请问 我现在希望设计海龟死后他的财产可以以一定的比例留给后代。这些海龟如果代表的是穷人则它死后(年龄大预期值)会生出3个孩子,其生前的财产的90%均分给其孩子。若海龟是富裕的,其死后有随机1~2个孩子,财产已70%均分。请问大家如果加到下述程序中怎么实现
% }" u3 T, i& o. e1 aglobals- o4 Y+ m+ k$ G5 }
[
1 i3 L* W4 o4 M6 K1 R' Q$ ?' q3 o max-grain $ @6 Y. r# m2 h
0 _: E" h/ U& j]
# X. K$ j2 |" e. l$ Y0 [4 |( @
. E5 j8 ^- v, L' O: d8 W3 z! }9 Gpatches-own4 S! c% \+ _; W' H( O: w, z$ F
[
) A! ]5 \4 g: ~5 P grain-here
) H# \% R/ B/ d! M; F* |2 [ max-grain-here - U9 F* D1 E+ {0 n) A; Y4 k7 P0 _4 J
]
0 L& z1 p+ C+ ]/ k' O- h- b5 m9 C; J5 I
turtles-own
: s% G. n, m$ O/ ?; t& }. G' {; W[
. _) `) z0 Y9 v& Q$ }) i. O* d1 J age
X: j6 [1 U. `- @: p wealth
0 h$ d* E7 U1 M( A7 I life-expectancy : y, w0 }( I1 e" H0 m8 y
metabolism
5 u! |3 l( l& w8 j! G# s vision
5 [0 m M- h2 p! o( m+ o$ `# H% u; V inherited 0 m9 Z; v7 U1 [- {# O: d
]- s7 H7 T1 P( s5 ^. J" ]& ~5 \! {
; S% k+ ` l* E& p5 g3 o. ?7 o
6 ^$ b- x& t( [2 |5 oto setup
6 d" m6 h' A* E5 X9 O ca
8 C0 m* I& D' }3 g. ` set max-grain 50* N; g. R1 ^2 u' b( G" _
setup-patches
+ m, G/ A* L5 H& D0 w setup-turtles9 _: B4 P: C- N4 k
setup-plots
& u% R6 V- y2 q update-plots
% Z! q7 c( F+ s0 M$ ~1 ^end' E6 v% Q8 `1 X0 C- ^- ^) m
to setup-patches
+ E; [4 L" H0 c/ b* C9 ? ask patches$ {- `( m/ K: S: D
[ set max-grain-here 09 e1 [4 | h4 e
if (random-float 100.0) <= percent-best-land
7 H% o1 c3 K0 U `( S [ set max-grain-here max-grain. N `- H8 `0 ?8 ?' u. W2 o+ m: B
set grain-here max-grain-here ] ]6 i# ~0 g2 S2 B7 a* B0 G5 f6 s5 m
repeat 5
9 \0 {7 A% A5 N3 r [ ask patches with [max-grain-here != 0]
$ `0 v7 _9 e# t' i [ set grain-here max-grain-here ]% R8 @4 j: o; s7 b9 W+ D
diffuse grain-here 0.5 ]
6 F7 U8 B, t( f/ g: { F% [ repeat 10
: S: W* |- R: s, Z& L. ` [ diffuse grain-here 0.5]
! z+ h) h: Z% j7 N$ y) H* Q' t ask patches
5 @" ? o: Q$ `' }5 o$ Q! i [ set grain-here floor grain-here # G0 m" {/ y" w6 V$ M/ I
set max-grain-here grain-here
- O( K ]% X p, [3 v% A/ [/ | recolor-patch ]
+ Q1 w8 `) _ s! S1 Xend
- S( d! C! B" U/ Q% gto recolor-patch R8 {2 s& S$ d6 s
set pcolor scale-color sky grain-here 0 max-grain; N9 G2 \' k6 `% E, O
end4 G1 C; N5 q( w2 A" N* p3 H z
to setup-turtles' b! c$ L$ C7 A I: j" X( [' k
set-default-shape turtles "person"
! S q4 A0 N0 ?8 ?% I crt num-people
" F: R; E9 d5 Y) N3 I* E [ move-to one-of patches $ B% d1 F3 Y" ^: d% _
set size 1.5 5 S& b* C4 d* W1 w
set-initial-turtle-vars-age
! L' o- |5 v; _, Y/ [4 J% S" @ set-initial-turtle-vars-wealth3 x: a6 ~0 G0 `& X' H3 K8 @
set age random life-expectancy ]4 U0 _# k) D8 e9 M5 ]) I
recolor-turtles
( ]5 l- z- y* [end
. R g6 a+ U* S- ]( T. [# x: Q; d; n: s0 G k3 o8 l
to set-initial-turtle-vars-age
# n. C/ T/ |. m6 i& t. m) M let max-wealth max [wealth] of turtles
6 v" ~5 y ]3 o9 F$ u
! Z1 G: Z! K: t3 B ifelse (wealth <= max-wealth / 3)+ f- C) J y1 \. ^' i9 E
[ set color red 6 c" s+ p1 s* C
set age 0
3 t" h1 O/ G1 I) | ` face one-of neighbors4
6 }' x$ ]" _0 A. F3 K& P! { set life-expectancy life-expectancy-min +$ |8 J% T# w" u L# |
random life-expectancy-max - M3 @' E% T/ P" B7 f
set metabolism random 1 + metabolism-low5 P* @9 S) T h6 ]8 ?1 e7 X
set wealth metabolism + random 30. m% d! W1 s/ h
set vision 1 + random max-vision* R" h7 P+ O' w0 z
set wealth wealth + Wealth-inherited-low ]3 m { b7 H- c$ i1 f1 Y
[ ifelse (wealth <= (max-wealth * 2 / 3))
, B' ]/ ]. n& K4 x0 M7 s9 Z0 I2 H) K [ set color yellow ; x* t! k7 x. _) I! W) P$ B
set age 02 P/ r* p4 A, u0 b* a' l) Z! u
face one-of neighbors4 2 G% J7 b6 H/ y6 Q: ^ N/ ^
set life-expectancy life-expectancy-min +
- ^- R! c+ r, A/ c5 r% R/ Y; n5 G random life-expectancy-max + 1
" b0 _! r( x' ]3 r; { set metabolism 1 + random metabolism-mid
, @2 a) |( F# b! T. {9 X, b6 E) a set wealth metabolism + random 30" N2 O7 k. D# f! K% i- Q
set vision 3 + random max-vision% K1 n s5 b# B, V9 M
set wealth wealth + Wealth-inherited-mid]$ u2 I0 A+ E4 j& h) G" ^8 _
[ set color green ! A4 N/ p' t9 Y; P
set age 0
( b; W+ s& Z& r face one-of neighbors4
9 U, s* c' u( t; i. ?6 w& I set life-expectancy life-expectancy-min +
: z9 f% ]. S) N+ n8 j* [; j random life-expectancy-max + 2
. _9 R* ?- r+ j! O/ Q set metabolism 2 + random metabolism-up
6 J, c* b1 Y" H {& e set wealth metabolism + random 30
" X% I: W8 v9 O5 r set vision 3 + random max-vision
' R' L a: I) h9 ?! m) V% k/ O set wealth wealth + Wealth-inherited-up ] ] X; e& b: o# L# b7 Q4 ^
1 {7 ^: V+ b. K, x; s/ jend, {% Y( n% u% ~$ _5 c' B$ Z" N* d
to set-initial-turtle-vars-wealth
; e; M$ Z" [. j. D- m7 Q+ B, ^; U let max-wealth max [wealth] of turtles, w3 k% ]! g3 `) M, o; m2 B- F# r
set age 0
+ l8 g8 r* J T; D face one-of neighbors4 # ?, @; F, P4 N- B
set life-expectancy life-expectancy-min +
: p1 G! V" c4 Q) ], h/ w, R2 s random life-expectancy-max - D3 @6 J/ I" Y4 F3 y! z% J4 D
set metabolism 1 + random metabolism-up/ z- d' I# m! z) V% c# Z' z& F
set wealth metabolism + random 30& Y" ]. z3 u9 R& o+ j
set vision 1 + random max-vision 6 [( S; y+ M. _0 V: }8 }
end0 c8 @' b: _3 g, [; F- }+ X x
to redistribution
, Q: w* a4 q2 Y- w' @let max-wealth max [wealth] of turtles
/ g& P, r8 \3 B3 v* W. @let min-wealth min [wealth] of turtles u1 K( `% f+ `8 v" K4 m! n
if (wealth <= max-wealth / 3)* K2 |) v6 Q ]- X* h
[set wealth wealth + Low-income-protection ]
4 D# _' b J+ g/ L, Jend) ?& I6 w3 c/ H; a3 [" _
0 c4 [1 q0 I& E; N1 Kto recolor-turtles% `- G5 h) m; ~6 _, K9 d' N7 R O& J
let max-wealth max [wealth] of turtles
! G, Z/ z [) ?" n2 L ask turtles
- o5 v( A! {7 ^ [ ifelse (wealth <= max-wealth / 3)- R5 i/ @% q2 x5 T2 o# b7 R# a+ O+ O
[ set color red ]
% ^9 C" E7 D! y: F: g% s) Z [ ifelse (wealth <= (max-wealth * 2 / 3))
: E) X" S1 H, p/ a& p; Z9 S! X [ set color yellow ]
1 n% V" f! N* x; O$ c4 a [ set color green ] ] ]: W8 Z ~8 c$ k7 K+ b
ask turtles [ifelse show-wealth?2 }% n+ d4 ~* ~8 v* ]
[ set label wealth ]
1 N' w' ^, y" ]4 q1 w9 M3 U/ D1 h3 I [ set label "" ]]* `* w8 ~! f& d4 ^& T
end
, u: H0 G! {# y |, ]' e3 C5 ~3 v$ W' v5 {* }' ]7 Z8 d3 i1 I
to go: W6 R8 X- V2 H* T; J
ask turtles
6 s- W# M0 x- d2 F. ^- m [ turn-towards-grain ]
/ v; y. @& h. U* B8 Z harvest
( X# y* I! h) O, V( {# I; r4 o5 g, D ask turtles
: T* t! g5 e- Y* G [ move-eat-age-die ]
# a% _1 |$ i6 V) A! d+ C recolor-turtles# z/ E# C% ~% |: r; Z* T+ _
if ticks mod grain-growth-interval = 0
7 \6 T3 q8 X. u7 k3 } [ ask patches [ grow-grain ] ]
# W n1 @4 m* c" E: q
, e! _" K( {+ m. E2 | if ticks mod 11 = 0
8 |8 \7 j; I: v2 R [ask turtles
! i; Z! Z% L5 I7 i [ redistribution ]]* B/ e: z& J+ X
if ticks mod 5 = 0
0 f6 L2 s+ n2 K( w. l; h [ask turtles. H9 z* C& f* i8 Y1 g
[ visions ]]
3 X# c4 j8 ?2 ~ tick
3 i: p7 I# J; M j update-plots
( _0 J2 N. G0 j* c5 Zend5 l0 V% N; t; |0 W! v- d
to visions
! U( \: T5 U _5 N0 f! A& T set vision vision + 1 # a; x$ ? b3 A2 W$ a7 ^7 H6 f- m
end
9 Y$ {4 j1 g/ b0 b- s
! |" i! W' e. A0 s) \
% o1 j: z. L# ^; G, Y4 k3 M" @/ K) p) i
to turn-towards-grain
( |# x, f* _- T' @ set heading 07 r+ s' N, p3 b+ h) y! z8 |
let best-direction 0
# G4 x) P+ [! n let best-amount grain-ahead3 _; l4 p$ `9 \0 w- B) n" H+ {
set heading 904 u1 F5 o) b. ~4 k/ g U$ r
if (grain-ahead > best-amount)
7 _( |$ h: f- w, u- S! w [ set best-direction 903 q. h* p/ s' Z7 q8 N+ A) T* t
set best-amount grain-ahead ]
9 ~. E; X) b% w) \1 Q set heading 180. Q9 K! |$ }: I/ c$ a- x
if (grain-ahead > best-amount)+ t9 R' F0 t+ ]# j+ F$ e
[ set best-direction 1806 O- c4 a/ o' H2 N
set best-amount grain-ahead ]. G7 J G ~2 {8 B
set heading 2708 \, x7 W+ z" I! w4 C
if (grain-ahead > best-amount)
- f: P$ Q1 N, I [ set best-direction 270' g6 q) w8 Y G4 H
set best-amount grain-ahead ]' }. C3 Y9 C& n- `
set heading best-direction
! V5 U M4 c lend
0 B& g5 [. ?+ l4 p" ?# n" r- z$ ~8 \+ e" s$ u* f5 y
/ b: X4 M2 T% D# \* n" X ]) x0 {to-report grain-ahead
2 W$ m% e/ N& y# A2 C let total 0' {/ Z( y7 ?5 s" Z' ?" l+ A
let how-far 1
( g8 u- p5 e+ T4 y+ _' g9 k0 _; A repeat vision
1 _9 ~# s9 g" [ [ set total total + [grain-here] of patch-ahead how-far
( y* s4 Y9 v4 P8 }1 G set how-far how-far + 1 ]
, V# O6 T1 ]1 ]9 X/ W report total
# H$ M, Z. l7 {* F/ l/ Tend
- Z* q' c4 w. B+ R7 t G) ^3 y+ P- i$ j
to grow-grain
6 ~0 O( K* x: `/ m0 E8 j if (grain-here < max-grain-here)0 c; N( d3 x: E( T* D" ^! U
[ set grain-here grain-here + num-grain-grown. S! m' d0 f/ @3 r
if (grain-here > max-grain-here) / g6 U) ]9 R% G/ Z# B
[ set grain-here max-grain-here ]
" q' L7 r7 d' R) g& X- E, ~( r, ? recolor-patch ]. ^" C3 @1 `8 g5 l! T g! A
end a4 C, B6 m" w8 {* u
to harvest
% i3 I- K& @9 p" k3 W ask turtles, u/ X' _1 I9 a, Y1 m$ w
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
1 H4 s/ A+ ~' i$ m/ @: O ask turtles1 b9 h6 t8 O4 d2 |4 p; @6 v
[ set grain-here 09 C. X8 J! d4 ~# E
recolor-patch ]
' g9 g7 Y6 ^" N6 [$ F, U 1 A2 ~! Q9 e, B4 s
end
% \% ` i+ i, U' |, m7 H$ v% I1 ^3 U1 N- `& n" ?" K) a/ Z
to move-eat-age-die
: k0 [+ s) ~* m! O& m7 l8 { fd 1, G6 z; Y( ~' o( w
set wealth (wealth - metabolism)
% e+ m$ o' b/ D# E5 k set age (age + 1)
K k+ h$ i# R2 j5 c7 S7 y if (age >= life-expectancy)8 r; w: }; T# u2 r2 n2 I
[ set-initial-turtle-vars-age ]
+ G4 r( ^& b3 `& F2 {+ y if (wealth < 0)5 D/ Q' W0 T6 r
[ set-initial-turtle-vars-wealth ]
% Q, ?( A* J0 E" y
0 x) F+ ~1 A8 Oend
$ q a& ~' e0 F V% J' ?( Q% P
& U9 L" v! }2 `; H# {! T: i+ e# A/ A; G4 ]2 B% g
to setup-plots2 o \8 V# h F: ?
set-current-plot "Class Plot"
) n# h# I, C+ p set-plot-y-range 0 num-people7 I* L* O: n) K2 h% L, y
set-current-plot "Class Histogram"
- B9 J& S3 b( t8 m7 n set-plot-y-range 0 num-people' G4 N3 m9 k" x
end
& {6 r7 y8 q2 V$ v& }6 k# H" W- e% h* N" F- A3 G* J! W* ]
to update-plots& Q+ F* g. i0 W `5 @$ P
update-class-plot
" h) D0 L7 T6 ~1 j1 b$ F; ?. p update-class-histogram3 X y9 L$ E& c" R
update-lorenz-and-gini-plots
; j/ z" O& X, cend
' K$ Q" f" ?% j' w6 F
; G- m" J. v0 G R8 o& @$ Uto update-class-plot
+ k1 D1 N1 K: |1 B set-current-plot "Class Plot"+ P& z' g2 g2 H7 g9 D
set-current-plot-pen "low"
5 `( @0 x7 a9 u- S; t1 Y6 A plot count turtles with [color = red]
- i( k- [* A) e, e set-current-plot-pen "mid"
* F1 ?/ r: d: b* C! ] plot count turtles with [color = yellow]
$ {5 W( w2 f5 h6 o set-current-plot-pen "up"
0 T$ P {% H: y8 v/ D- M plot count turtles with [color = green]
7 b4 Y3 j1 V8 w4 S! }end0 x0 L) |' i8 a
4 p/ |+ E( l8 w9 K% Z
to update-class-histogram+ B, {- U3 r* p/ l6 N5 E2 b" g
set-current-plot "Class Histogram"
! f: V5 N5 }* r0 k/ Y% k+ C plot-pen-reset
; b- y* O* E# L- b set-plot-pen-color red
' F4 q; \$ ]* j) l( _ plot count turtles with [color = red]
& ^( v# V2 K9 Y" m; {/ M' z2 t$ k7 U set-plot-pen-color yellow! m" p1 `# a; D' U1 N
plot count turtles with [color = yellow]. n$ E6 \; d! n9 f
set-plot-pen-color green* }0 ^! c/ o l4 b4 s, S; Q
plot count turtles with [color = green]
8 D. d! ?3 @( @# h* h5 ~end# G4 D) A+ @( R7 m+ z$ k5 v. S5 M
to update-lorenz-and-gini-plots: Y0 l ]" a* t' v v: l2 y5 n% T+ B; @
set-current-plot "Lorenz Curve"
& {1 ^2 a) @! U/ K9 }% ?" m4 p clear-plot# t: m* c6 i& J3 \# P
" ~+ i% D7 b/ p; x
set-current-plot-pen "equal"
0 @% D2 \. x/ i" s plot 0
. ^' P( V( o8 b c/ [ plot 100; l6 t, T& ~0 T8 A! f
! a3 c8 I6 ~4 L; k/ _" C set-current-plot-pen "lorenz"
% w$ F: Z# _" g6 Z set-plot-pen-interval 100 / num-people5 P! B4 _5 h6 F
plot 0- `$ g: _! P3 S# o5 B: t
! _+ V0 G5 G6 ?1 G! Q9 x1 u
let sorted-wealths sort [wealth] of turtles
- L' J" U7 m, C u; c let total-wealth sum sorted-wealths, J. r- K: Q3 } y0 T
let wealth-sum-so-far 0; Y" P N+ y& _$ f$ F! F$ m$ E
let index 0
5 H' d/ c; ?3 l4 |' a let gini-index-reserve 0
- \! r9 w! l* `/ S1 S
; F" e/ ?1 _7 l1 E9 O) Q repeat num-people [& }& T! a! X( p% a& [. G" s
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
7 \3 u9 E5 _; a plot (wealth-sum-so-far / total-wealth) * 100
, B, ]# @' t( w1 ] set index (index + 1)
: e- b3 q3 _+ U$ g set gini-index-reserve
& a. }& Z. N! _* |& s* I) x8 w gini-index-reserve +
9 N0 S0 q2 W e# N9 b (index / num-people) -
7 ]# U. t0 u! f' X. S7 u0 K* p. C+ [ (wealth-sum-so-far / total-wealth)
3 ?5 |0 x6 h% R2 f5 T ]
) ~; d" J% F( o6 U$ M2 z. v! k& p( s; I' R" x) ]
set-current-plot "Gini-Index v. Time"
) j5 m4 M. |% b! N1 `3 k. N4 w j" d plot (gini-index-reserve / num-people) / area-of-equality-triangle
l; k1 J( i! Uend4 k3 t' ?) D) V; q
to-report area-of-equality-triangle
" S- T! e; S7 n; Q report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
! x+ [: C) `+ Gend |