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! k0 w/ N! p8 d9 w' i2 Y
globals
$ ^6 D, g+ j( W$ f4 I3 B6 m0 S% f[
- n4 Q& ]/ Z; q1 d) N" j max-grain
2 R0 G' _3 U H5 O. o+ i+ n- x# Y& L; g1 N- W# N
]
9 C" ?: M; W4 X$ o! G: L- h. w& o$ Q0 o$ v0 \8 I& N; T/ w
patches-own
; y- |: V2 O7 `; L[" Y5 M* x$ ~5 o) x
grain-here
3 B. P0 ~) c; Y max-grain-here
7 Q) X, ]. y' i5 ^% q0 G]/ ?4 q% J5 [3 G$ Q( |
% Z% a8 y: {7 m
turtles-own2 @8 ?: c6 P4 \5 ?5 b* \
[
# V# S: P0 Y4 [$ D age
- E" [- }, w/ E* K" r7 e+ q wealth
. h) P3 Z1 c' o z- \. \4 Y1 M life-expectancy 2 j8 a8 n. b) x, r7 P( Y/ F3 ]
metabolism ( b: e+ [! S% t4 K7 b& y
vision
& r9 [/ O# S/ D1 q7 v# c inherited
2 Z" U+ f4 B$ n, m# i$ o]
: r3 S2 K+ ^; X3 o1 _$ o) F; Z, f* h( V0 H0 U! ]- _4 x
& [3 E0 D2 w% E: S5 N# Wto setup
7 [. W: a$ t! f& L: E0 H. n ca& |! C' J1 f( N" l" I
set max-grain 50
" a! Z m8 M* e- j setup-patches
5 Z7 C0 O3 J& D U( Q- ?" T; R setup-turtles; M+ F; L1 f" |2 h& O% Z
setup-plots5 v" L" x& U9 H/ X+ N" O- n! x- s' b
update-plots- G" X, n5 A9 P
end1 P9 p' l8 n) R5 b6 q: A+ i
to setup-patches
2 i. r& B. f% ?8 X% K* o9 W, \3 X/ z( m ask patches, N4 u! s* x4 u3 B+ z$ }0 a' p
[ set max-grain-here 0! p: @, [3 K8 l" ]+ [( L' J4 v* b, k
if (random-float 100.0) <= percent-best-land# i# x& M' x ?2 \& U* S
[ set max-grain-here max-grain( H$ g+ p( A* K8 o: z' N/ ]
set grain-here max-grain-here ] ]5 ^, M0 h! N' M, S( K8 t/ X1 B, w
repeat 5
1 Y: z0 Y$ L2 B2 B [ ask patches with [max-grain-here != 0]
2 i$ V2 r' C x* q w6 J# `# c' F ? [ set grain-here max-grain-here ]) f; I5 s9 [7 N* q3 W9 P1 P
diffuse grain-here 0.5 ]1 r; v3 |3 ~, g
repeat 10
/ D2 r; C6 R, S6 g" L. v [ diffuse grain-here 0.5]
- p, W0 D% P/ S& A) I ask patches
- i/ ?, S" a' f) n( ^+ K [ set grain-here floor grain-here 2 R- `7 u- U2 B. A. G# n
set max-grain-here grain-here
3 `# E2 y8 l7 U8 J$ a9 _* N5 B7 I recolor-patch ]" S6 m* z3 |3 ?6 @
end, k! z% C ?9 p$ F% k9 x7 P
to recolor-patch 1 |6 u8 r/ S$ {- h3 h, D( j
set pcolor scale-color sky grain-here 0 max-grain' ]- V2 U8 m1 Q) j' O% U* I
end
% I; b, G2 z7 K6 ?) h2 E* Ito setup-turtles
7 q6 N( b" ^, s set-default-shape turtles "person"& p. ?: X. X, |$ a
crt num-people; s& O6 S% F' ]# C$ V. f8 k
[ move-to one-of patches
0 X% Z- j# N7 X6 u set size 1.5
- w9 r, Q4 b" J/ | set-initial-turtle-vars-age- z. a3 P# R n( M
set-initial-turtle-vars-wealth
+ z7 T Y+ N) \, @/ j) u" u set age random life-expectancy ], c" E5 D1 V: H. g0 J
recolor-turtles7 C4 ]* A$ y' ?: m% T0 R; E4 ~' q
end
7 e$ y4 @5 Q) j
, w. g( t* x; b; r! ato set-initial-turtle-vars-age' ^! K! P. t$ g2 U! q
let max-wealth max [wealth] of turtles
) k5 W* [- V; h. N* e% P% M% V# { L! F
* _4 b# i9 v7 u ifelse (wealth <= max-wealth / 3)$ \4 Y4 R6 s( ^: E
[ set color red $ Z3 U- R; ]1 i5 m- D% ?
set age 0
0 [. M) Y/ i3 x- T face one-of neighbors4
# s2 T5 E; H* v& h5 H set life-expectancy life-expectancy-min +
% s ]! A2 ^, D% C W: } random life-expectancy-max
9 a0 i. P3 h- g3 d# N set metabolism random 1 + metabolism-low, N) S1 T6 ?2 w' i. L! l
set wealth metabolism + random 30# @! A$ r3 v; b% f' K/ N
set vision 1 + random max-vision' O# O6 t, a* D. @3 {& N" c
set wealth wealth + Wealth-inherited-low ]1 U8 N7 b' x1 U. d2 R0 G
[ ifelse (wealth <= (max-wealth * 2 / 3))
: M, ?7 {% H+ f# @9 h2 T [ set color yellow 8 H( s6 q# U% c9 g, Y
set age 0" N1 d0 _; h4 r, r1 K
face one-of neighbors4 ! P. N8 U& T6 ]0 @' Q
set life-expectancy life-expectancy-min +: o3 Y* F# Y% e; `9 E
random life-expectancy-max + 1
" M" k" z& F" Z set metabolism 1 + random metabolism-mid
0 W+ t0 U$ F- v& S, x6 M set wealth metabolism + random 30
7 F: m& T9 d9 c* X3 L) y, y set vision 3 + random max-vision
& e2 p# @' O$ o: ^7 [* _$ z7 Q set wealth wealth + Wealth-inherited-mid]1 E( _+ l* r5 Y6 }$ J5 ]
[ set color green
* X+ a$ x2 T- n+ z, _& w set age 0
7 ]( O! v( b1 S4 A+ N* h face one-of neighbors4
- a1 K5 n. O7 z set life-expectancy life-expectancy-min +
$ |' G7 Z z8 b6 G random life-expectancy-max + 2. M M0 Q+ r a m0 w: O5 {$ l
set metabolism 2 + random metabolism-up& R9 b r2 |$ E. K1 p0 u3 p' i
set wealth metabolism + random 30# a* w* }9 S/ z8 [
set vision 3 + random max-vision% g- S+ x; ^% Q$ w4 r2 ~5 `8 ^2 W. W+ o
set wealth wealth + Wealth-inherited-up ] ]
' {7 M" g6 M5 u* R4 k
$ h( v$ @" U8 k1 E6 gend% h/ `+ T; u0 p% C# S5 k% [8 ^
to set-initial-turtle-vars-wealth7 {+ e/ m7 l, b
let max-wealth max [wealth] of turtles
6 ~) u+ C& _! T" _$ A set age 0
0 a) K6 u0 x' e2 x) W3 _7 g$ {0 X c: O face one-of neighbors4 9 i7 x/ u5 _: D) u
set life-expectancy life-expectancy-min +7 c0 x& ~; H! e3 G8 l+ f
random life-expectancy-max
! p C3 [9 x2 P# G/ d x3 j* t set metabolism 1 + random metabolism-up& B! X2 K/ t* ^
set wealth metabolism + random 30
% \& y. n1 H0 U2 J) ?/ m set vision 1 + random max-vision + `, q! n N) [4 C/ G. h2 ~
end
' W u }& a6 k0 R7 Zto redistribution
6 H. _+ a2 T% Dlet max-wealth max [wealth] of turtles
7 [- w" i2 z$ U) C1 G. N [5 Wlet min-wealth min [wealth] of turtles
9 S) a( r6 d* q. q$ cif (wealth <= max-wealth / 3)& v; Q9 |2 ]4 f- q
[set wealth wealth + Low-income-protection ]
8 D X5 H4 z* mend
# F. a9 r0 b' @" ?" U% G. ~6 c, R 2 F+ O6 N' c2 t& u# n
to recolor-turtles
. y- j/ A/ n8 N, \4 P$ u6 { let max-wealth max [wealth] of turtles
% S. Z# z6 e/ b9 V ask turtles
- u, q) Z' g* v3 p5 K7 m [ ifelse (wealth <= max-wealth / 3)
" D7 U/ r/ [9 ` [ set color red ]' h7 x) m/ `2 q# ], m! v
[ ifelse (wealth <= (max-wealth * 2 / 3))
, c8 {, H* N9 H. t [ set color yellow ]2 E, E; l* ~% S' b6 {- ~3 W
[ set color green ] ] ]
! J9 R# U- P! w6 b8 G* h1 A ask turtles [ifelse show-wealth?
% t t) `1 W; w0 D! [6 w, B. R+ o [ set label wealth ]! `! ]6 z' R6 y: C' k
[ set label "" ]]5 e* u" p, R- d' b: E b
end
3 W+ ~, H+ z- y: t
1 l e) U v3 r$ vto go* ?3 r {9 ^2 k& ~+ u5 b! e( c" h
ask turtles
9 E; L9 t4 ~0 Z! D8 n! S- j9 ` [ turn-towards-grain ]
( D+ r. S" x) w& ^6 ` harvest
) f" P. ^1 N* a, A4 E+ d9 Q* Y9 w ask turtles% @& l1 a7 C% g0 `. t% @" a
[ move-eat-age-die ]
; o+ ?- a) n- x3 Z; V! x recolor-turtles
8 ~7 V( @2 K2 G8 D) b. p if ticks mod grain-growth-interval = 0
" e) J+ {* A" k' N [ ask patches [ grow-grain ] ]
5 T* l, a: J u2 X' S- @
& p3 G6 P+ B8 E2 S, U) q if ticks mod 11 = 0- G7 G8 R- F5 f! L
[ask turtles+ C+ q. Z) ?; f+ x3 Y- g
[ redistribution ]]
- @9 i$ v q, Y* B8 T- I if ticks mod 5 = 0
" r' J# X' U0 a* ?$ Z" q/ p) _# } [ask turtles
$ ]. A* l5 F, O! ]; Q7 _3 Y [ visions ]]
) N8 T2 P. c" K tick% S; } o; X) y
update-plots
' m2 R3 I$ p. Q! T: xend
4 a2 _0 ?/ a- Z3 J; Tto visions
0 W8 j0 Y0 ~( r/ `7 c) f' T0 Y9 f' Y set vision vision + 1 0 g$ X$ u0 [2 t7 G* W' n* a8 Y/ o
end5 |- y9 m( s& p1 j* u
0 P" n5 B! s, _: G' ~2 q% k
" H, i' d B f
9 p+ i# K9 n: ]% Nto turn-towards-grain 7 F9 n; F# `9 w4 @6 F
set heading 0
/ J5 Q+ w* G2 m let best-direction 0
1 ^; H1 a7 _* x. T8 d& n- G let best-amount grain-ahead. l, _# W4 s% s7 R" N& o) k }; N7 U* q
set heading 90
" F4 h7 q1 H I) L. K' M if (grain-ahead > best-amount)( }6 k* T5 I" }1 n
[ set best-direction 90
1 h( a3 @5 A2 v: v/ e set best-amount grain-ahead ]
5 j$ D5 I/ s$ D1 A, A2 p set heading 180
3 I/ V u) ^. K7 D) l if (grain-ahead > best-amount)7 Y9 U3 A$ s& C+ ~- K1 ?
[ set best-direction 180
, K. c. n" l U r+ ^% b$ l! B set best-amount grain-ahead ]
- L/ _& y, k+ |2 O- m/ g) P* n1 E set heading 270
2 X/ |; x' I. y( }/ K0 g! B6 V# v if (grain-ahead > best-amount)% v- G0 e6 r3 o1 R; v y
[ set best-direction 270
) s2 f/ {* e6 _8 ~" J, e( U. V7 t set best-amount grain-ahead ]; }" m) Q+ B. y' d9 y* ?6 n5 [
set heading best-direction
+ ^# O5 ?: z0 N( a. @) j) Send/ I& {8 C- c: e
& d- |# D! X4 Q8 C
6 v# P, B' _3 _4 l; v K
to-report grain-ahead : B) q- A/ x' ?
let total 0
! \8 E: y# \# e, Y( [1 n% F" i1 U let how-far 1+ H P3 U' W1 d8 d
repeat vision
& `7 w9 X$ j, K7 R3 G. K [ set total total + [grain-here] of patch-ahead how-far
* v$ k8 R, Y! Y2 j8 D4 {! q set how-far how-far + 1 ]
3 L, y4 d/ V+ W, f report total3 _8 g# }: h0 I" B2 j0 A
end- B6 R h; L4 O1 Y u; m0 m# m
' V6 g# O( P; L6 D R, ^# e- e
to grow-grain
# l) P" s( w( `2 R0 @3 B) i" N if (grain-here < max-grain-here), ` V6 r+ C7 z* {( ]
[ set grain-here grain-here + num-grain-grown
; L) p& ?- @# k7 g if (grain-here > max-grain-here)
9 P2 x K" X9 n; ^5 l2 S; T4 S [ set grain-here max-grain-here ]! `1 H2 D6 c$ m
recolor-patch ]
7 F5 Z6 o( i; X" K+ E! [8 v9 E6 Zend8 g/ A$ r) T1 ?; K' U
to harvest
& K# a4 _; q2 \3 c. l4 m ask turtles1 ^, ?; a/ L# i7 A
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]# Q8 Y/ c2 V. P! e/ s- X! s
ask turtles
( ]$ I- z e' `% j: n; u/ Y [ set grain-here 0
% u* }$ u+ o$ o/ W: m recolor-patch ]
; q' R( z! \ [
& j* u( t. l% U- |+ cend5 K+ V9 N9 C7 E$ D
) ~7 v9 S( t, l& _1 z8 {# i" @! X
to move-eat-age-die h* ~4 ~" o. H9 z: X
fd 1
* P& V7 T, _5 X# c/ s" R set wealth (wealth - metabolism)
3 z: z9 r! [, k2 s" Z' g5 @8 a set age (age + 1) Z* ^0 b# _" W. }7 k
if (age >= life-expectancy)) @" m. ]% w; G. R d D/ V
[ set-initial-turtle-vars-age ]
" v; z- D1 I# N: v, d if (wealth < 0) b) R* b' Y* ^+ U+ l
[ set-initial-turtle-vars-wealth ]
" b% h' E6 `# R9 w * q$ z# C4 J' `, ?
end9 O/ z) [* k* w& X1 C
( n: R* e* t6 x2 j% k
' w) i/ D+ |7 E# wto setup-plots
7 }7 C- c, R+ b5 c. g set-current-plot "Class Plot"
, O7 C1 r" B; I1 {6 ^8 m set-plot-y-range 0 num-people
% S. Q- T% H1 o2 u set-current-plot "Class Histogram"/ H5 Z9 G; }, \5 {6 n" V( r6 R* y
set-plot-y-range 0 num-people3 H+ d8 @+ K8 a+ {- p$ h- I
end& n- z% l3 e8 Y. } h' s3 H
$ c: Y: X& V: a7 z2 I7 kto update-plots
* Y( Z) d2 `. V update-class-plot& v4 K8 R; q8 I! K
update-class-histogram- { g/ g+ ~% J
update-lorenz-and-gini-plots/ f$ V, C6 q( h6 ~) ~
end ~$ k4 ?! ~8 l2 r2 a- e/ E# W
7 ^5 r3 {% j% h, ^" K. |
to update-class-plot$ Q8 ?4 k) _; B3 {
set-current-plot "Class Plot"
# b% T4 g( X# R! [4 z' C) } set-current-plot-pen "low"
" ~2 k i' S y plot count turtles with [color = red]% X5 P% P% U* T5 B+ F& Q! M0 W
set-current-plot-pen "mid"# x; G+ n% J7 x% O. U
plot count turtles with [color = yellow]
; R+ q+ A! d. k set-current-plot-pen "up"3 W- v! S8 m- ]$ e; ^
plot count turtles with [color = green]* S7 N7 X; H: f5 `
end9 ?: E6 p6 ^# ^- }
( d7 l* O9 @) \. v7 i* Kto update-class-histogram
$ J4 g I9 i* u" N) w8 @ set-current-plot "Class Histogram"
' ?" P/ _2 ?" ?" P plot-pen-reset0 \# l/ e D5 E9 t! Q; }5 _
set-plot-pen-color red9 ^0 E& G3 h/ {
plot count turtles with [color = red]( |9 V. _: J0 K, }) S: a& T( u
set-plot-pen-color yellow
" Y8 o1 K; ?; D ]( x, w plot count turtles with [color = yellow]
, y' t) T5 z n5 C set-plot-pen-color green. b3 H5 V4 I8 w# X. {
plot count turtles with [color = green]% N5 W6 c$ a; M8 M" A9 s* N8 S
end6 a) d8 W: E4 e9 S+ y( V0 u+ |* l
to update-lorenz-and-gini-plots% j& J3 @6 \( U6 a' @
set-current-plot "Lorenz Curve"8 p/ T7 D, [! D
clear-plot; o+ z/ {' \- n1 R8 x
: w8 A# q( r/ V# T
set-current-plot-pen "equal"
6 |$ T& W- N$ F% D plot 0
% x+ U9 w% ^; ~+ D: l plot 100
% o+ o. _4 G: h# |# ~7 y9 B0 v% [& |+ x8 X
set-current-plot-pen "lorenz"
8 h* [ V2 M( _! j set-plot-pen-interval 100 / num-people
( n; q# y; w8 q plot 0
) ~: n) n1 v2 d9 L
$ c3 C1 j1 [7 l" l let sorted-wealths sort [wealth] of turtles
4 C+ c1 v% [6 A# U6 ^8 r* r" [ let total-wealth sum sorted-wealths) A( O. b; J! f+ i5 g; K7 E
let wealth-sum-so-far 0- J' Y) y8 N0 x: U! {5 d
let index 0
; H5 z) {% x1 V! ~8 n let gini-index-reserve 0
9 |8 T# q1 B; z1 V0 m3 y
9 F& y- J3 S; w; d repeat num-people [: m' w8 d3 s; w/ s9 q. n& ^, L \
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
" d7 f/ q4 G* O$ L; v$ R) ?6 q9 s plot (wealth-sum-so-far / total-wealth) * 100 q# D/ h' b/ [: {0 {8 V' D
set index (index + 1)
4 v1 G' F$ B) B$ `7 l set gini-index-reserve. z5 t3 ?% R" c
gini-index-reserve +
/ j, E$ S9 C* G8 i$ \3 @ (index / num-people) -
" y4 {' r- C! M* e1 K9 b. c (wealth-sum-so-far / total-wealth): |( y0 ^) R4 K
]8 Z/ ~' Q& g6 R
! A# M E9 z/ l! K) a
set-current-plot "Gini-Index v. Time"
6 K" a! K, w+ `4 G* ] plot (gini-index-reserve / num-people) / area-of-equality-triangle
z7 ~! K8 B# s5 S8 ^4 T, g: g. `7 Lend8 x! A2 o2 C' x' v
to-report area-of-equality-triangle) S5 v0 b+ }0 n, y
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)* ?, P. H1 T& C; `, K7 i
end |