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
- \, ?% J! M5 t" e Hglobals
4 B$ G9 _) [% O( Y( Y# N[
6 _' G% `5 K; k& Q) f. L, r1 x5 k max-grain
- `7 ] W: r6 `( p: Q0 I$ n. n8 w
3 ~+ K& y5 I! Y0 W+ W% ^7 q]
" e$ c3 m; B( @, f. Y+ I( t6 X9 {) E) b, b" |
patches-own
( ^8 m: X" h# U! H9 h8 \' t3 u[
8 l8 P4 g; F* d+ G3 D% @2 |+ o grain-here $ ]4 ^5 \, R$ [# E h
max-grain-here ; G% }6 Z( q. G. y/ H* o" x9 ]
], q" |! E. L6 }. O- c
$ J! C! N- J% [. ~
turtles-own
- L- s% `" d, ^! }- J[
6 N& `, j9 K( ?# S age
2 b% c. J) [9 j, ~ wealth
: w y; V7 @( \6 ? life-expectancy
' ?8 s% U: @' F6 P1 ], V% a7 Q) I# \ metabolism 5 t8 w4 M$ Y% e! e
vision
8 R, W8 |7 c% G2 @9 B) A inherited 1 ~' A/ a3 c( S8 Z9 @
]" q) A" S7 F( j0 {
! O8 R# {5 l5 U. s' V
Z# V+ A( ~6 y+ L, g- F$ Q& yto setup' J- Y' B6 \" p( B$ H
ca
& s/ \: g9 K2 L) s- a: M set max-grain 50
% ~! H8 r0 l6 D/ \% S4 r' S setup-patches
8 R& Z8 L# K' k, b, V! @ setup-turtles, B7 b1 [! A6 }; J1 n+ Q
setup-plots2 z( Q5 G/ t* `+ B/ g
update-plots! d2 J6 S7 K l8 k" k; ~- { K7 |
end6 K5 y4 o( n9 ?
to setup-patches
+ L! f. b9 q4 x) F3 J" { ask patches
$ `( M* I; _! o' D7 J/ b# n [ set max-grain-here 05 w9 h$ Z+ y7 X/ W; Z
if (random-float 100.0) <= percent-best-land* K0 \9 {$ n8 M9 ~! G# Q3 r
[ set max-grain-here max-grain2 d* T! k) P* Z# C5 v) f- g
set grain-here max-grain-here ] ]
- @3 K& L, y6 _- r repeat 5
) }. F! y0 d. A* c& X" t/ \$ ? [ ask patches with [max-grain-here != 0]
0 @+ T5 m7 B y# Q, J) C [ set grain-here max-grain-here ]% K! v) T. ~* H' Y* f- W% l
diffuse grain-here 0.5 ]
1 u/ D5 Z0 S! p3 U repeat 10
8 j {. [7 W( D9 _2 u( d7 k [ diffuse grain-here 0.5]
# X# p1 W9 F) c7 h. H7 w ask patches
$ B/ ]9 x; ]4 q1 t* l1 t8 p: G' V [ set grain-here floor grain-here
- i0 J P( G4 e$ b+ a; s0 H set max-grain-here grain-here - M8 z* [6 o" ?6 G9 B( b# A
recolor-patch ]$ F& V6 n+ ] W( K0 N0 ^5 M
end# @$ L s, _0 ?' S4 H
to recolor-patch
+ _9 d, \( S2 C* \8 @: a set pcolor scale-color sky grain-here 0 max-grain! V& ?& f7 L9 U# g
end- z: a8 l/ \5 K9 ]+ h) q1 A
to setup-turtles/ G$ z/ C f; n& B$ T
set-default-shape turtles "person"
, b0 f3 G- N, X& d crt num-people! @" J1 k" l" T! R" j; U9 K
[ move-to one-of patches & p9 b7 W( r1 d5 n d! X0 J
set size 1.5 2 m) S' e+ n8 w9 K1 ?- A
set-initial-turtle-vars-age5 ^( w8 L+ V6 ]
set-initial-turtle-vars-wealth
) }2 B1 G# n. x8 T2 c1 w" `) A set age random life-expectancy ]! o5 j) O9 x/ Q2 q: q
recolor-turtles/ p% H% { n! Z0 \/ e
end/ p( l' I. W0 p! O+ F$ s
. v) M2 ]2 a! ?1 n/ P- S; h
to set-initial-turtle-vars-age5 X% s+ { J' c/ a" u/ e
let max-wealth max [wealth] of turtles. X2 J+ Y+ E0 J
8 I1 g8 q1 [- Z7 J7 b( z
ifelse (wealth <= max-wealth / 3)8 L" s* W4 g& v% c5 e' M
[ set color red 1 H: v7 Y W$ o
set age 04 B/ o. t4 f1 Q4 c
face one-of neighbors4 6 o' J. ~/ @2 Q' Q! |" z
set life-expectancy life-expectancy-min +4 U' I: z9 [& u# n( V* K! e
random life-expectancy-max
7 b+ Q9 l5 g, z2 d; L& Q set metabolism random 1 + metabolism-low8 P) s1 j5 O) e) s
set wealth metabolism + random 30
$ d# b3 ~1 s1 [; ^' G, o set vision 1 + random max-vision
8 N3 V. u) D' C, X `6 V* J set wealth wealth + Wealth-inherited-low ]) B' N/ j. z$ [$ V& J8 e% G. K
[ ifelse (wealth <= (max-wealth * 2 / 3))
& E- ~5 Z* i; T5 z/ P$ f N& {5 k [ set color yellow
, M* I# R* M: i& r: Q6 G: ? set age 0
x( S4 U* n# C" L+ e face one-of neighbors4 # I; R$ I, e( G9 a# x( `: ^
set life-expectancy life-expectancy-min +
. o/ C, s- U% Y random life-expectancy-max + 1
/ d/ U: \1 v3 z! J, F8 C/ Y set metabolism 1 + random metabolism-mid
9 A4 a0 F9 E9 C& Q- p set wealth metabolism + random 30. E1 v$ d* [. y
set vision 3 + random max-vision% V S% L3 N- V3 I; {
set wealth wealth + Wealth-inherited-mid]
# ]4 z* r5 s z% j6 j$ E [ set color green 7 i B' V; l0 ~ C- e
set age 0( j/ o% c) N W* q2 n- b4 F
face one-of neighbors4
: y% H2 _7 y! i" J set life-expectancy life-expectancy-min +
4 a+ W# K+ f6 `: ~! g! l% b random life-expectancy-max + 21 b% J$ ^7 v+ m
set metabolism 2 + random metabolism-up7 l( G4 {; N3 T0 F3 ~& S
set wealth metabolism + random 30) ?( }0 G% @$ I0 E( M9 @8 `
set vision 3 + random max-vision
, d* O8 L7 l2 _; @ set wealth wealth + Wealth-inherited-up ] ] 7 S# l5 e( d7 m% z( {) r8 N
. G) ]3 q2 l9 S! x* W F# F
end
5 \7 g( x1 j; m1 J) Cto set-initial-turtle-vars-wealth; m$ t/ `5 M, `: z+ b9 _# T. H4 c+ C$ _
let max-wealth max [wealth] of turtles
" s5 a* h. h. N8 k set age 0
9 \4 |& T0 q- }( J# p i6 h9 f0 s face one-of neighbors4 ( C% O9 R. M$ i- {! n
set life-expectancy life-expectancy-min +
4 M/ Y7 F" T- _" A2 N& l% H4 S random life-expectancy-max
/ C8 b7 K5 S$ ]0 u* Q( I set metabolism 1 + random metabolism-up
2 g) p2 O+ a7 r' p g set wealth metabolism + random 304 t0 A1 @& Q k4 t
set vision 1 + random max-vision O' g1 r0 \, r! w3 H3 P; S
end$ i! ^- |& m* [' {
to redistribution" c, u1 A# J* {4 `; x- F+ Z
let max-wealth max [wealth] of turtles9 i" c; A, m! G$ T& D% E/ Y
let min-wealth min [wealth] of turtles& [* k. p+ F! l4 N
if (wealth <= max-wealth / 3)# ^4 e* a/ q6 |1 }
[set wealth wealth + Low-income-protection ]
3 S; p0 C2 O0 v. ?/ X- g9 Qend
$ d. [4 A! U2 l3 ?9 i ) T; M, k$ {4 t' v5 b
to recolor-turtles2 j; R% R" R8 f& G# P4 B; Y- i" I6 u6 _
let max-wealth max [wealth] of turtles
+ Y; M9 @4 [" R) M2 g ask turtles
3 x! s2 t# Z, Z( B& G" H; A9 Y [ ifelse (wealth <= max-wealth / 3)! o: t, q: Z! d( U. E! s; K7 h
[ set color red ], D) N; [& k; W( _5 D
[ ifelse (wealth <= (max-wealth * 2 / 3))
& r$ H) G, t8 y6 u; U9 W [ set color yellow ]$ c t4 q+ K" P0 ^( @
[ set color green ] ] ]. A+ J+ k3 L( u: K" G
ask turtles [ifelse show-wealth?
5 h+ D! N2 A2 M% C. h) ?1 v# p [ set label wealth ]
7 l5 H' I: D. K( P [ set label "" ]]
& b- @" I0 p+ @% B) H( fend4 i7 c Z9 S8 b) z9 D
( q; b8 x& }( J5 p* O5 \8 V( a
to go
: _, V& o7 r7 O2 Z ask turtles
( _ s$ Q' J* Z6 B% O [ turn-towards-grain ]
) R7 m7 \+ D' a harvest
9 b( f- s/ Q" c* L) ?2 s* D5 F M ask turtles& C, A5 m6 z) Z4 q/ W
[ move-eat-age-die ]
, }. V- ]& i( Y! ]: |) y- i recolor-turtles
' {% p- G4 {7 X, c if ticks mod grain-growth-interval = 0
* M5 l# P% ^4 D0 L& d [ ask patches [ grow-grain ] ]1 ]) j$ b k$ R! `1 e1 q
" s. w% T/ O7 P8 D
if ticks mod 11 = 0
7 R0 G& d( I" j! g7 ]4 I1 j [ask turtles1 U+ D- n" ~3 J. k8 B
[ redistribution ]]9 I) ~0 u2 c2 e6 e
if ticks mod 5 = 04 F% F0 Y) J0 Z5 m" C2 D
[ask turtles
& I5 r! F7 [6 F& t& z% J [ visions ]]: V5 V4 d) {! L2 z
tick
- `0 X- x; o$ ^/ Q6 x* v5 T3 l update-plots
, Z( G; }7 C2 y! z9 b: _5 iend
' s2 [: S1 C; e' C% ^- Fto visions& n# P' D/ H% e7 r6 N `2 x
set vision vision + 1
( p5 N* X5 E0 z1 dend! T. a# [4 U+ u+ M+ b
/ _2 E5 G7 v w
% X1 |) t8 g5 }, S
3 J- z1 S8 i% R2 r* Zto turn-towards-grain $ @- K) }* x' P0 P% c
set heading 0
* ]! B0 W+ M# J$ h$ ^ let best-direction 03 a- ` L( r" e+ m2 W9 j" x
let best-amount grain-ahead
9 O: Z( x; v* M U Z5 t# V set heading 90
8 D* O6 @& p1 J0 x if (grain-ahead > best-amount)
* H) x* l# @- G [ set best-direction 90
0 E) A5 z, \3 v6 K$ ~0 o set best-amount grain-ahead ]/ m6 o0 S- y4 w
set heading 180 Z& A9 X- f8 M6 k9 U* u* C# a% ?
if (grain-ahead > best-amount)
% c7 U! \: [. y# J" t3 O, n2 N, k [ set best-direction 180
5 c9 x; L) C! S set best-amount grain-ahead ]$ E$ F* ^9 f1 t, t
set heading 270% q- |' i0 _: m u# j
if (grain-ahead > best-amount)
' G# H6 F/ s+ a4 H, e9 f5 N [ set best-direction 270
$ k( ]! U! w) L set best-amount grain-ahead ]
1 D3 A4 {7 L8 G% c# A: k- r1 Z5 b+ B set heading best-direction
# W! G0 m4 |# c+ }) `! J3 }end
5 Q+ n# }1 x" ^/ T1 o8 K, x! K. p: W" ~3 e: J+ O5 x& S
0 @: p# Q* V& W1 Ato-report grain-ahead
( o3 s" M3 m* }4 w let total 0
C8 G) E: U6 y- K* ]2 \' L! [: E let how-far 1
' O, p5 Z: P. P: K- b repeat vision
$ N$ K! B* y2 S8 C5 c [ set total total + [grain-here] of patch-ahead how-far/ y2 O8 ?$ J1 I0 B
set how-far how-far + 1 ]
M7 \ t6 q0 w: t* _ report total
/ R( U( l( ]: R9 lend
, e Y; p! s' R/ c9 n: F0 v) C; K% U6 L- `2 y( x# g8 h x
to grow-grain 3 a4 p+ Y. `2 P! m1 [
if (grain-here < max-grain-here)
& Q$ R0 O: |& Y [ set grain-here grain-here + num-grain-grown
( v6 K1 r2 l" d3 x8 M/ a* O! q if (grain-here > max-grain-here) . Z8 W0 K, v0 r, R
[ set grain-here max-grain-here ]6 B" u/ g4 l" f7 r: @
recolor-patch ]
- P- g }, @) Rend2 {& a0 A4 b/ h2 @8 Q7 s, f0 [) A
to harvest
: h1 p7 m! o. _ ask turtles* E! z9 C* [( k) |3 q+ [
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
+ h5 H$ o; K" m; ? ask turtles
1 N4 o& p& ]) B# n( h, P c [ set grain-here 0
& R+ v% @& b5 F9 ^3 K/ d0 D7 x* ] recolor-patch ]
: Q+ U! R& U5 u1 b6 J
`/ Q3 c- |: L5 C8 Z2 q, X& lend
, P% ?+ n6 ]% U7 H
& Z6 ?- K* p3 e) E* ]1 }; Gto move-eat-age-die
" q8 H) ^0 Y0 C" u+ {1 J fd 1" {3 T3 ^7 r- `) L1 N- o
set wealth (wealth - metabolism)
- k6 D0 {7 z3 v7 Y$ y2 J+ R) z set age (age + 1)8 L9 H( ]4 f$ P j1 f' t
if (age >= life-expectancy)
! K: ~0 @- S9 g* d2 @/ Y% n [ set-initial-turtle-vars-age ]5 U5 p4 f$ z. A" x+ |0 ^6 C
if (wealth < 0)4 B: ?/ d7 w. `. U5 R! L
[ set-initial-turtle-vars-wealth ]
% |0 A3 a o. H: j
9 [! e% I; E. A+ j! `end6 V% o- N; z+ @" a: f
, f4 q2 x% n6 k; A3 x+ f8 N. p
( t' s' {( N: u' y
to setup-plots
2 q! ]8 y* r4 _* I set-current-plot "Class Plot"
6 R( S' f( H# N: z) _6 t set-plot-y-range 0 num-people
9 K: m' m/ I# f" Q# v" X# u! ~9 L0 M: b set-current-plot "Class Histogram"- X' r. L" o5 T0 z2 U& b
set-plot-y-range 0 num-people
9 z4 k5 L% w: E+ lend
/ P7 k/ c8 ?! |# q& V% K( }( U2 b* q9 u5 z
to update-plots, ^, Y/ ~& b6 n# w# [4 z: ]3 p
update-class-plot
( H# _5 N' C) o/ t; }2 U. t update-class-histogram7 `% R% J C* |1 H- m- S
update-lorenz-and-gini-plots! y4 a" R: m4 {6 B$ \! d# V
end$ C" A# ?& x- f2 C% R6 B% X3 x% C
5 J0 S- W0 g! l- j
to update-class-plot
6 E: |; D, i7 b/ ?1 J set-current-plot "Class Plot"
5 {$ P% M: `- S1 ^: N set-current-plot-pen "low"2 q' d. }' p* w- U) ]
plot count turtles with [color = red]- t3 ]7 o. g! `. d( v
set-current-plot-pen "mid"
& ]1 }7 q" S- \* `; ]6 h5 a0 K% i& r plot count turtles with [color = yellow]
0 i& A( @/ \* D# Z+ L8 i set-current-plot-pen "up"
! f( c$ P& Q0 r2 {: V9 ^ plot count turtles with [color = green]
' W" i) l- `- C$ p. p; _1 U" Wend% [; l) a3 {9 |) S) k; O
2 H/ |) |2 c/ vto update-class-histogram; \6 N1 X. k" }+ ^6 }
set-current-plot "Class Histogram"! K( Z( Z) J( a. a; O
plot-pen-reset
* A9 @# h/ W: y, J, ^4 X# K D" q set-plot-pen-color red
2 w, c- D# b; e4 ^* v" I1 m8 @ plot count turtles with [color = red]
! r6 l/ D' Y% f0 ?% o. T9 y set-plot-pen-color yellow
8 y0 {2 n+ r( a8 L* p8 w$ h' o plot count turtles with [color = yellow]
* f+ v6 ]% {7 k set-plot-pen-color green
, a0 x* Z; N) z0 ?. ?: @6 o3 f- w plot count turtles with [color = green]
$ @9 K5 u- y* W. Xend
* I* B5 {' G" j" yto update-lorenz-and-gini-plots0 N2 l! l: z4 Z6 |
set-current-plot "Lorenz Curve"! ~: H e, h n, I
clear-plot
4 J! v8 b- b- c, v# a
4 @) z( | P4 u$ u1 s, W4 Q set-current-plot-pen "equal") b) J) V% p( ^9 h+ ~ c
plot 0) `& ~! v7 P0 t4 e
plot 100
+ N2 b2 I3 Z9 H% N! F! ]
% v, {2 E/ s; M2 ~ set-current-plot-pen "lorenz"5 W( H# f+ q( |
set-plot-pen-interval 100 / num-people
8 E$ \6 B2 u* K2 C plot 0
+ T' K2 s5 q1 l$ R. Y( w) ]5 ~( ?, v8 O5 Q
let sorted-wealths sort [wealth] of turtles
( j3 t* J( I6 }* L% T: I0 h; a let total-wealth sum sorted-wealths
1 A( e7 W$ b4 ~- |8 Y let wealth-sum-so-far 0* x6 y" N' \( I, X
let index 09 P7 a; X0 m% }# E; E* _" x
let gini-index-reserve 0
- T5 u! p: n. c5 w- u+ R0 ?
$ s d) R7 s/ q* }: h# ^ g repeat num-people [
9 a/ k5 ^4 [( n: R set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
1 {+ e/ ^4 N- G8 ?% v& V* S( c- ` plot (wealth-sum-so-far / total-wealth) * 1003 i2 X" X8 Q# R, g8 F; h. e
set index (index + 1)9 J. D2 X9 Z2 H! f
set gini-index-reserve
; v$ [' p4 _' q0 S gini-index-reserve +4 e/ G; d% {# g! m$ J" `) s
(index / num-people) -
3 T" |) X: X: [# c, H( q (wealth-sum-so-far / total-wealth). Z6 G0 d2 s) I1 ~
]
$ @4 m" _# G! i; p: h( g3 _' p7 g& }, M- d
set-current-plot "Gini-Index v. Time"
- ~+ s, k+ ^; c6 g" N% W; ~ plot (gini-index-reserve / num-people) / area-of-equality-triangle/ }+ ], i- h% L) ?
end5 _. U9 S. ]( M6 N4 z( F
to-report area-of-equality-triangle z/ E. g& V( T9 Q) }
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
# U) {1 L" r1 R a% P, I# ~end |