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
! _. Y" O9 X8 r% L; H1 tglobals$ v t" A9 s8 H4 m* F2 N$ b# k
[$ y. b8 P$ t9 M
max-grain % p) N! X% M) P3 m) T% }* O3 `) D* N
) u n/ q# v. x5 ]" S
]3 S- T7 l2 Y8 N
$ U6 |0 l2 E ~9 `0 \* V- ^patches-own1 x0 x `7 H9 T; [5 C
[
* D8 c$ x5 b' x9 ] grain-here
' z# y- [3 t8 E1 X; j3 a4 F) v max-grain-here
6 `; v+ P, q0 y ]]* n9 ~5 t/ T3 a# Z% I* v& g @
. [. }9 P. q% yturtles-own
, j1 x+ o; P! j o7 w! @# I9 ^" F4 ~: X[2 V' i4 V, k. S( }9 J
age ( ?- V4 A0 V( u& K6 ^
wealth
; y2 b8 q# l( q9 w life-expectancy ( e. _8 ~2 c" o) c
metabolism
1 c& X; p$ Y* l( Y vision; s; z- @. i {- m9 a
inherited
3 |7 u5 P0 ?6 H5 |" Z3 W6 W7 R]' b7 @( f2 S( c% o" x
& _0 \. W" {/ ^( u: l6 c
! I- e+ a3 V% {& z3 g9 @
to setup+ J7 O3 \1 Q5 D( x* D
ca; A* R: a9 F M/ K0 p
set max-grain 505 u5 ^- q, f# S7 v1 Y
setup-patches
6 X3 W+ |* e$ a1 d% s$ Z8 ?, J& x! g setup-turtles, W B- S y% R1 j6 s
setup-plots# `7 I! Q. n6 n6 q/ t* |
update-plots
9 }( y% M# f' I' M3 V- Wend
- _6 I$ I9 _5 [3 x5 S0 q* E, N1 N) oto setup-patches$ F+ {) h1 h+ m& K# P+ F
ask patches
% c' H! F0 u4 ~& t; O1 L [ set max-grain-here 05 E5 K% i5 B* F2 w0 o% _
if (random-float 100.0) <= percent-best-land- ^: W; {( `/ @6 t- c8 Q
[ set max-grain-here max-grain# a4 n6 v) J* }1 W; U$ D
set grain-here max-grain-here ] ]8 K) i, i+ L Z
repeat 5- v- K; y; a- Z4 m
[ ask patches with [max-grain-here != 0]' l% Q- s3 e* m
[ set grain-here max-grain-here ]! N" O, X8 N. ?; b) A) l- {3 n
diffuse grain-here 0.5 ]4 S0 h+ K- m, {8 J( c
repeat 10
, {; M+ P( m4 a) Q B [ diffuse grain-here 0.5] - V* \3 q/ B6 g; C- u
ask patches; ]; p# P5 @9 [3 q2 V, _
[ set grain-here floor grain-here : X, W# a" t: K5 h, ^
set max-grain-here grain-here + Q6 @. y6 e" {! N8 E, f
recolor-patch ]
" j0 B: T! i4 u: z. _end
4 L+ ?. \) ^! h% m7 @to recolor-patch
- E0 ` i7 {2 I. Y, o set pcolor scale-color sky grain-here 0 max-grain
2 N \& _- L0 Vend: Y9 ^2 _1 ?: T4 T- F1 |3 |2 i$ W
to setup-turtles0 c9 C9 |& ~7 w" c! _8 j
set-default-shape turtles "person"" ?5 B; \% }- F# Q$ m" n
crt num-people
3 E- {/ O7 w- c# |, h& ~6 N. I [ move-to one-of patches
5 T+ Y/ P; p$ Q- W2 T t4 b5 e2 E8 r set size 1.5 0 `4 h; N- b2 }/ d
set-initial-turtle-vars-age
1 Q) L8 m3 @+ N9 s4 [ set-initial-turtle-vars-wealth$ A- D7 X' o' S- Y' {
set age random life-expectancy ]
+ Q+ ?$ `" y/ T recolor-turtles d. ]" u7 }6 a" D/ n W
end' d. L& s1 ^) A
4 F# y: p& z( s5 [% Q& X! K4 f4 v' Rto set-initial-turtle-vars-age) @1 ~/ h7 C( r3 P/ E: V: \+ E) s
let max-wealth max [wealth] of turtles$ n& C) {. y* p( |4 S
* [7 U: O8 F1 y8 i/ B4 N
ifelse (wealth <= max-wealth / 3)' A" l; q" n" g2 N4 B
[ set color red + h/ L1 f# O$ D! a
set age 00 Q j7 U, b- ?0 r! m8 L
face one-of neighbors4 & q/ Y) {; N) \& K1 r4 W: |0 B/ h
set life-expectancy life-expectancy-min +
5 }' A" F- A6 j random life-expectancy-max T9 T. S, y9 i& f; Q: u8 W; p2 G( p
set metabolism random 1 + metabolism-low
6 R3 m* C# n) N set wealth metabolism + random 30
) J. Q* b X$ t# C$ A- p; c- q8 A set vision 1 + random max-vision m# m. @" D' X c& A' E2 w
set wealth wealth + Wealth-inherited-low ]2 ^. @. z; ^% W* v
[ ifelse (wealth <= (max-wealth * 2 / 3))( C- t6 B( N$ J' ~
[ set color yellow ( j( |2 G0 o6 D0 E: F
set age 0
; K4 P. }3 H- }% E3 m face one-of neighbors4 : {& d% s. u: f
set life-expectancy life-expectancy-min +
+ B$ z U. F* \5 @* e random life-expectancy-max + 1
" B* p; K% O9 }0 o/ F% q set metabolism 1 + random metabolism-mid) J$ z8 c6 E5 W, i( N' i; t7 v
set wealth metabolism + random 303 {6 X7 F6 \1 V g2 d' n" @: o
set vision 3 + random max-vision
( p& M+ n1 P7 [8 _+ I/ X set wealth wealth + Wealth-inherited-mid]
# [& I2 j0 i z) `( ^ [ set color green - f/ V0 A# `' h/ T2 j: ~; I' g5 a
set age 0
. e& P) T0 E: w3 p+ k' ]5 R face one-of neighbors4 0 h. \; ^; z5 ~1 Y9 k
set life-expectancy life-expectancy-min +. @* o$ ]) y6 F# x3 G" w7 v' h
random life-expectancy-max + 2 R% K6 A$ F* x" j* m( J
set metabolism 2 + random metabolism-up( c/ E+ {' ]! h: E3 T( x* K
set wealth metabolism + random 30! s, L5 F( \; _1 Z' b
set vision 3 + random max-vision; L& U# Q, U, ?$ R- Q1 i* F
set wealth wealth + Wealth-inherited-up ] ] 3 x: J- p: @! n( D! r4 G
; i, F5 k+ w% g( O: `end/ W s0 i3 f$ }$ ?2 Q
to set-initial-turtle-vars-wealth1 U" p1 e' U& N6 i
let max-wealth max [wealth] of turtles
* I6 d' B; n; b/ I! W1 C5 S set age 0
8 x/ }) _( h+ Z4 X4 b' O face one-of neighbors4 7 Y2 O2 y8 M! X- h4 l
set life-expectancy life-expectancy-min +
! R6 K2 S* s1 V/ | random life-expectancy-max ! q+ {; Y5 _: O& q+ O
set metabolism 1 + random metabolism-up
$ H9 u% I9 O( ~4 n7 k5 G$ }2 l set wealth metabolism + random 309 R$ q9 O6 @ n; B6 J
set vision 1 + random max-vision
3 \+ S' ?- O F2 Iend' e* B9 ~5 f+ |
to redistribution
6 T% d4 A, b0 B, f; u9 z% o5 qlet max-wealth max [wealth] of turtles% J5 Q: L+ M/ A. O5 o
let min-wealth min [wealth] of turtles$ V M* _1 R/ `8 e
if (wealth <= max-wealth / 3)+ |3 k5 Y! P+ K/ L9 L& L3 t
[set wealth wealth + Low-income-protection ]
8 F) B/ V8 x! M! Fend7 D3 x" ]7 |$ u" a, |" s* r
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to recolor-turtles2 P# a4 S$ P9 {" o* t
let max-wealth max [wealth] of turtles
$ F1 ?6 F! [1 b0 I ask turtles- l4 K: E1 y& G; R
[ ifelse (wealth <= max-wealth / 3)
/ H/ |% q) h6 P3 p5 T [ set color red ]. o6 k5 ?! ?4 l0 ?9 i* |
[ ifelse (wealth <= (max-wealth * 2 / 3))1 X0 a& z+ I4 E: Q
[ set color yellow ]
2 t8 B4 R- \ a [ set color green ] ] ]8 A' L" r2 V: Y E7 e* H3 P' r/ x
ask turtles [ifelse show-wealth?9 ?7 C: d0 f. l' k3 w2 C) C4 {* |
[ set label wealth ]
# h: F! c2 \& W8 u6 [ [ set label "" ]]
/ s9 j' e I/ L& b$ c$ bend
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to go
( \2 L' q" Q+ C$ p- z' C ask turtles
5 n G1 C3 v$ L. G" J [ turn-towards-grain ]
3 U3 f: _4 Y3 N) b" r9 F- N harvest1 u: s' E5 {: z7 P0 s. j4 q& u. k
ask turtles
+ U- E; n k6 ?3 j& P; a7 i w [ move-eat-age-die ]
. i ^8 E% c# U- J recolor-turtles( x# L$ ^% L' m, W
if ticks mod grain-growth-interval = 01 ^1 w; M% s9 z- n
[ ask patches [ grow-grain ] ]) H2 x) Q# B `9 o
! t6 V3 V5 I. G2 R* ^0 b( H
if ticks mod 11 = 0
4 r, Q5 j1 i* O0 g* [ [ask turtles
" K" G, g5 L! i; u [ redistribution ]]: U& D6 \& {8 r, d4 X
if ticks mod 5 = 0) v9 T; u) d) @9 q
[ask turtles; E4 k6 L5 R Q5 q
[ visions ]]
. ]; {3 C( [( n2 f tick+ H: f" E7 @: @; T: ~% T, l" o
update-plots# y* B1 q p5 ~5 |
end
% T* \7 V, Y2 w' X8 ~to visions2 R8 i0 ]! N9 ?7 i* y" W9 W4 h3 Q4 M
set vision vision + 1
$ d+ ~2 |+ J' H; ^6 j5 }: X9 i# nend
( @' e3 n8 ~+ k' H' x$ Z* P9 J+ P3 s
& a% c5 R6 X$ A {# S
/ @: _7 O9 Z% U* U/ c, V3 _2 p, S5 bto turn-towards-grain
5 L1 G) k4 b4 J+ {6 L/ u% t set heading 00 ]) P9 A; F7 _3 G. U
let best-direction 0
: x1 N( I0 E& K6 l! G6 n let best-amount grain-ahead
5 D4 b7 q0 K3 ^3 u. }; P set heading 90# L/ P+ c9 u4 s/ e
if (grain-ahead > best-amount). C# `) G# R5 }% q3 J& P$ _5 w
[ set best-direction 90: | {1 |6 }, O0 }9 S6 |* j
set best-amount grain-ahead ] c6 C3 }' l6 z' c3 `$ @
set heading 180
! S% t. i1 \% V6 l if (grain-ahead > best-amount)
5 B: z: l7 R" z1 Q( T [ set best-direction 180) \& Y0 r q+ x) ]6 }
set best-amount grain-ahead ]* D+ {8 Z0 J/ y( \$ w0 O9 Z
set heading 270; j0 r! C" q% `/ A. h
if (grain-ahead > best-amount)
+ R$ m. i8 j, y7 P. Z) O1 v& e- S [ set best-direction 270
$ D' S, Z; V5 G# k. B2 l0 V- f set best-amount grain-ahead ]5 _$ @# z( f* g4 h3 y' J
set heading best-direction
* D, A! \. P( D/ v4 _end' t' x% ?5 O+ Q
: v: f* x" ]( j( {; d& X
$ c0 P" ]) S9 t# J& V
to-report grain-ahead % W. d5 V8 R% F" W8 E! b
let total 0: E# l1 }% Q7 Y( D0 {
let how-far 16 _8 V3 f" D5 Q
repeat vision
& z/ h4 p! X) N" b, u [ set total total + [grain-here] of patch-ahead how-far
( x8 J5 x" |. _6 {" s0 j set how-far how-far + 1 ]
( c( G& X6 }* N) b4 r5 R report total/ y) A$ G. _: H& i5 W% `
end% z! x" t* ^4 L; v3 U! ? A( y
0 ^% \- g ?2 I% E" X
to grow-grain 9 [5 [# Y; b" m, v( H
if (grain-here < max-grain-here)
+ I& F9 W U- a" K% E1 l [ set grain-here grain-here + num-grain-grown
7 b4 W" G' x6 W6 i, J if (grain-here > max-grain-here) - B2 }4 @) c5 h0 t- z
[ set grain-here max-grain-here ]$ J$ K& }) K# w6 W
recolor-patch ]5 Y/ r- x- N* ]6 G
end3 {% o8 V! N, W. @$ o
to harvest0 b; G. Y) y( e- o7 h. c
ask turtles
- K, A3 R# d: ~! ? [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]% Q a/ v7 q# \0 J/ _
ask turtles
* E- |2 ]& X; M# s4 L [ set grain-here 0
, B% X6 v9 E: }; y$ i1 x recolor-patch ]
0 U5 A2 G5 ^9 w9 o" W: ?5 M
s. ?% e5 X9 v# p; x9 {# d) lend
! b5 g# z0 S% U6 V5 Y
% x$ G, f+ ^: cto move-eat-age-die
6 K3 v& \4 d. s- |" c K: Y fd 12 F) j6 g; g' s# {! _ @, R3 U3 t8 D. z
set wealth (wealth - metabolism)
- i7 O8 ]3 p& |/ P1 b, X+ M5 X set age (age + 1)
; n; N0 r( N5 `; N if (age >= life-expectancy)
( e3 ]. v( Q2 V [ set-initial-turtle-vars-age ]
( `( N" ^3 ~6 s5 G. F0 e if (wealth < 0)* p6 u7 d, {. k, y; ~
[ set-initial-turtle-vars-wealth ]
3 p6 a/ ^, n( Q- R& d/ U
/ X; ~; Q# N6 e: Oend2 e/ @7 r" B T3 ~' _( X
% W6 F( B( b* w
' \: H3 ]5 b1 y5 N" a* rto setup-plots- E& i6 w5 G& B( @7 @3 w( P# V
set-current-plot "Class Plot"* M( `9 h t$ o2 t" O3 R
set-plot-y-range 0 num-people# c3 j, ~$ d5 Z" p c& S4 w
set-current-plot "Class Histogram"
4 F( S, K* e2 ? T4 c( G set-plot-y-range 0 num-people$ m+ x1 `4 ?" g2 b- d5 U' y5 v* x/ d4 Q
end
, \- l. B# j- ~( g
: B. ]& v+ Z4 g m3 F6 V" u1 a. I, t# Sto update-plots4 X5 V* ?. n4 T1 R6 @
update-class-plot
2 j& X2 n- G) P$ d, Y' _; ? update-class-histogram
4 ^4 d& Z) \4 U; v: g' p3 U/ N update-lorenz-and-gini-plots* z/ _ Q! [1 A0 x/ b# X
end$ m7 R: [/ _; R9 ~1 ^7 P/ r
" g# C& S& Z1 S/ f
to update-class-plot' m9 O) `1 G. L) J& G5 ], _* N$ t
set-current-plot "Class Plot"
& W8 v! [8 w0 J+ | set-current-plot-pen "low"$ a& o" y# b( ]/ a( z
plot count turtles with [color = red], g) F7 H. ?4 v, v! Z
set-current-plot-pen "mid"
( L- m' u( J! Z5 X plot count turtles with [color = yellow]7 K& e# x3 x( b, y
set-current-plot-pen "up"
9 \: {% Z$ \' B0 R' ]! M plot count turtles with [color = green]9 `# p6 S, a8 e7 j2 \, d1 b
end. f8 L" x0 r' P ~2 B; j
3 R9 o$ E3 n( |: }0 V7 r6 Y
to update-class-histogram7 }5 y# H3 k$ f& |: G" w
set-current-plot "Class Histogram"
5 K0 c: Q# R$ Y2 ?. a plot-pen-reset$ T3 h0 X& N% @) g& f5 ]5 g
set-plot-pen-color red q! ]! K; @9 L) n( b4 [; z9 E
plot count turtles with [color = red]' B8 ?, s9 ~4 a4 P8 v( w: j
set-plot-pen-color yellow2 o8 g! I2 o' @' _/ F
plot count turtles with [color = yellow]
0 c A3 v8 Y. e7 j3 ` set-plot-pen-color green
" `3 {6 t3 d8 c5 k6 t- z4 U plot count turtles with [color = green]
$ K0 `* d3 ^/ V$ {7 y% Gend6 t' y# P/ h3 g. ^1 i
to update-lorenz-and-gini-plots
0 a' y$ ]2 i0 Y5 s2 C) F set-current-plot "Lorenz Curve"
3 V) H4 _- K7 b0 q; s( [ clear-plot
# g* x! j9 c# s4 T4 k$ B, F$ m' N |7 I
set-current-plot-pen "equal"( R- @* q, `' d
plot 0+ Z+ a; A+ M7 O! B: J. m
plot 100. M. d9 _+ s8 Y) m
9 V" w+ T e# d3 Y- L
set-current-plot-pen "lorenz"* r h; F E0 U4 ?( C
set-plot-pen-interval 100 / num-people
4 L+ U* |' {; S" |- L) O& ?& O plot 0
1 p3 P( ^( t2 }
% y1 V. [5 H! m; X let sorted-wealths sort [wealth] of turtles, I/ J9 Z& B. i- n
let total-wealth sum sorted-wealths
( _; E e8 t) q. X6 V let wealth-sum-so-far 0
8 H! m; ?' g. W4 B, ^; ~ let index 0
: o4 |" t; n8 ~) U let gini-index-reserve 0
}% d& v P9 B: J0 r6 g
8 ^% F7 q4 X% R! G7 w) h* W repeat num-people [$ m$ R* t; ]. e- R( _: p) z
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths), I7 m# [" N7 D& { H7 t+ l
plot (wealth-sum-so-far / total-wealth) * 1005 ~4 v% Y4 W+ K8 }1 E, j! p
set index (index + 1)* f+ d8 I& R" k+ M4 C' ?
set gini-index-reserve
6 a6 K8 M, G- [0 g+ t4 I- ~/ Z3 ` gini-index-reserve +
9 B% X$ V9 t! v (index / num-people) -
! L" X+ A& g# ? (wealth-sum-so-far / total-wealth)
0 I9 ~, f1 C& s s3 C& D4 } ]+ K! \, k0 |& w2 o
& w4 c7 ]5 K, C- u5 d" u W7 ^: k set-current-plot "Gini-Index v. Time"+ K2 C( g; f1 R4 p9 i/ v
plot (gini-index-reserve / num-people) / area-of-equality-triangle
' Y" V) S' A& q: z, jend% r3 b: L& c! a7 y, Y( O$ ^
to-report area-of-equality-triangle4 X$ x. R/ J' G
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
+ [* E; l" m6 o0 C3 tend |