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4 m! V* w6 o* {9 e+ g Z
globals3 v' o) j8 t9 u7 t! P, R4 o
[( U" Y" C9 [3 H. d( L" c& W
max-grain
! }4 L, J1 L$ y3 a1 E. m5 ?
* | y+ e- J5 g$ \]# G2 K0 Y( m( \
6 I; w) M" R: p5 y2 m, [patches-own
, V1 w) H5 R8 J+ k" ~[
& V* d+ s( V- i- r* k grain-here / O4 f. _) }/ `8 d9 ]
max-grain-here . l" o) S1 ~" W+ n
]8 }& s9 ~/ r5 `( u9 t; ^; {+ F+ A$ B
+ A9 y9 A0 S7 |" H. x
turtles-own
1 V0 W6 R# I4 ]- n[7 |5 y k. Y" K' U2 q- a- F
age 8 A) u( g' _0 m7 V. S7 |
wealth
1 \- Q; A r& Y( Y life-expectancy 4 b! R5 w u4 p/ r, g+ s
metabolism
6 H* X; x3 O4 A% C vision: L$ D4 [/ G# r
inherited 3 y6 e1 n! i7 V" F
]6 w6 }( W" {% \- }" t3 r3 D
( @! P+ t9 ?0 o1 D' o5 a$ f7 ~7 k/ f5 e$ L7 w
to setup9 _# }/ f: W, o9 Q
ca7 C" \5 @: R+ P
set max-grain 50& L- J) F, n, `; E; G
setup-patches! E, e1 @5 a/ @; h
setup-turtles* x$ i: K" Q" _! {( O, g4 h4 M5 f
setup-plots
6 V) Z: I) H$ t7 w update-plots
2 G- n1 `) q: }$ \end
% }) m7 Y6 T' U: ^) x5 |7 Xto setup-patches
9 x1 Z8 `, Q u7 r$ J3 U+ T ask patches
' @+ b; k% \4 k4 E! i [ set max-grain-here 0
: j# n1 V* H( v' s4 I( } if (random-float 100.0) <= percent-best-land) P! q* J! x4 l$ V- D, f" M, p0 V9 z
[ set max-grain-here max-grain
. l ^, x2 Q" E# V9 ?; v, o2 | set grain-here max-grain-here ] ]# X+ A) j5 C+ C+ f! D
repeat 5* H( e( e: [! k) |( i; f" h
[ ask patches with [max-grain-here != 0]
4 J. l1 }+ k3 d; G7 l5 T [ set grain-here max-grain-here ]1 }0 D2 B: }1 D
diffuse grain-here 0.5 ]
# A& p; ]+ c! D: K& W repeat 10
% \9 ^. w$ r6 S0 u [ diffuse grain-here 0.5] ( C" l! v; Q0 |* }# g' j# j
ask patches* }% f+ }) ^, ?+ L: r
[ set grain-here floor grain-here
0 j) t% R/ V! p5 l set max-grain-here grain-here ) Q( ?: l0 e9 e& T; z3 m( X7 i
recolor-patch ]
! O( C7 d! U( `/ @end
: M. C f' F' Z& Gto recolor-patch U1 z7 t8 ] \0 W
set pcolor scale-color sky grain-here 0 max-grain' c) j/ N* n2 c1 f
end
, u* R# g9 h8 ]! s& m9 W1 ?to setup-turtles5 X9 T$ h t$ M8 r3 K3 |
set-default-shape turtles "person"
/ Q) E( r2 K# M { crt num-people+ m# c) [4 G. k- c
[ move-to one-of patches " q3 u' G0 m% H
set size 1.5 . y7 P, x5 C/ `& ^$ H& w+ i% M( O {
set-initial-turtle-vars-age
B5 n6 ~; I, F$ U* R+ S set-initial-turtle-vars-wealth- O5 E q# Z5 ?, J0 \
set age random life-expectancy ]
0 e0 j7 ?# G4 E; q- q3 Z# U' ?0 }( ? v recolor-turtles
" O5 e- Y5 f- A2 \; x5 V4 E9 C: M+ ?end$ m/ v7 S7 l; {8 z) `1 k
. R- v: d& H2 k. r% Sto set-initial-turtle-vars-age
4 y1 ?1 q" V$ z. G5 a! ` y let max-wealth max [wealth] of turtles
4 y- U+ x+ j! r: J( i, p, ` ; R" l. _( G: R. i, `3 I4 c7 i
ifelse (wealth <= max-wealth / 3)
! a/ M& Z# n5 S, y$ I1 Z [ set color red + }# c) v" a" s0 U& h/ i
set age 0" L. O" _! ^8 @4 A1 i* |
face one-of neighbors4 - y3 e% K. D/ Z1 I/ a
set life-expectancy life-expectancy-min +
3 Q: V6 C3 o+ ~- c$ S! Q) @5 m) X random life-expectancy-max
9 C5 P" f z' X* T; B set metabolism random 1 + metabolism-low/ w. G9 y' `7 ]: F
set wealth metabolism + random 30: u# k6 y2 {; Y( G) J
set vision 1 + random max-vision
* T5 a; [6 k9 B set wealth wealth + Wealth-inherited-low ]
3 p$ `' K1 y z [ ifelse (wealth <= (max-wealth * 2 / 3))
, U7 a3 {1 H% ? P [ set color yellow
& G [; {* N, l* y# ~ set age 05 `8 {; l' z1 B& f# o* z% S3 q
face one-of neighbors4
7 K: ~+ p$ T5 W set life-expectancy life-expectancy-min +0 f5 k+ Z s) Q+ A4 B+ l) x
random life-expectancy-max + 1
5 a; P* n3 H7 V set metabolism 1 + random metabolism-mid
7 y4 [" d* K9 y set wealth metabolism + random 30& g$ J; d0 k, k: }
set vision 3 + random max-vision" N2 f F { D# M
set wealth wealth + Wealth-inherited-mid]
i% m3 U9 x' k& C" J [ set color green
}5 g/ F9 J1 q+ w: V* t* X set age 0) t' I8 \+ v+ ?+ Z. F ^
face one-of neighbors4
. s: x! I: Q: m9 a set life-expectancy life-expectancy-min + B9 n. j" o5 g" u- q# I# p
random life-expectancy-max + 2
( K8 w8 A! ^8 N; U6 @$ S* ^ set metabolism 2 + random metabolism-up2 x& o8 D3 u& H X( @
set wealth metabolism + random 306 j0 P5 F/ `9 y/ }. a
set vision 3 + random max-vision6 h* f$ O) J3 I* q" r, q
set wealth wealth + Wealth-inherited-up ] ] 4 }9 I4 S. T- w0 \$ A- f
# p, p; U6 y% `: l" o: I9 i0 bend
8 ~2 E7 z v" b# Z6 N" S9 xto set-initial-turtle-vars-wealth" O1 n7 _% o( V) r
let max-wealth max [wealth] of turtles
5 }/ n+ H9 O: {0 Y9 A+ r; | set age 05 ]0 z4 J; r) G/ c6 L
face one-of neighbors4
+ Y& p( I% S$ u! b3 @6 `5 S O set life-expectancy life-expectancy-min +# r9 G- c) K8 [* h
random life-expectancy-max $ t* ?& w% u# E7 N8 y0 G
set metabolism 1 + random metabolism-up
- g. l" E3 S2 { X set wealth metabolism + random 30
) r; z$ c0 t0 q6 m Y+ ^! A# | set vision 1 + random max-vision 6 [1 D# B L' w9 l! b0 B
end+ J/ ^( d; n7 z s
to redistribution
% P& ?5 Y5 b+ v7 `5 Rlet max-wealth max [wealth] of turtles5 }$ [, [# \( P' H2 Q" `
let min-wealth min [wealth] of turtles
3 C$ |, Z7 c6 S0 E6 Q/ Rif (wealth <= max-wealth / 3): w- h" P9 W0 l
[set wealth wealth + Low-income-protection ]% ]( A: W8 ^6 {; Y
end
/ ]1 z* N5 _: t. f 4 ?: T6 x% ?, _/ S
to recolor-turtles! H: p4 V& p3 q5 `
let max-wealth max [wealth] of turtles x0 W# r) n! x8 H
ask turtles' X( ?6 l, D2 S) W' T. C
[ ifelse (wealth <= max-wealth / 3)
" h5 ~8 r# i. P2 p. \, Y7 X$ i [ set color red ]
, m" O& T1 \! a [ ifelse (wealth <= (max-wealth * 2 / 3))* [8 S; h6 ] S% ?. X+ h
[ set color yellow ]
: n3 @1 Y" C0 X4 K; V: i7 }0 J [ set color green ] ] ]
$ J) o1 g6 O j* h ask turtles [ifelse show-wealth?
. ]! k' O3 e; Z, M [ set label wealth ]. ]# s( w. E7 r" O( _4 b
[ set label "" ]]- G' ^3 e, r g& ? I" i
end/ O: U4 U4 h" P# ^1 c2 K: ~
! ]) R* W; ?! Bto go/ X3 A; E( j: Z# X; w' @% {, V
ask turtles( g* _0 p7 s$ {1 Y4 K
[ turn-towards-grain ] 1 [4 h( r- P5 |& }0 c6 w# ^
harvest$ D D! @. e1 V4 s2 X+ x
ask turtles8 o; O( l% K' _ ]2 ]: h* ^0 U5 H
[ move-eat-age-die ]
9 {2 w) @5 W! J% G recolor-turtles( e2 C; N/ {: B/ }3 \
if ticks mod grain-growth-interval = 06 X, b/ M5 |4 e; c+ H" C* [3 v! v) L
[ ask patches [ grow-grain ] ]
0 G2 h: M3 v" b/ B( U
1 o# H1 n- J1 d if ticks mod 11 = 0
1 o8 Y& U0 w2 u" G" Q8 ?+ b [ask turtles
; r9 ^4 j i+ V: p, u [ redistribution ]]
, t' l! H/ F9 k- j if ticks mod 5 = 0
9 n, S3 J- q4 w# M [ask turtles
* P# e+ E5 K- U5 E; U$ L [ visions ]]
3 X5 W) f5 B. b- b; F tick
" T: w+ J. t" H& v update-plots3 d5 E& |5 C" H6 N; y* B
end8 u8 ~8 k" j1 r1 f- {) k
to visions
' o5 V# N4 _6 X+ W set vision vision + 1
, ]1 e7 F4 @/ _end
& W6 C$ `% j. t* h; N, ]2 c( R3 ]7 p& [9 h
n Y/ y Q X4 k1 z: \4 \* _
, {2 o- h: z8 E+ b4 mto turn-towards-grain 4 J* A1 n X# w5 K+ Y8 t! k
set heading 0
0 k2 r6 U" P4 |5 [2 X9 w) e; T let best-direction 0
/ l" |9 v- z& x# y% f let best-amount grain-ahead3 ?) I; `- D# R
set heading 90$ g; B. @; r' z3 c; C
if (grain-ahead > best-amount)# o! c* l4 Y6 {/ w6 i. f- E
[ set best-direction 90
1 o. c+ r; D6 n& Q8 v) Z3 | set best-amount grain-ahead ]
1 T& g2 l W# L: } set heading 180% D1 o" ]% D. T4 P: Q* W9 m" D9 J
if (grain-ahead > best-amount); T0 k, I$ x! e: Y. ?( }) f
[ set best-direction 180
7 Y* f" F: Y/ g1 K8 _0 H: U set best-amount grain-ahead ]1 K" v$ Z0 t6 } K5 z; F$ _
set heading 270
7 G' x2 g" v1 `9 I3 j; E7 j2 d* d" p if (grain-ahead > best-amount)0 S: n' }% I7 y* e6 T. j4 c6 f
[ set best-direction 270
( s. o! T7 `: ?+ z9 P; R set best-amount grain-ahead ]
' D# u8 d$ F: ~; H( u set heading best-direction9 D& h4 V' U4 O* `
end: M% [! ~3 I7 R, P% C
' z7 u6 K) \5 r8 R; j: o* F) ^
# y2 u+ y) t$ R2 ~+ w9 v
to-report grain-ahead , q: l. d9 m; E1 q. V) n1 }, ~
let total 0+ z+ w2 v' |, ^+ M4 S' w4 X
let how-far 1, Q! n' L. Y( m, i
repeat vision
2 X7 z* N, ~" G% J x, k: G7 x [ set total total + [grain-here] of patch-ahead how-far
" L0 H( b: E* t5 N' p( e* m set how-far how-far + 1 ]
7 _& x7 U' r5 A9 p3 Z# G report total# \9 q9 o" V$ {+ {' `
end
9 Q% u+ K8 | [. j T, c2 ~( H7 _$ N. h9 _- X3 p5 N
to grow-grain
( O$ Y1 q# ` s' F if (grain-here < max-grain-here)
" M& r& _/ V" V" h3 `" @) p/ f [ set grain-here grain-here + num-grain-grown
6 w% H) I# e! ~$ u if (grain-here > max-grain-here) + i0 _9 W2 s% u( I3 ]
[ set grain-here max-grain-here ]
5 V( Q9 b( g% i1 i recolor-patch ]0 C5 J1 p3 h/ f9 u; q
end
$ z6 ~, v' D: ]) ~: c! P- Yto harvest* n/ U! B% |) O+ {9 v2 f: z# _7 A6 v' e
ask turtles1 J, z" Y( k: Q- b8 C
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]# e* z' y7 P+ h+ h
ask turtles6 N( d/ n" q0 v% n" W7 G8 S
[ set grain-here 0# {/ I( ^4 n; P8 w j9 e. ]3 k
recolor-patch ]
; Y2 r1 D& ^. E- ?3 e : u+ R2 f2 y- `" f
end
" ]" d1 H7 a# F6 z4 ]. `( |$ D1 v1 l4 R" ]. ^4 S* M5 r
to move-eat-age-die
# A# i- e/ {# ^/ N& W" H0 Z+ @* l fd 1
: n* F) {$ j1 K, N' S) P+ J set wealth (wealth - metabolism)
, e9 i) U. U3 x7 K, M: j set age (age + 1)
]) y' }- a# L- t8 J2 }) q if (age >= life-expectancy)
& x2 g, N: l! g6 y) N [ set-initial-turtle-vars-age ]8 q J8 i6 Z2 ?- ]) |5 P* J6 w* i. d
if (wealth < 0)
# K3 {1 _0 T+ O [ set-initial-turtle-vars-wealth ]
/ T" B1 O9 e$ n / P+ i( j( z" a" m4 \+ G. R2 N8 |
end( a4 f, X2 P( e# t
! r! I0 w" b& k( W6 m v
( V2 B/ o( |5 k1 Sto setup-plots
- r+ D+ c8 Y( {% Q; H/ z2 V L$ V set-current-plot "Class Plot"
- `* o, {9 s0 s. X( Z set-plot-y-range 0 num-people# w7 q' P# S4 L9 l% Y. Y
set-current-plot "Class Histogram") _9 Q2 a7 P* b! I2 e; {
set-plot-y-range 0 num-people% s2 x: f; @; p' g
end% p. I3 h0 x& T) C* I+ @5 B
$ Y( U t( q# T& d; A2 g
to update-plots
# m" [4 p$ Z; T: p update-class-plot: t, h7 A, Z# ?
update-class-histogram
- |3 s9 Q0 l) C% T; n update-lorenz-and-gini-plots
& N3 Y" q9 J7 g6 E! Lend; o- P4 [& B2 J' H
8 |. O& z" h! @3 Z" u. Y! y+ yto update-class-plot
- i! e% S( q# z K5 W& I3 y( I set-current-plot "Class Plot"4 N8 i9 X3 d9 k6 X( V
set-current-plot-pen "low". Z3 a" ? x( J S' }
plot count turtles with [color = red]
; D3 w) K B- H$ i, o3 @2 O5 b& R set-current-plot-pen "mid"
5 m9 x! O. a3 i! K6 H' b plot count turtles with [color = yellow]' Y* P `! O0 r5 L+ W
set-current-plot-pen "up". g$ @& c9 \( k1 m: _4 y4 h& f
plot count turtles with [color = green]3 A8 ~7 a) I1 w
end1 G, P! j* @0 C9 N; n& a/ Q" Y+ T
$ Q3 L- ~! b9 |, Vto update-class-histogram
+ [6 [5 e8 r R% | m" X set-current-plot "Class Histogram"' q- Q* ?- Y2 t
plot-pen-reset$ S2 X' `& B- K% q& R
set-plot-pen-color red
3 T% F; J" f* t- I$ J' h plot count turtles with [color = red]- _- a" K- `1 M5 s/ \( X9 A
set-plot-pen-color yellow
2 B& g. f/ g2 m5 k' s) O3 L$ y7 Q plot count turtles with [color = yellow]% O/ L# w8 r) y. i6 @3 b
set-plot-pen-color green- Q) C& w( @& V4 x
plot count turtles with [color = green]
( o) H: I/ k m3 send) c1 {" L% Z5 y0 p% h& \* p, i
to update-lorenz-and-gini-plots
: I! t4 U4 y3 R4 q7 R set-current-plot "Lorenz Curve"4 K$ a% X: B9 M- g- `; a
clear-plot
0 e: }5 D1 I* t" t+ G T+ [/ D0 { r+ o) d
set-current-plot-pen "equal"5 K- w+ {$ Q, l, d/ e; a: D5 ~
plot 0 z( v3 w( v0 ]3 u
plot 100
* m0 @& Q) o; P2 l
$ p# M: o: M! A9 L set-current-plot-pen "lorenz"# X) _4 ^* k1 r
set-plot-pen-interval 100 / num-people
/ {. P5 E. D! @5 m' N: F plot 02 G" G% \: _# m6 h
( U8 e6 k9 l6 K
let sorted-wealths sort [wealth] of turtles1 _! P+ n, V- \5 k+ Z
let total-wealth sum sorted-wealths
; H* l; x! `8 c+ J% e/ r let wealth-sum-so-far 0. A: N3 y8 Z) `$ ]
let index 0
! B( g5 b; u# n let gini-index-reserve 0
. }0 T0 y5 J+ p' ^0 b2 ?& s3 x% A7 G1 t- f, J/ K
repeat num-people [) q* w1 [* h, j7 w, Y
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
- H( n5 p! M. ~ plot (wealth-sum-so-far / total-wealth) * 100( k2 C- N1 n# I5 e- j. D
set index (index + 1)
; H0 H& Z# R6 ^. _6 H set gini-index-reserve
& P8 I, `% }; D; r gini-index-reserve +
m. ^; ?5 q" J/ b$ ? (index / num-people) -
; q ]" n; [ A9 V (wealth-sum-so-far / total-wealth)# l' k# m! k# e1 G6 ~, a: O7 i3 E. ^4 j
]
# v& j0 \& A) k, n1 D& Z1 ^/ a: [( X* X: Q. R. z( \5 Y+ c `9 `
set-current-plot "Gini-Index v. Time"3 z( T0 E. N# _( }2 P3 m A* P
plot (gini-index-reserve / num-people) / area-of-equality-triangle- c2 o/ F6 e# p! X/ Z
end
: {8 Y' h& }6 g, w: \3 k: R oto-report area-of-equality-triangle, s8 ~5 r( F; U# H$ K2 ~" G
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)6 Z6 o' c$ \/ ^! m& {
end |