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
% F. J! }8 s# L$ s5 h' wglobals3 C# o7 z' d% c! G% H
[* ^4 F( [/ @& q: Q. M% J! o
max-grain
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patches-own
1 a% s% B$ ^1 s' _* V/ z[1 {# V9 I4 t6 s4 r7 H% X! W; ]
grain-here 0 G- v$ J8 A3 j8 q
max-grain-here
1 z4 Z! Z/ o' M$ x1 I4 r]2 `+ H. \4 j/ j" b6 c
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turtles-own
7 v) h- P" j, e! Z# U3 V& C7 n[* r% D* @8 n( L6 R" [6 [
age 1 D0 R4 Z3 d/ o$ `3 D
wealth . Y% u( G e; i7 K+ s. x& F: ]
life-expectancy
$ x. e9 R B- \* X5 q/ x5 A metabolism 3 s6 u; B+ r Q; D
vision
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]/ a- @8 }( O8 E7 j# u+ i; Y
( M$ s( S* m0 |2 D8 }+ \' y
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to setup
( n5 J( y) W: F, H) n" r ca
5 l& u8 R, A' ] set max-grain 50
B- E4 s& u! W# k$ I% N setup-patches
# p6 J3 j2 g; W: S setup-turtles
1 l) v3 i8 M) q$ G: p: f* R2 J setup-plots
# ~# Z8 \9 x7 D8 M1 z! n update-plots
1 I8 p v( B3 wend
: Q1 t) _" I0 G. O5 k& a/ Sto setup-patches7 y! h0 h* _- u
ask patches+ F! y# j+ Q5 _* }) D
[ set max-grain-here 07 l2 x6 }. W& m" }. _
if (random-float 100.0) <= percent-best-land
# W8 l$ K9 F+ I! a [ set max-grain-here max-grain+ s7 [4 n' A5 ?) w
set grain-here max-grain-here ] ]9 A ^ P6 v4 w4 ?$ ?4 Z- F. t
repeat 5
4 n( z: C- f4 E8 v" P1 S# S9 c [ ask patches with [max-grain-here != 0]
& g' ]- m- ]: D! @2 k7 ^ [ set grain-here max-grain-here ]8 W u* K8 _: L( G7 ?+ T
diffuse grain-here 0.5 ]; l: ?+ q# T: `2 j" y% q5 @
repeat 10
' u9 b$ j/ R- j( W+ s: L [ diffuse grain-here 0.5] $ k2 s/ E$ C: ~- u! d
ask patches
8 O' G# J) X! u; l/ ~1 y [ set grain-here floor grain-here
# F: k! m3 T/ p2 R2 f/ Q set max-grain-here grain-here 9 Y# G7 f& A$ O7 V& H
recolor-patch ]& t( O0 I1 N6 I2 i
end' [( l2 o5 I% i3 A, [
to recolor-patch
0 s) F9 B- ?& J& E! ` set pcolor scale-color sky grain-here 0 max-grain
% v2 r, n6 k% B8 j7 n" K4 Zend
& u- w8 E v. F; e; W. u$ j6 D; wto setup-turtles
6 K) h7 w+ |2 ^; {, V A) c2 M set-default-shape turtles "person"" m: r- Y0 k5 d3 i+ V9 m% y
crt num-people
4 Z S9 u' D, Q3 \' I# K [ move-to one-of patches . O+ \! X# O2 ]6 s1 M9 s
set size 1.5 0 u: K. M2 L+ |6 i7 w# W
set-initial-turtle-vars-age% W- C" D! P* }) d( F+ r3 \7 g" b
set-initial-turtle-vars-wealth4 x1 @ y3 Z( u6 _. [/ y) i) \& v
set age random life-expectancy ]
. j/ Z* @: J' ~' F recolor-turtles+ y' ~" N+ G1 f$ k/ j; T2 a
end3 \* v- |# T W" `- j- J7 G
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to set-initial-turtle-vars-age- j; E; x6 j+ n+ F$ @8 i1 T
let max-wealth max [wealth] of turtles( ^7 A$ x4 P5 d' B& }
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ifelse (wealth <= max-wealth / 3)
$ k# {( N1 d: _0 N x ] [ set color red
7 r; w9 P% ]; U( N* q3 v! Z set age 04 n% E! x: E% d& ^4 Y
face one-of neighbors4 + B2 S5 n; g. I, l0 w% M
set life-expectancy life-expectancy-min +
* x2 ]# n4 D5 N* A! n- E random life-expectancy-max : h+ D @5 Q/ r' B/ f" c c
set metabolism random 1 + metabolism-low
) X, S8 w: ?6 q9 V% d set wealth metabolism + random 30
2 ^0 Y# ?, y+ }" p0 M set vision 1 + random max-vision% i! Y# c( m: }. w) K* S
set wealth wealth + Wealth-inherited-low ]8 h. l& |& n' V# z0 S
[ ifelse (wealth <= (max-wealth * 2 / 3))
- w, K5 z+ V, T+ U( ~0 c6 x [ set color yellow
0 t: L/ i m5 d# {* h set age 0
- _! C3 P0 o; v face one-of neighbors4 0 Y8 F& V. E8 C& M# P5 o! G
set life-expectancy life-expectancy-min +
; y* Q8 n: y( x random life-expectancy-max + 1
6 x) N7 n7 y- Q set metabolism 1 + random metabolism-mid
9 N, e( K d6 N set wealth metabolism + random 30+ {% J5 ?- e0 b
set vision 3 + random max-vision
! c% M5 b9 K6 k( X, ] set wealth wealth + Wealth-inherited-mid]! t! L1 K% L3 V" Q7 J7 K, b
[ set color green + }9 p+ T- W# J) e; x
set age 0
, j+ A6 P2 f2 o0 ~- H4 G face one-of neighbors4
6 d- k0 e6 L9 I set life-expectancy life-expectancy-min +
" u+ C4 S2 p" ?5 F random life-expectancy-max + 2
& N2 G. G) K2 B8 D, c) \0 ^7 G* L# x set metabolism 2 + random metabolism-up0 n5 N8 n$ [7 M$ K+ ^& Q
set wealth metabolism + random 30
0 ?8 K4 F1 P0 G( v- i$ s set vision 3 + random max-vision
0 _8 T1 H* u) y1 Y set wealth wealth + Wealth-inherited-up ] ]
# T7 q8 O; `( X0 [; n! H8 \) V & n# v) ^$ H5 C/ R: E5 O9 Q. O! y
end5 T( X! j, X8 a7 n8 r- t
to set-initial-turtle-vars-wealth. r v- Y* U5 M- G
let max-wealth max [wealth] of turtles5 F0 O8 p1 ^* M3 r* ]+ Z2 P
set age 0/ b( \, T8 a A: [! m3 d
face one-of neighbors4
( v; `& Y; G4 s% u( t0 |6 _ set life-expectancy life-expectancy-min +
9 O! X* _" v/ z7 u) { random life-expectancy-max ' D* Y) A6 \5 `
set metabolism 1 + random metabolism-up
" h" z& T u+ {# @! x set wealth metabolism + random 30% @# B" i# R/ C) l: t, {, s+ o( N
set vision 1 + random max-vision
# W- i8 ]% @. V# p7 Kend9 a' B' U) w( H; K2 |
to redistribution6 [* i7 H4 \& |
let max-wealth max [wealth] of turtles
1 T$ D4 t* ]8 f8 z! j( @let min-wealth min [wealth] of turtles( s6 q3 H0 B: d: Y
if (wealth <= max-wealth / 3)
! H& N' G9 |4 x [set wealth wealth + Low-income-protection ]
- W8 \2 m% f5 L2 B* l* i. |3 r* qend
' C7 m: {6 _- ~5 k ! p' H2 W) K8 }1 C: Z }
to recolor-turtles
- k1 L& T8 ^* D# G3 a$ y& O# K let max-wealth max [wealth] of turtles
/ K& }: Y& B/ L- x& C ask turtles
2 i, a$ S! D D, h [ ifelse (wealth <= max-wealth / 3)
% Y: b) i1 L/ j( X0 x7 o4 P6 q [ set color red ]0 s, ?6 l' e8 F6 ?, e
[ ifelse (wealth <= (max-wealth * 2 / 3))
6 L; U `% J. W7 p" V8 V$ y [ set color yellow ]- x D- ]; i& W3 W( C- c% Q+ x
[ set color green ] ] ]$ e/ t9 i2 B+ E4 u& S
ask turtles [ifelse show-wealth?
: G- n- E! q) |' Y5 a [ set label wealth ]
1 A7 A( G- n0 O9 w$ { [ set label "" ]]
. u" z! a( s' ^; D" B& m' x% [% f8 eend
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to go [$ x9 }/ T1 \) [) s3 Z
ask turtles0 z( A9 q% E' j- g' b
[ turn-towards-grain ]
1 Z3 c: s3 i: d+ x harvest
/ H: s9 t& p2 \8 }5 f" x ask turtles
. Y8 M+ e f# q/ m8 X# t [ move-eat-age-die ]0 |# z! T9 t$ a1 q0 F$ _
recolor-turtles5 V2 E) }2 U* L0 p1 U. W
if ticks mod grain-growth-interval = 0. X5 y2 w: u6 J0 |
[ ask patches [ grow-grain ] ]
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- s3 z* f( f5 A" u8 R if ticks mod 11 = 0
, I1 k& p: T# ]- g [ask turtles7 \2 T+ d6 v8 y" S& |: V
[ redistribution ]]& i( ^, z% f( r+ P
if ticks mod 5 = 0
# z# s) ?( x8 X' p [ask turtles" j1 J" e4 E+ H1 q
[ visions ]]* r; z4 y3 T+ i! m5 M8 `
tick: E& V" z% N# V0 d# m
update-plots
' m6 X5 B% o8 C+ h6 d: _end
8 Q; J9 c9 I! E5 w* q! T5 ^' Nto visions( k! k$ `9 f" m( O5 C
set vision vision + 1 & {9 Y9 ~6 \" _4 x" [
end
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to turn-towards-grain
7 ~$ o3 E- N0 _: P* i set heading 00 E' M# y+ `% g0 W
let best-direction 0
`/ T l% j% u let best-amount grain-ahead$ q Y( i3 x8 U1 O( f; ]# f
set heading 902 H/ L+ U, [3 X5 [4 a/ {
if (grain-ahead > best-amount)/ |* U: H" U" h
[ set best-direction 90
% Q) l \$ O* w$ B set best-amount grain-ahead ]
! C: x3 Z% v3 |; P: R4 ] set heading 180
9 D/ P3 {& A* ?2 c: n7 [' z" ^) p3 \7 ` if (grain-ahead > best-amount)' A& X" \: s: [& Z7 C- m
[ set best-direction 180
3 ]0 A0 S. u+ g set best-amount grain-ahead ]: p; K7 @- [0 }6 L! K: G
set heading 270
, X0 R1 w# n7 M/ ^8 h" A if (grain-ahead > best-amount)
7 q! {4 U# ~( B8 d' K# m, r [ set best-direction 270
3 K. c/ O' l& [. s5 P set best-amount grain-ahead ]8 U1 q9 n( x$ {) t' ?) L' @
set heading best-direction
7 Y; F- C2 p( n. e1 M/ zend
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* l3 b8 T! t% e/ K; H1 Z
to-report grain-ahead ( o9 u8 S) j8 l) O, }; C- K! y; j
let total 0$ a- l$ z- N8 c9 ~" j0 a/ r2 q
let how-far 14 b* t( n- k* _3 x2 }
repeat vision1 e. Z- n4 M p8 i
[ set total total + [grain-here] of patch-ahead how-far
2 P5 d5 ^# q2 ^. k( h set how-far how-far + 1 ]! ~& a4 U% a3 G
report total/ a# `7 { z$ O9 z9 f
end
/ ?; h S1 q% m% {$ a' {5 J& [% ?' R& Y% c# w
to grow-grain ! W8 R! {/ ?# w% r
if (grain-here < max-grain-here)0 w1 ^/ A9 e$ H' h
[ set grain-here grain-here + num-grain-grown: v k6 A2 U+ U7 ~+ C
if (grain-here > max-grain-here)
5 s8 Y1 h. R5 Y( F* r$ I$ n. } [ set grain-here max-grain-here ]
7 @5 @4 C' }5 B4 P recolor-patch ]
2 } u/ e* {6 v) s, r: R6 K- Dend
4 }0 H5 g5 m0 U b# fto harvest& P! R" { Z+ D- @
ask turtles
/ x/ J. d% {; J3 J7 p [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
( n% x) I& B8 d" t6 k- {0 u% x ask turtles
9 V( s% a7 V# C- f5 B" Y2 Z+ R& z# x [ set grain-here 04 R8 p ^* M" E
recolor-patch ]) T2 b1 c+ L6 T- A; g0 [
; Y4 q3 H$ n6 R
end
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' {6 F; N1 O7 o. k# ?. |to move-eat-age-die 9 e7 B, U; o7 c! S
fd 1; V: c, v9 C6 q
set wealth (wealth - metabolism)
5 }" y0 `" H; ^3 k$ E/ p set age (age + 1)
& h! i% P% F$ g' d u5 U# p% [ if (age >= life-expectancy)
& ~! L- O7 f2 d+ @4 a1 K [ set-initial-turtle-vars-age ]
7 j/ l3 O9 n( J& ~ if (wealth < 0)
' ]' j6 x ~! B6 k- X2 q5 S j [ set-initial-turtle-vars-wealth ]5 ?5 _: L; Y% }0 C9 Y* n
; u. q+ n, X& b# m, F9 [+ C4 e$ C$ bend
9 Y, }% ^) {# c/ m+ V* |7 \. p; N( I
* Y+ u% `, j% \3 q) |2 d
4 k' H7 |# u# n0 q) a- ~/ m* pto setup-plots: V) V+ S1 z" F/ }( Z
set-current-plot "Class Plot"8 D( M6 h& o& r, f
set-plot-y-range 0 num-people R5 w! B; K- \5 @ {( W1 p
set-current-plot "Class Histogram"
9 E/ J0 s: E& a( j set-plot-y-range 0 num-people
) ^: W/ `! _0 wend2 [' Y- R8 B5 ~$ }3 j
+ x# K- p4 e( j& g& } a: c/ W
to update-plots: I9 V* x6 c" T6 U0 i
update-class-plot6 B! [8 A: M1 s0 h* z- Z
update-class-histogram _/ c$ ?. D; T
update-lorenz-and-gini-plots/ d8 @7 u, M. y7 f
end
) Z% |7 h; P1 |, b
7 G: g4 s" ?& Tto update-class-plot% H5 P& T, E4 ^. t4 o4 p
set-current-plot "Class Plot"7 F6 w2 O. I; i
set-current-plot-pen "low"
% [; }3 C+ `- I$ b! e plot count turtles with [color = red]# K4 s+ `' t7 \2 ^( B
set-current-plot-pen "mid"" H" H5 N: G) q: _
plot count turtles with [color = yellow]: j8 l2 s& v3 C4 e
set-current-plot-pen "up"
* l4 u( g( o* m plot count turtles with [color = green]
9 r5 W. b8 w" a }0 Qend# r" D: N( V# [$ ]
+ E( B. N! }* Y `% c7 \5 R) K0 j
to update-class-histogram
% N9 C6 B* Z# M3 } set-current-plot "Class Histogram"$ z. y- y! H [5 b8 d S6 m1 |0 r
plot-pen-reset
! D6 z1 _! M `& ^6 |* M" q set-plot-pen-color red
4 } j, b2 @8 R+ f$ X plot count turtles with [color = red]2 N6 ~/ C7 c" V2 j+ l" f, `* K
set-plot-pen-color yellow
$ d, v. D; e8 ?1 W4 ~ B, @ plot count turtles with [color = yellow]
; @4 Y9 I# m+ R0 a( N/ B set-plot-pen-color green* r8 e2 ^# }: |2 p% {9 L- {6 P
plot count turtles with [color = green]: M n: t$ r9 U( H% [- e
end
) G. M- Q# t# O ^, \/ cto update-lorenz-and-gini-plots+ u9 G, ], l9 C Y! V
set-current-plot "Lorenz Curve"
) c) p- A8 c3 |/ Z5 y clear-plot2 e; G" A& \: B8 ? D, U
( B, S% p! W# ]6 D/ W
set-current-plot-pen "equal"% ^9 ]7 X0 ~1 p- \- s4 v e' N
plot 07 A+ C0 b+ `1 A: Y
plot 100
?" T% U0 _/ q$ X8 i+ K! D; _, Q* z6 K% B0 E
set-current-plot-pen "lorenz"& L( M0 Z4 r1 w! Y8 J
set-plot-pen-interval 100 / num-people
% L4 Z' ~) R( V5 v3 c. P plot 0
$ w9 V' |- ~ L. A2 V0 G! `1 B# L9 m9 q8 h8 j X( G5 j
let sorted-wealths sort [wealth] of turtles
7 T( W/ v! Q c+ J4 `% I6 F. V" _ let total-wealth sum sorted-wealths
, L* X7 h5 v! M T; k# _% t3 Q2 x let wealth-sum-so-far 0
2 t% J! c5 @' l: y9 g5 v# E! d. ^" k3 g let index 0
, I0 C. A& u- ~* D; M1 H F N let gini-index-reserve 0) f% B( d$ j! h( I! \2 }# b- j% q
' a0 }+ x. T- n/ Y2 | repeat num-people [1 |8 |7 A! ]; @" |
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
1 T: E9 F3 o& {1 d! ^8 [! ~ plot (wealth-sum-so-far / total-wealth) * 100( Y' y2 D. \! L5 R; z
set index (index + 1)# M/ s! t5 W' @, B3 p2 _/ F8 ^
set gini-index-reserve
; k9 ]+ J9 Z& T9 t0 s- j. m" ~9 ^; b gini-index-reserve +% W! u- c* E" W/ L) ]
(index / num-people) -
9 C# ]5 n" T& H, q9 g o) O, c (wealth-sum-so-far / total-wealth)( _* M4 q$ d$ B' Z! d- h4 ?
]9 C# G2 M4 |; n% w3 \: N6 M& g
; v& g7 H! M, ?7 ?- w' \
set-current-plot "Gini-Index v. Time"2 N, N) N7 {' g1 Y
plot (gini-index-reserve / num-people) / area-of-equality-triangle; R9 F0 O; r0 O6 f, X5 E' p2 ~! v
end
" l, \4 h# ^3 I3 _to-report area-of-equality-triangle- l- `3 _8 C, r" G
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
. u: i5 U, R5 p& H/ c5 Nend |