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
! }% t& u: L" A4 z1 bglobals7 F% X, X; `% n
[
9 O/ X5 ^5 M$ o1 E6 B8 L7 {* I max-grain 2 S. L2 \: [9 Y
! h7 c& ?" ?( o. B# M
]
2 }$ Z/ _) p ]' h w& |$ S
. B/ R, W6 j* v7 Q# Ipatches-own
' y( n) w- H" J) p[
3 }* K! R/ R- y: \ grain-here
0 \8 [7 j" d# W5 U8 A7 f4 p max-grain-here 8 w; J" ]$ O) p+ K; W( Z$ h! t1 N
]3 R: f) c( Y- i9 B) v
$ ?3 \3 n) @' I& D! U6 w% Z
turtles-own! I; V; u' ?* U$ t$ n3 x, c
[" P+ h: J( j" |: m
age
' B, v- I% G) J- I& g4 s wealth
8 t( b" v/ H; j# ?2 c( j3 J life-expectancy
! ~" m& d% R1 ^ metabolism
' {. a4 P# e8 g6 |" v vision, E: M9 T( M: {4 M
inherited
9 f# o+ y. o9 x3 @]5 {- ?9 Q9 t3 @
$ [3 A# j% Z6 {! T1 P/ i
5 r* a, S1 g4 A, r. \to setup7 k7 H/ z0 Z6 k0 O) r; @" P
ca
' l9 U6 ~% y5 x& M set max-grain 50
& w+ \8 H+ o5 g: O2 Y! r setup-patches5 \8 j* {" P* Q/ u4 {
setup-turtles
2 r4 x: k- a, v# t J; f$ Q) q, e setup-plots
+ p. ?3 s, \/ N% y update-plots
. x: Y# {; Q t0 [0 send+ U3 ?5 e2 m& y8 Q& o* M
to setup-patches
$ u. ?4 t" A$ s, T) H ask patches/ o1 p( _1 \7 g6 d
[ set max-grain-here 0% q/ u/ |. X; p% x1 a9 ^
if (random-float 100.0) <= percent-best-land
! n1 j2 h- H& ^% h, C0 j [ set max-grain-here max-grain
$ s( r% z( c4 Z/ A set grain-here max-grain-here ] ]$ b. [3 _, h. ^5 X' K# \5 o
repeat 5. G- Z* m8 \. x
[ ask patches with [max-grain-here != 0]7 C! u* U$ G; E1 o2 R, [
[ set grain-here max-grain-here ]
9 I7 A+ t% k) E2 | `# l diffuse grain-here 0.5 ]
3 K3 H; W- q4 J3 _ {4 g repeat 103 d/ g' V* {9 q# L5 K
[ diffuse grain-here 0.5] ( S$ m B. ~0 i6 ]8 f
ask patches
j. Y4 d' k2 o t7 x3 n [ set grain-here floor grain-here - s9 k& a3 J( Y' C- C9 s
set max-grain-here grain-here 8 x* W B- G5 Z) D& Y: b; o
recolor-patch ]) _* h' A6 t9 d% g
end
# M; Q( N/ Q, |* j0 Q+ Sto recolor-patch 8 B* F- t( o. {% ~7 A
set pcolor scale-color sky grain-here 0 max-grain( a+ O0 i: i1 l, b" `7 b, J' E
end& w: b# w8 O8 Y% ]
to setup-turtles/ K) {. ?6 p# T
set-default-shape turtles "person"! X* w: y" p' S* I0 \2 Q
crt num-people( n+ W. r1 r2 e" \
[ move-to one-of patches 2 r' T$ J \7 E, L
set size 1.5 1 c/ \# k$ C+ a6 t
set-initial-turtle-vars-age8 @) S3 W2 D- |
set-initial-turtle-vars-wealth5 D) C* g0 P, ~, Q+ M. C
set age random life-expectancy ]5 b1 b& h/ g* v3 A
recolor-turtles
" a2 t- a/ v& V5 W# c" k& b( w9 C6 mend, b1 l# G2 y) y
2 f J8 X e, w! Y/ p* zto set-initial-turtle-vars-age
% g! p' B( a: f let max-wealth max [wealth] of turtles" z2 f5 `- m# K% {+ _4 F5 ?
. b; k9 {" r& F
ifelse (wealth <= max-wealth / 3)+ W8 x s4 S2 k4 ^" h& d3 C& h2 i- k
[ set color red
( u" |) i# Y4 F set age 0/ H; m' C+ l; W9 m5 l2 Y E
face one-of neighbors4
. @ P# e3 R) c& y set life-expectancy life-expectancy-min +2 A) f, T0 u/ P4 |
random life-expectancy-max
' m" J# s4 w2 I4 W( C2 q. p; d set metabolism random 1 + metabolism-low+ U1 a' `( R; {1 {% `
set wealth metabolism + random 30( D7 r5 R, n' a$ s4 E) }: T1 L
set vision 1 + random max-vision+ j! d& b/ ?' a( \1 x! O
set wealth wealth + Wealth-inherited-low ]+ M/ `9 D( p. V5 k; l
[ ifelse (wealth <= (max-wealth * 2 / 3))
* {! z7 {1 |0 G+ J) {: C: d [ set color yellow
" H8 d. {2 h, N. S6 [/ J- i" e set age 0: s7 i+ B+ R) a& ~
face one-of neighbors4 5 W& m9 o j& f" P7 t3 Q0 ~
set life-expectancy life-expectancy-min +
# q C: Q) [% P0 O2 [ random life-expectancy-max + 1
5 `* q- x3 }$ o* p set metabolism 1 + random metabolism-mid
; \1 w, }% h7 X4 j& }- j set wealth metabolism + random 30
- E+ |1 F5 J% ?* K# E set vision 3 + random max-vision8 F) Z% m! n" T# G# J
set wealth wealth + Wealth-inherited-mid]5 p% b* }" E& T K; G- {) ?* D
[ set color green
* W) h6 l- y! f set age 0+ ~1 P6 K, Y8 r6 E: K3 s2 c q
face one-of neighbors4 " g$ |& _% f5 y. ]2 S) m
set life-expectancy life-expectancy-min +/ q6 {; M- W r# b- D6 v
random life-expectancy-max + 25 ` C5 U, n/ `
set metabolism 2 + random metabolism-up7 j! K Y6 m$ C" [6 w4 s
set wealth metabolism + random 30
2 @" R7 x& w' _' {% i set vision 3 + random max-vision1 W# X. U+ S9 \3 r" X) z$ T! K
set wealth wealth + Wealth-inherited-up ] ]
# j1 Q: ^8 h! ^( }
& a' [" {. L9 _' q2 W" \, _end
7 n4 }" E* m+ I1 V0 `$ ^' |( y. cto set-initial-turtle-vars-wealth
5 M0 ]6 [! \! O9 d4 P let max-wealth max [wealth] of turtles
2 L9 f1 Q" i; ~; y( e2 L* U set age 0
/ _8 C1 \" N# B& C# u) H. ~ face one-of neighbors4 7 Q. ~/ L4 Y0 h6 i3 E5 ]# G
set life-expectancy life-expectancy-min +. ?/ g' t$ I$ F+ x& `
random life-expectancy-max - y+ J+ m7 ^: G5 j. }0 t* [
set metabolism 1 + random metabolism-up, _8 J4 o* q( q
set wealth metabolism + random 30
- v6 `& m9 Y% j- ]. x* N set vision 1 + random max-vision * c; \; m" G5 @) {
end
4 C6 z4 k) I" Jto redistribution* s8 q% E" r9 H# Q: W$ s& Z
let max-wealth max [wealth] of turtles& W6 _+ Q( p& ^
let min-wealth min [wealth] of turtles
, H( B3 j7 \& Q) u6 Q+ Tif (wealth <= max-wealth / 3)
' k1 O! |6 s; \5 `: g! F4 _ [set wealth wealth + Low-income-protection ]$ W t3 I) p& N0 F" c; g# r
end; f( r9 V7 _+ U5 A6 P5 R3 v* G3 N
: N- Y' ?; p2 }* k1 ]# I/ A5 Z
to recolor-turtles
3 U9 D6 k# Q+ K9 Y7 o) z let max-wealth max [wealth] of turtles. x0 I7 Y0 L* x# |1 `8 P, v! F
ask turtles: |# ~* Z1 q4 f
[ ifelse (wealth <= max-wealth / 3)
) z0 a* Q8 P' U V2 n# D* N# Y [ set color red ]2 s t" F4 r4 \3 U: y' }, _. r& u) d
[ ifelse (wealth <= (max-wealth * 2 / 3))
: o% c& U* `. ^. X6 \ [ set color yellow ]0 \' W8 s( V8 _9 c
[ set color green ] ] ]
) _ V: m( G1 F6 M! B9 h9 R ask turtles [ifelse show-wealth?
( z5 ~( M3 N' f7 g3 j, h0 ?- H [ set label wealth ], s: j4 M5 \6 w9 W7 A/ o8 C# o
[ set label "" ]], N! z. y5 m7 O6 l, i- m
end
' N" W+ q7 j) ~# z1 X8 J
" E9 U- @& s/ j( Cto go
- z6 E$ j: l! ^; I ask turtles- y( |# q# ^4 N* R* a; Q- J: R" x
[ turn-towards-grain ] % h# P! f' I6 p
harvest8 k$ W# U2 a3 Z5 T0 B6 z* U- k: b! A" b
ask turtles
* `6 E( \8 ~9 f0 s [ move-eat-age-die ]
! y& g, q1 d- D! h recolor-turtles
6 v' L8 m/ p/ s- V if ticks mod grain-growth-interval = 0
8 k4 u, R$ L/ V+ {. ^" g' R" I0 z [ ask patches [ grow-grain ] ]2 x2 N- C1 I/ ~
% Y: @4 r3 W. a) _( }) C, h
if ticks mod 11 = 0+ ~ {1 E$ J! M, w
[ask turtles
6 ^- s7 q1 Q/ I [ redistribution ]]6 L; e5 W7 y( V8 x. E
if ticks mod 5 = 0
: H7 _- H0 c# [" {' L0 t' A [ask turtles S1 i: h4 A y0 i- S* r
[ visions ]]
4 Q4 ~1 P7 C* t% v7 A2 m- _, S t tick
( M: M5 A. k, d update-plots" B' w3 I! a. J5 [9 q3 Y
end
* _" A! o. }% o7 Oto visions
7 y8 Z) U" s" u! u9 h6 |' d1 v set vision vision + 1 1 _# @6 e8 I8 k9 U, i5 S
end
" u, T2 V( R/ s4 O7 [5 C+ f7 U6 j0 G8 Z p% R
9 s A' F& I' v& P8 d1 W
) L8 j+ y; }5 J; y2 t8 S ]; kto turn-towards-grain
' ^# _8 J1 d$ q" w+ N& X$ m set heading 0
& g5 ~+ O% ~0 R+ B2 _& q1 |! ^ let best-direction 0
7 {8 ^; m, y3 B4 K& A0 v let best-amount grain-ahead
$ R; ^5 }9 ^/ I& w" B. ?9 ] set heading 90
+ A4 W+ ^$ l- P4 A% l/ n4 g4 k# T0 M. R if (grain-ahead > best-amount)" }- l4 k# f& ]! b: }9 q
[ set best-direction 90
0 V) z5 T9 a$ w5 v# q. G& I" ^3 U set best-amount grain-ahead ]
: I( y! u& t( ^; H& e% G6 d5 i set heading 180
) o( m y/ x+ `- S% q7 s if (grain-ahead > best-amount)
: x* T. U6 z$ n4 g2 y) C$ V [ set best-direction 180
Q4 @7 ?+ t( H. w1 l7 } set best-amount grain-ahead ]
$ {( d! U% f: k; ` set heading 270
: ]8 k e2 i' A4 L& C if (grain-ahead > best-amount)# f3 E4 J+ k7 M# P5 u5 a+ q
[ set best-direction 2702 o7 a& @/ u/ O, o7 {1 A
set best-amount grain-ahead ]$ j R! i; @: U+ F
set heading best-direction# W0 G6 |; b* H
end/ F7 T) l1 m" W, d9 m9 K. e
: t7 t0 A/ i; } M
! B, E, b+ {1 `
to-report grain-ahead
3 G1 ^ C1 R8 M6 b let total 0$ Z1 P, j& L" {; f# O
let how-far 1
+ Y. `8 P! Z5 A% ?$ J& t repeat vision, f/ K5 i9 h/ z3 S8 Z. m
[ set total total + [grain-here] of patch-ahead how-far
$ `2 R# g8 I& C7 ^9 h, [ set how-far how-far + 1 ]* @* T$ _; J p, u
report total
* ?' M4 k& }4 @0 F4 X; Kend
7 g: Q! i6 R" c# C
8 s: E3 o( c2 r& E j. t, Lto grow-grain
$ |# \: z. N1 H- N6 {1 {1 O6 L2 S" L if (grain-here < max-grain-here)
; }/ c; k8 y$ N7 r, E0 f [ set grain-here grain-here + num-grain-grown
/ h% f" r, T* Y if (grain-here > max-grain-here)
1 X# ?. ?0 s$ {% J% k [ set grain-here max-grain-here ]
5 r5 S1 i4 Q0 u, Y7 v' X C+ S recolor-patch ]! _! I# P2 z4 ^% f1 q. B% S
end
/ H: P' [4 W2 c2 Xto harvest
+ y0 V- N6 p. a# a- ] ask turtles
; N: M3 }9 `0 T9 a6 l. g6 B [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]- ? v5 `4 |, s U3 @- l+ E, f
ask turtles
& u1 X2 @5 `4 o7 |: x# Z [ set grain-here 08 @) K- r( I$ X7 t- k
recolor-patch ]
: P, t6 ?5 u, J
- N8 C3 S" b- g" r* oend& I1 t4 L8 N- z3 P: E. w( Q$ l; M
# }2 M2 V$ G! n4 j. ]9 K9 fto move-eat-age-die
1 r) h& W- t# Y fd 12 D3 z3 k$ j9 }0 b0 I- W) ~
set wealth (wealth - metabolism)
& o. |; J9 Z# Z. m) l1 O set age (age + 1). K$ r* _* W; X' P* y* d
if (age >= life-expectancy): a/ C2 i; f! p) f, [: v
[ set-initial-turtle-vars-age ]4 }5 q; {; _& o8 h
if (wealth < 0)
6 D2 T' ~4 ] R; {" P [ set-initial-turtle-vars-wealth ]
8 Q4 V1 M p! }/ {; k: k# ]' T " o# u% p# v& i! [
end% q5 n3 J8 @$ k2 [& f ]) K" r
t2 b# Y6 i6 F, x% M
a1 Q# `, Y% b% f0 V
to setup-plots, K' b; Z3 y' ], t; t8 g
set-current-plot "Class Plot") R3 w# g8 p+ q. p8 U2 D9 U: T2 F# s
set-plot-y-range 0 num-people% Y. k) Z8 @5 O- x; j* h
set-current-plot "Class Histogram"/ }4 u& k9 ]) c7 Z
set-plot-y-range 0 num-people7 ^1 v( G) ]" v) t! V# k$ R
end/ L& O& y& W. c, s( P
( y0 b& s; z- c9 r9 m5 K F1 N$ Vto update-plots7 q5 O; g4 q+ P" k6 l
update-class-plot
8 U" h" j; n7 i8 z. y6 n update-class-histogram
9 K( m1 i( b/ a3 M4 Z7 z# v update-lorenz-and-gini-plots& p0 F- {' L( N( j% W% F }$ O
end3 m3 i9 E# L1 m! W2 m5 f) P& x* j7 q
. b* v1 R% P# o) b2 P" d
to update-class-plot
: v, V6 k1 {( O8 g0 c9 S. T+ y set-current-plot "Class Plot"
. O4 h* J2 V6 D+ f: r( Y7 i set-current-plot-pen "low"
. n8 P1 L7 \# S. y1 P: ^% y. X plot count turtles with [color = red]2 o% p" [4 v/ V; Q- D! U0 F1 Y
set-current-plot-pen "mid"
+ N& H7 Q& c9 w9 l4 Y plot count turtles with [color = yellow]
- S$ F# y3 _* Y( o# [' d" o6 } set-current-plot-pen "up"
- j6 S* t' Z, t- U$ i plot count turtles with [color = green]
' f9 V% y: g. Z: [% ?end# K: O0 l& m8 s* E+ U. ~; T
* D6 Y8 B1 J4 p! I0 Oto update-class-histogram5 }9 w0 x" r" v9 }1 @
set-current-plot "Class Histogram"5 W$ G3 i G* B' P" b
plot-pen-reset
. H3 @. Y1 c2 a+ u set-plot-pen-color red8 _* G7 e1 V4 E; N; q* d
plot count turtles with [color = red]
. x0 s8 l) ?( a- z, B9 n set-plot-pen-color yellow+ a# g% \/ r& s- X# B- U; y
plot count turtles with [color = yellow]; q7 E ]" [0 S
set-plot-pen-color green
# ^( \ c$ p0 G, _ plot count turtles with [color = green]
: _: g3 o' D" D- l7 U" B# t4 ~end# m! d4 m! W' O
to update-lorenz-and-gini-plots
& W& G4 a4 B. Q* Q0 }$ D5 \ set-current-plot "Lorenz Curve"
" a8 h- ?3 K& w) V0 t clear-plot
7 g1 ?) K% X) l& `, A' q% i4 [7 Q/ j9 }; F/ Z& I# S+ @
set-current-plot-pen "equal"
1 C1 @ X) G W* u plot 07 ]! R/ B( K' Y0 A2 X
plot 100
9 ~2 ~# b* Y, ?% c% }6 _, _4 z8 _
set-current-plot-pen "lorenz"
{" S: m0 U$ g! q) W set-plot-pen-interval 100 / num-people
# F3 z6 k+ [- K9 F plot 09 x# Y) ^1 u0 H- A, ` q3 j
+ d: l) b# ]- z) b9 G8 }
let sorted-wealths sort [wealth] of turtles
6 X! s. {0 \( ]2 h$ t& y let total-wealth sum sorted-wealths
% W4 ^9 x; m: n1 I" m0 T2 S5 l o* w5 [ let wealth-sum-so-far 0
9 x2 q4 Q, }5 S0 f6 w9 N let index 0% n3 G5 i: n; e, l. z
let gini-index-reserve 0
( ^, |. I" z& K) b/ S5 T$ G
$ P; m5 }! I2 @- j; X repeat num-people [4 A( m4 W$ ?1 o) ?- [
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
; j. s6 p Q" }' ~9 D plot (wealth-sum-so-far / total-wealth) * 100. n7 K0 E0 w2 h$ W4 \, Y1 N2 S
set index (index + 1)% G4 N1 m y8 e. ~2 L& @ P4 W
set gini-index-reserve0 z' B! C2 T& j Q5 C& J0 }
gini-index-reserve +
2 {4 q# a( S! S; m, O8 R% p (index / num-people) -; S: ]; ~( q& e
(wealth-sum-so-far / total-wealth)
0 n0 |' o- j0 z5 u3 T5 e, Z: [& A ]
) D0 N. x* h% g/ R$ q
3 Q0 y) K( S- g2 X) Y- ` set-current-plot "Gini-Index v. Time"
! Q4 X8 T- s) t9 o1 m5 g2 y+ _! a plot (gini-index-reserve / num-people) / area-of-equality-triangle! v& P6 y+ n \1 M+ f0 |
end' \; x7 o8 H \( i- p
to-report area-of-equality-triangle
" j; o8 G7 Z; s+ k% Q report (num-people * (num-people - 1) / 2) / (num-people ^ 2): W$ \/ e& R/ e* B: y
end |