- smto(Company, SMTO), >=(SMTO, 1500).
[qsmto2(Company)] qsmto(Company, average) <- smto(Company, SMTO), >(SMTO, 750), <(SMTO, 1500).
[qsmto3(Company)] qsmto(Company, bad) <- smto(Company, SMTO), =<(SMTO, 750).

% qoyto - qualitative one year turnover : {bad, average, good}
[qoyto1(Company)] qoyto(Company, good) <- oyto(Company, OYTO), >=(OYTO, 3000).
[qoyto2(Company)] qoyto(Company, average) <- oyto(Company, OYTO), <(OYTO, 3000), >(OYTO, 1500).
[qoyto3(Company)] qoyto(Company, bad) <- oyto(Company, OYTO), =<(OYTO, 1500).

% qcapital - qualitative starting capital : {low, average, high}
[qcapital1(Company)] qcapital(Company, high) <- capital(Company, Capital), >=(Capital, 60).
[qcapital2(Company)] qcapital(Company, average) <- capital(Company, Capital), <(Capital, 60), >(Capital, 10).
[qcapital3(Company)] qcapital(Company, low) <- capital(Company, Capital), =<(Capital, 10).

% status - credit status is the ratio of lmto/limit.  The idea is that it shouldnt exceed 0.6.
[status1(Company)] status(Company, Status) <- limit(Company, Limit), lmto(Company, LMTO), product(LMTO, Status, Limit).

%------------------------------------------------------------------------------------------------------
% business rules
%------------------------------------------------------------------------------------------------------

[increase(Company)] change(Company, 10) <- history(Company, good).
[decrease(Company)] change(Company, -10) <- history(Company, bad).

%------------------------------------------------------------------------------------------------------
% specialised business rules
%------------------------------------------------------------------------------------------------------

[a1(Company)] change(Company, 10) <- qlmto(Company, good), qsmto(Company, bad) 0.8.
[a4(Company)] change(Company, 10) <- qlmto(Company, average), qsmto(Company, good) 0.8.
[a6(Company)] change(Company, 10) <- qlmto(Company, bad), qsmto(Company, good), lmto(Company, LMTO), smto(Company, SMTO), is(S, *(SMTO, 0.6)), >(S, LMTO) 0.8.
[a9(Company)] change(Company, -10) <- qlmto(Company, bad), qsmto(Company, bad), qoyto(Company, bad) 0.8.

[b1a(Company)] change(Company, 10) <- qsmto(Company, bad), qoyto(Company, good), smto(Company, SMTO), oyto(Company, OYTO), is(S, *(SMTO, 0.7)), >=(OYTO, S) 0.6.
[b1b(Company)] change(Company, 0) <- qsmto(Company, bad), qoyto(Company, good), smto(Company, SMTO), oyto(Company, OYTO), is(S, *(SMTO, 0.7)), <(OYTO, S) 0.6.
[b2a(Company)] change(Company, 0) <- qsmto(Company, average), qoyto(Company, good), oyto(Company, OYTO), smto(Company, SMTO), is(S, *(SMTO, 0.5)), =<(OYTO, S) 0.6.
[b2b(Company)] change(Company, 5) <- qsmto(Company, average), qoyto(Company, good), oyto(Company, OYTO), smto(Company, SMTO), is(S, *(SMTO, 0.5)), >(OYTO, S) 0.6.
[b3(Company)] change(Company, 10) <- qsmto(Company, good), qoyto(Company, good) 0.6.
[b4(Company)] change(Company, -10) <- qsmto(Company, good), qoyto(Company, bad) 0.6.
[b5(Company)] change(Company, -10) <- qsmto(Company, bad), qoyto(Company, bad) 0.6.
[b6(Company)] change(Company, -10) <- qsmto(Company, bad), qoyto(Company, good) 0.6.

[c1(Company)] change(Company, 10) <- qoyto(Company, good), qcapital(Company, average) 0.4.
[c2(Company)] change(Company, -10) <- qoyto(Company, bad), qcapital(Company, average) 0.4.
[c3(Company)] change(Company, 10) <- qoyto(Company, good), qcapital(Company, high) 0.4.
[c4a(Company)] change(Company, 0) <- qoyto(Company, average), qcapital(Company, high) 0.4.
[c4b(Company)] change(Company, 0) <- qoyto(Company, average), qcapital(Company, average) 0.4.
[c5(Company)] change(Company, -10) <- qoyto(Company, bad), qcapital(Company, high) 0.4.
[c6a(Company)] change(Company, 10) <- qoyto(Company, good), qcapital(Company, low) 0.4.
[c6b(Company)] change(Company, 10) <- qoyto(Company, average), qcapital(Company, low) 0.4.
[c7(Company)] change(Company, -10) <- qoyto(Company, bad), qcapital(Company, low) 0.4.
[c8(Company)] change(Company, 5) <- business(Company, new), qcapital(Company, high) 0.4.    % These three rules are re-written. It's awkward to capture 
[c9(Company)] change(Company, 0) <- business(Company, new), qcapital(Company, average) 0.4. % "oyto doesnt exist", but if a company is new, then they dont 
[c10(Company)] change(Company, -5) <- business(Company, new), qcapital(Company, low) 0.4.   % have an oyto, so this premise is used instead. 

%------------------------------------------------------------------------------------------------------
% limit is capped to 60% of lmto
%------------------------------------------------------------------------------------------------------
[cap(Company)] ~change(Company, Percentage) <- 
	lmto(Company, LMTO),
	product(LMTO, 0.6, TheoreticalLimit),
	sum(100, Percentage, Result),
	product(100, Multiplier, Result),
	limit(Company, ActualLimit), 
	product(ActualLimit, Multiplier, NewLimit),
	>(NewLimit, TheoreticalLimit). 

%------------------------------------------------------------------------------------------------------
% arithmetic rules - standard prolog constructions.
%------------------------------------------------------------------------------------------------------

sum(X, Y, Z) <- nonvar(X), nonvar(Y), is(Z, +(X, Y)).
sum(X, Y, Z) <- nonvar(X), nonvar(Z), is(Y, -(Z, X)).
sum(X, Y, Z) <- nonvar(Y), nonvar(Z), is(X, -(Z, Y)).

product(X, Y, Z) <- nonvar(X), nonvar(Y), is(Z, *(X, Y)).
product(X, Y, Z) <- nonvar(X), nonvar(Z), is(Y, /(Z, X)).
product(X, Y, Z) <- nonvar(Y), nonvar(Z), is(X, /(Z, Y)).