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$ Y, d n1 o* O6 pglobals/ X2 k& s. l- f- R/ ?' F7 M
[6 B" V R( a" x" K
max-grain 4 t- C; f. P# j
* Z) C( i3 A. a
]
3 t2 S7 E6 e9 Q2 y4 v4 g
! W/ g% J& B6 X4 D4 Q- H; m- }patches-own0 ^8 |, _: e) k' d7 Y
[8 S! H! v2 r/ O' I0 Q5 I, L
grain-here
* |" L( D1 |/ _. Z) y, d max-grain-here ' }1 G* j" I& L0 o
]
# a& |" t3 d# j2 @; n, G$ C4 P" @9 z* q- r. h8 u3 m. p- n; L, v
turtles-own7 V/ ?" @3 y! A# z
[
. o' F* l d- p+ U% s' G age ( r6 ~4 T( d, F3 a, [ d
wealth % g0 z0 F% j. o& `0 n
life-expectancy
& J I$ [, `5 [% } metabolism + l( | B+ f3 T1 E ]
vision( H+ |) X( e( D4 v9 \8 {+ L; ^
inherited % O8 A7 w, a( }/ V- p4 B- e4 w: W
]
0 ^& e8 X" C1 Z" i5 O$ ]+ A* ^2 p* [, I
9 b7 Q6 R' o, T* I, I* |- F+ Fto setup1 z1 S) b0 M( e( q5 J4 X" v& K
ca" |- L* ?- }0 }6 Z3 p
set max-grain 50
% }1 `3 q$ J s/ | setup-patches
+ u5 U1 q8 s0 T9 w setup-turtles0 S* H2 ]% y6 e; J
setup-plots
# x4 N6 q6 b& z$ E9 p update-plots
5 x& Y: W5 g. |+ m) @9 yend4 B5 `2 U* e! q# Q7 M s" O- d
to setup-patches
2 @0 {! }% C1 P% x3 N" z7 W ask patches
9 `$ ]- V# \' { [ set max-grain-here 0
6 {) j; x$ \( G5 d9 L$ f if (random-float 100.0) <= percent-best-land/ ^+ K8 P; {9 p) _ c) x
[ set max-grain-here max-grain4 p M4 y# H" W0 p% k
set grain-here max-grain-here ] ]! I' o7 E$ i" U; D+ l- K
repeat 5' D& r; X. C z& c+ v. k
[ ask patches with [max-grain-here != 0]
- {2 w, W: ~, @+ h0 j! z% v [ set grain-here max-grain-here ]- p3 {% Z( ?( b0 V+ I% j( l
diffuse grain-here 0.5 ]
: f. V6 K; a: r% X- X+ G3 c repeat 10
' {# |, U& H; h& T3 e8 C [ diffuse grain-here 0.5]
% G; o3 [) k" f ask patches7 j. J& a2 R1 C
[ set grain-here floor grain-here # D; K' k+ E6 G# V# J
set max-grain-here grain-here 6 L6 X5 t& j8 Z# i& @& n8 F' U
recolor-patch ]
1 A5 M9 }! h6 c4 Y& eend
$ ^' v0 h, h; E: u; Rto recolor-patch 9 o( l1 V' P) I
set pcolor scale-color sky grain-here 0 max-grain" H5 p* X: z. T; u' V- w' L
end' ], y; {0 D. H) ~( U
to setup-turtles+ \. M" p1 f% {, N; D. u/ B: i2 b
set-default-shape turtles "person"
5 X6 L2 g9 o5 m crt num-people: ?( C: D1 F/ a- Q y$ [$ p
[ move-to one-of patches - g: `- G2 v6 a' ]7 G# p+ Y
set size 1.5 9 D. ]6 a% ^9 w7 u
set-initial-turtle-vars-age
; U4 G% @8 U: ]1 l$ L3 _# R/ ~ set-initial-turtle-vars-wealth
5 c/ Q) f! X: P3 j! d7 n set age random life-expectancy ], `) \1 {( {* D! r1 M) a8 Y
recolor-turtles
# e; g0 F$ @ K/ t3 ~" m8 Send2 C1 n% |! q5 d$ u+ w% i5 b
" A# Q: J5 g2 w! C3 f5 j
to set-initial-turtle-vars-age
; b0 }5 D. s3 g/ B/ `$ { let max-wealth max [wealth] of turtles
9 {" E9 M# M" u% g+ \( S9 @! L1 s" \
P0 O2 J. b6 r. o- o ifelse (wealth <= max-wealth / 3)5 p4 o% v( f% w: b
[ set color red
# ?+ t( A! u; @) b' Y" i( |8 { set age 0 M3 @% V5 f/ b: X, k
face one-of neighbors4
5 E9 d% r9 |$ F set life-expectancy life-expectancy-min +
# D- x ?% j; C2 e7 O) p random life-expectancy-max : I: @0 q5 O1 o" D3 i7 M
set metabolism random 1 + metabolism-low1 V" \* J& E* l! V1 W$ S5 M, g
set wealth metabolism + random 30
5 m0 I* [: ~0 L5 | set vision 1 + random max-vision9 F/ A8 G3 ^4 M$ V
set wealth wealth + Wealth-inherited-low ]
" m4 d! n4 G; }& d, p. ], w [ ifelse (wealth <= (max-wealth * 2 / 3))* J% U1 v9 {" K- z9 v+ @$ s
[ set color yellow x( G# E7 |. l+ n& E
set age 0* Q" b; U1 r& O& C3 E- ]0 `
face one-of neighbors4
D; \# y( \) _; q7 H9 G set life-expectancy life-expectancy-min +
8 O. }1 y( n9 _4 P8 Z ?/ I random life-expectancy-max + 1
6 D$ B+ T! m. o! A+ D% L' _ set metabolism 1 + random metabolism-mid
X& h( l7 q( ]% E0 A$ p6 j* j/ ]: X set wealth metabolism + random 30
* a1 h/ G( D) _$ A2 t# i+ x K( b set vision 3 + random max-vision
$ f5 o8 Q4 K( X6 j- T set wealth wealth + Wealth-inherited-mid]8 x z. a& l9 S! P2 z1 s% m
[ set color green
8 O; a! b% `* U; B set age 0* p# o5 h. g7 Q0 |
face one-of neighbors4 ! T8 ~+ A: b. j8 O9 Y" x2 s3 P
set life-expectancy life-expectancy-min +
( q8 P2 |3 n, p* h+ w: {& @ random life-expectancy-max + 2
) F3 s" R5 _3 R, i, J set metabolism 2 + random metabolism-up
`9 r6 w' D0 M$ w+ M* w% j set wealth metabolism + random 30
- {5 J; X) _* [+ f2 r* v" y; A set vision 3 + random max-vision' q0 p! K7 f# J: \; \8 n/ S2 Y
set wealth wealth + Wealth-inherited-up ] ] N7 r# J u: w7 {. Q; m& D
' l7 Z) V) D" i! Wend; k" ~. @7 s* N4 s
to set-initial-turtle-vars-wealth6 g0 P& k# U. t* A, Z1 W; g$ p
let max-wealth max [wealth] of turtles r* O' x) Z: M) C# E
set age 0
; D9 v6 C9 k& d4 J- H face one-of neighbors4
1 w' o) S6 z0 f1 O+ j' g' H set life-expectancy life-expectancy-min +
! ?; N! _& s: h0 l/ H) { random life-expectancy-max 0 ]; d2 E5 O1 T( ]" w5 h. }* @
set metabolism 1 + random metabolism-up4 _' k& [6 J" q. x$ c7 y
set wealth metabolism + random 307 u9 O( L2 F$ H, z; ~; [7 }% ?
set vision 1 + random max-vision
4 ]- ~9 t( o: G9 _4 x6 Cend5 R- d( f1 U% _! m% W
to redistribution
z$ A! ^8 u: jlet max-wealth max [wealth] of turtles( C+ O" t0 R1 w; v$ e# w2 ^' Y
let min-wealth min [wealth] of turtles5 n! M. K4 {. P! e+ ]
if (wealth <= max-wealth / 3)0 D0 K* ?% J0 i! l* v8 F
[set wealth wealth + Low-income-protection ]4 Z) q/ m& _1 A" g6 o, o+ N
end6 l2 F9 E7 p7 ]* E0 i: s3 @
, M& T! p& m: |. {' a9 a6 Sto recolor-turtles
7 [$ D n5 Y! E' ?; I6 E let max-wealth max [wealth] of turtles% B6 m, {9 B' `& y, |+ u$ u
ask turtles6 x! q" n+ {+ w
[ ifelse (wealth <= max-wealth / 3)" g7 M% Z, a/ J: Q1 u: A1 k5 K
[ set color red ]
}6 K% W2 R1 B( r& v [ ifelse (wealth <= (max-wealth * 2 / 3))
* A" t+ Z% y9 u/ o/ H" e& L [ set color yellow ]
) {, V2 v# |+ q+ w% c4 {; X2 ? [ set color green ] ] ]: D8 Q {' u7 s- s
ask turtles [ifelse show-wealth?
: H/ n* G) D( K4 B) h+ ] [ set label wealth ]+ }9 A6 V. } T* v
[ set label "" ]]$ Y. Z3 k- j5 M0 u( t7 G
end
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: f+ u4 z D) b7 s1 ]# @9 [9 lto go" e; }& ~- e% ~9 D7 _5 s/ f! W8 @
ask turtles$ e% C4 Z9 _1 q+ ~" ~% b
[ turn-towards-grain ] 9 {2 u6 }; p: h1 }
harvest
. ]3 D5 _' q9 ?, o( p9 [2 h" V* t ask turtles0 e0 l' S/ G9 R7 b8 \0 u7 A
[ move-eat-age-die ]
" l' x1 R# N+ Z' H0 V( O% m0 f3 p recolor-turtles# k, B1 i# t( I3 |) g$ A. D
if ticks mod grain-growth-interval = 0) n( C4 u) s5 n6 b# A
[ ask patches [ grow-grain ] ]
: F+ F7 M: [# z" @& ]+ H. Z7 A. V # D! N. X" Q$ j# M/ _- s7 t! h
if ticks mod 11 = 00 R! m* A6 K; @ D" l/ ?3 N" o
[ask turtles, O6 {) X% e7 y+ C8 l* _6 k; H
[ redistribution ]]+ @/ ]! M9 `. z! @& C% U) z
if ticks mod 5 = 0
# X) K% ~+ h6 Q/ D7 c [ask turtles
' Z, d2 f" ]. \ [ visions ]]
; [/ B) T7 v `, j tick# d; ~! [+ L& w! k4 @+ ?
update-plots) R F3 M! O' z. P4 m7 Z% }
end
( h: X7 V2 V6 s7 R1 Cto visions
: ~& \' }/ {; p! e/ |5 x% L9 ] set vision vision + 1 9 [) d7 u% \/ i4 Y9 b
end6 t* @ _' W; g( G# y) Z H7 p$ V B
2 A' I4 g- Z L9 M' \7 ]
8 I0 q7 m/ s8 c; t" u' y
% Y+ }- Y. L0 ~3 v7 m
to turn-towards-grain
- R5 V/ Z" P) v$ m" g; g set heading 0
4 S& Q) O6 q8 i* z* B let best-direction 0
8 p" ~% f/ Z1 F! K! I let best-amount grain-ahead
7 ^. G9 v; j6 k! k9 q set heading 90
3 s, |. f B( H0 U' [- ^ if (grain-ahead > best-amount)% c& {7 z8 |' ?6 h, T3 i8 P
[ set best-direction 90
) F5 g0 @4 C# {0 c1 @ set best-amount grain-ahead ]# |4 z* q6 v6 o
set heading 180
4 Q8 @2 L$ F: D+ `1 k; Y# @4 Z if (grain-ahead > best-amount)
, l) F" \, @4 ] [ set best-direction 180
( O, t5 i/ {% A/ Y& i# o set best-amount grain-ahead ]
% g6 d% t( V- t f; T4 m set heading 270" ^. U% Z& R" c, p
if (grain-ahead > best-amount)3 q* i% i# f+ l! D
[ set best-direction 270
; L, f$ J* |, T# `8 a+ o set best-amount grain-ahead ]) U5 n; V1 h/ X( B8 C$ n
set heading best-direction
, }9 M/ w* e" x/ Z* Uend* I2 Y; R6 w; \; ~( a3 j/ F
9 l5 A' [, U* |6 L% _
; s! t. a Q4 ^
to-report grain-ahead + c, w9 e; q7 J0 {: {9 \4 [: d
let total 0
. p3 k1 ~8 m7 J8 w& D, R. l let how-far 1
1 S* |. y0 ^/ b repeat vision8 E! l* v0 ~4 g1 v+ k
[ set total total + [grain-here] of patch-ahead how-far0 m7 a- B _2 P
set how-far how-far + 1 ], @7 `% V6 k+ u, n# Z% p: x
report total& D! k3 @7 Z. X! I
end
s* [1 q/ |/ P5 w5 H% P& Z! T2 Q( A
6 |3 L3 K4 N; ]7 q3 b lto grow-grain
9 J" m0 Z- v) q0 ?3 E) u- W if (grain-here < max-grain-here)3 F* O8 `6 y2 z5 D+ y* y& ]! S
[ set grain-here grain-here + num-grain-grown
/ v" i% F5 _+ g0 W/ Z if (grain-here > max-grain-here) & {7 V, a5 l y' y. T9 d" L$ r8 O
[ set grain-here max-grain-here ]
" `% u4 L! Y7 d: O( w recolor-patch ]
! G+ b$ n* b% i+ Mend* v+ J. o" L, q9 I5 I
to harvest* i( P, p: j' L6 X* E) r# n; @/ y7 j
ask turtles* O8 G% Y: A# l& X
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]. Q+ e" J) d! v! r& w
ask turtles- K6 g2 g% u0 w
[ set grain-here 0& A7 U7 A) ~( [7 b. }
recolor-patch ]
5 v& e# S8 [ q6 _8 _' S
/ _6 g* C7 F8 o F( }4 Y% _end# D% ^/ c5 V. x. m+ o
/ o# ?2 m$ X: K, ~# X2 }5 Uto move-eat-age-die & b) e2 Y s, k; l# F, ?0 O
fd 14 ^- K, A) J* a) x" h. f+ R
set wealth (wealth - metabolism)4 z9 M* `5 l* ~1 m" U
set age (age + 1)
& x! S/ [/ g- V6 r1 I+ _ if (age >= life-expectancy)/ {' Y% k; ^7 T# i# l9 t( }
[ set-initial-turtle-vars-age ]" ~7 m/ A f" T6 t& I& ~
if (wealth < 0)
. k, p3 @1 @- }% C5 w! o [ set-initial-turtle-vars-wealth ]
) c" Q2 w* x$ V. H7 Q T) D
2 E& o$ r+ J! n. a# hend+ D8 t/ `+ V$ N' I) ]
+ r' a; e5 `8 P; O. e' D. ]: ~% J7 ]$ c) i" x
to setup-plots
: [9 _7 \- \, N4 `. X: S0 H' w set-current-plot "Class Plot"
# s: ~" H3 I( W1 k% g9 ~ set-plot-y-range 0 num-people- M+ ^ V6 w( _8 S" ^. ^
set-current-plot "Class Histogram"
. o* N# L. h! Z R* e set-plot-y-range 0 num-people
2 l6 s) V+ ^* x; r5 Y# U( F4 Oend. @! e3 k8 t7 h
/ j! K h e* a
to update-plots
. x7 g+ }5 N; k: F* Q update-class-plot1 u, ^+ N' ]) Z+ j6 ?' C
update-class-histogram
- H7 `# k" Y: L* ]8 Q* [ c1 G: m0 H update-lorenz-and-gini-plots4 q+ u. N. |' n2 a
end; K2 p; z! w3 j* b9 B+ z7 Z
# j9 Y, C3 q$ S& Y/ c8 A6 y% m$ {to update-class-plot; Z6 `0 B$ j: ?+ Q. g. l, _
set-current-plot "Class Plot"
1 A' k6 h$ q4 G5 `& u set-current-plot-pen "low"
. ~% H7 N2 I; q# j5 o/ U8 H plot count turtles with [color = red]
" R/ u: L5 t! y2 L# e+ p set-current-plot-pen "mid"
) u7 ]+ c: g3 Y6 j6 a; A( I; g plot count turtles with [color = yellow]
J# M, C4 u( K4 N' r m set-current-plot-pen "up"3 _; ^2 |# H5 S g* g! f' C
plot count turtles with [color = green]
' p6 ~( ~% o# w6 ?3 gend" D+ @( K1 Q$ Z5 N
$ ]* Q3 J5 @% P! q
to update-class-histogram
|5 R' ^% I8 C set-current-plot "Class Histogram"
7 Y2 w- w3 ?& g2 Q8 t plot-pen-reset
( J6 b3 ~) g8 y1 W! F6 n( D3 D" W set-plot-pen-color red
n+ r+ f+ i+ _5 ?0 u3 Q plot count turtles with [color = red]# \$ R* i& x R* h, X& F
set-plot-pen-color yellow
6 ?) b3 G' {) h plot count turtles with [color = yellow]
" G+ S' t; ]8 |% o set-plot-pen-color green
, T) q9 L8 g Q/ I plot count turtles with [color = green]
1 @ o. a2 E6 N% O J) Dend0 X) Y7 J' u+ b7 x, Q
to update-lorenz-and-gini-plots
3 q0 \3 m1 k/ `$ s4 m set-current-plot "Lorenz Curve"
y# s4 m+ B+ {/ {6 g; k) w% K. B clear-plot
0 Y; q3 H9 U' j( V' Z6 c
' P8 U" a1 Y- p& W" N( d. n set-current-plot-pen "equal"1 H" w' p$ Z/ h' D
plot 0
0 m, a/ Y0 ~6 j( b- I( p plot 100 F" q. P9 i9 ?7 v1 b9 d2 H
Y4 o9 F( b/ [6 R set-current-plot-pen "lorenz"
- W1 B: L$ @: }& x: \$ |" D set-plot-pen-interval 100 / num-people
% M+ y0 u6 f+ k3 T plot 0
6 Q# U5 o4 [) z! m8 [2 \9 u, e# _4 X' N$ |
let sorted-wealths sort [wealth] of turtles
( S/ Y5 g" x- [% k let total-wealth sum sorted-wealths! w8 L) E# M- ~' w
let wealth-sum-so-far 03 d# L5 d" V* W/ z7 K! c/ c* U
let index 0
# U9 C5 L+ ]9 L2 v$ {3 B let gini-index-reserve 0
+ K1 N& ]( |$ n( m2 H6 Z
+ t3 G( |6 C* G4 U) h) L repeat num-people [7 k8 Y/ P! x4 w
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)5 C( V9 b& N% V, H+ s( k
plot (wealth-sum-so-far / total-wealth) * 100
6 w% t- ]" j; |1 J: b, o set index (index + 1)
( i" ^8 c: z6 Y; a set gini-index-reserve# h! j0 @2 }& f. x) v0 P( V
gini-index-reserve +1 k) _: {! p8 Q! l# _
(index / num-people) -
; o; l0 S# F7 B5 w& u (wealth-sum-so-far / total-wealth)7 D. k0 l# p# v6 w; ?& ^7 L1 F; P: S" p
]
0 j/ K1 q4 L1 Y( Q& ]5 r7 h
8 `" ?7 W! K/ R) b set-current-plot "Gini-Index v. Time"
2 h: ` [0 w5 W2 h+ g. _9 B plot (gini-index-reserve / num-people) / area-of-equality-triangle. D! ?' M; @/ s* r, C# C8 K
end
# ] n' t9 `4 x6 T- k$ b. zto-report area-of-equality-triangle
7 p6 M* a- N1 H3 O; B report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
8 I; S* k! J+ vend |