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/ \* s/ ^0 `/ J+ ^5 m- F! G
globals, A: U# b6 {7 S
[
3 o5 A- s& H% U max-grain $ L/ v l. q/ I. Z: V5 n8 E
' u4 R! Z1 S9 I4 T' O
]
) v3 D; B8 \+ c! @- @: m" y1 O
% @ k' ]6 p& ]patches-own( \: S( y- M4 D8 b4 Y( A( l5 P
[
K$ R8 K3 ^6 e. ?- ^" a1 K/ u5 B grain-here
; X1 x7 |% x' b4 { max-grain-here $ Z; T+ \* Z5 A. t( ~
]
: Z# M: R/ S- H
$ }+ G* y# y' V2 i5 {4 K$ Hturtles-own. u0 d' k' W; _6 o1 v% H4 T
[8 V* m6 |( h% C% x
age
; w" F- K! _# A/ m2 S3 D wealth
9 `' Y! j8 r" e' i1 B/ P( b D life-expectancy : O& J0 s6 i& ~0 _$ Y+ S; `8 k
metabolism - C1 h- ]. w N0 p1 ^) o2 e/ n
vision7 ]- H1 C! u0 n6 r( d% y- P2 y
inherited + \1 N; f9 v) q: X
]
2 P" \! v! d9 B! ^1 T: w8 i
P$ ]8 B* ?( ^& s# e4 V4 O% ^+ k9 g! S, {& B. R
to setup, Z" X; Y' \- U7 M( i- w) R+ |% k! I
ca+ P; i5 d& Q0 @: T: a$ y
set max-grain 50
& I- k! d7 q2 r/ B6 [( P7 h$ K setup-patches
* G4 [/ n7 Z& S: y# O( k; i. K/ B setup-turtles$ V+ V" A1 p k" `# U* _; y: M; W
setup-plots
# ^$ K" o' F5 ]* ]# T- P! } update-plots
" }! K. g% W* `' k# ]$ A, D/ Send
1 J0 I0 a/ [7 t: J% Wto setup-patches. h. p6 H& [: _' v2 ?
ask patches) l' i$ E0 E; j
[ set max-grain-here 0& c$ ^; U# E; u" E$ U
if (random-float 100.0) <= percent-best-land
) _+ s2 g N. V- P; W; v2 f& g [ set max-grain-here max-grain" R: K& n& M& k0 G- X: n
set grain-here max-grain-here ] ]
' g8 e- d' @$ A8 Z& B- d& }# h& d4 k; h repeat 5
1 u! {- r: F7 I) y( O9 U [ ask patches with [max-grain-here != 0]
' @" f/ T1 E9 f! t' O! D- E: w8 O& X [ set grain-here max-grain-here ]
+ K- n+ z$ b7 w diffuse grain-here 0.5 ]
. ]9 w. q% T0 y! k% z repeat 104 n# n# c( U9 w
[ diffuse grain-here 0.5] 9 @6 _- v; S2 Q) x |# g
ask patches1 X" Y" F- o) @
[ set grain-here floor grain-here l4 j9 e7 \: W& u g, `+ z
set max-grain-here grain-here
2 \% ~/ L& c& y7 V, k/ F) I3 k recolor-patch ]
+ N0 g8 a& Q# Kend
1 m, R! G2 Z* W& H6 ]- v& G3 b0 @6 wto recolor-patch
% e) y+ A9 n, W7 N set pcolor scale-color sky grain-here 0 max-grain
9 j$ }% Q- f9 }0 y9 fend
% k2 \" R% Q ]% Sto setup-turtles3 ~4 [% V0 g1 T9 ^% a1 @9 K8 i
set-default-shape turtles "person"& t# d9 o2 z7 p* W
crt num-people
5 e3 Y9 s" ]. }1 P9 W) N [ move-to one-of patches ; F" v9 c) u+ h+ m: ~ u
set size 1.5
@) D; C6 k' y/ ]% k! G set-initial-turtle-vars-age
( j) _2 {) C% _$ I l+ ^ set-initial-turtle-vars-wealth
n: R; D0 |1 ?% C set age random life-expectancy ]
9 m6 Z. Y8 [/ G recolor-turtles6 w2 D% i/ |; _) T X# Y- c
end- [, t: ]5 C; G5 c$ N f& ~
: `2 P8 ]; U* _! l" ^4 p
to set-initial-turtle-vars-age
* m# z$ M! Q2 `- n- u; r let max-wealth max [wealth] of turtles, P$ X% p/ Q9 `7 n, l& L
8 x p7 E J1 m. N6 p4 V, f4 u# [ ifelse (wealth <= max-wealth / 3)4 S& {- D+ w- ~$ p H, d0 Z! }
[ set color red
& H# r* M. s9 g* K- l' k set age 0
+ y- [9 N. M }: ^2 h* ~ face one-of neighbors4 0 Q0 S* O& {% y
set life-expectancy life-expectancy-min +
$ I) h% [0 K2 Y& O/ ^ random life-expectancy-max
S" w. R" x$ m) z, C: e1 | set metabolism random 1 + metabolism-low8 i) Q/ ?8 y! C. L: P
set wealth metabolism + random 30* W% p: `4 r3 Z# r- ]& U! I
set vision 1 + random max-vision
. l: f, R' x# m! T J set wealth wealth + Wealth-inherited-low ]" ^4 a. b6 U. s
[ ifelse (wealth <= (max-wealth * 2 / 3))3 f0 x \: J7 r1 `$ e& N4 Y2 s
[ set color yellow
' k0 b" s6 B0 C5 m0 m* ] set age 0
. |: h' P$ Z4 ^8 j! m' _ face one-of neighbors4 # `: G0 E' z% |/ {9 ?
set life-expectancy life-expectancy-min +5 J% f) \1 N! G, ?: C) b5 b1 i
random life-expectancy-max + 1/ e% Y. S; B+ v e8 x. H: a
set metabolism 1 + random metabolism-mid4 s9 ~: J" L2 w) _( p& W
set wealth metabolism + random 30% t; l( ^% _# ?& C7 W: v
set vision 3 + random max-vision) ]6 L0 e6 K4 ?% U! U, w
set wealth wealth + Wealth-inherited-mid], w4 T% I( g$ [6 x
[ set color green , \2 ]+ i# N S
set age 0! X) `0 a& ?2 K* d) \
face one-of neighbors4 + n. c8 V4 h8 f$ F
set life-expectancy life-expectancy-min +
: B3 g- P4 r$ ?$ D random life-expectancy-max + 2( X9 J# g, [5 E! a) t' Y4 ~
set metabolism 2 + random metabolism-up! c& s3 a2 J% x- L; q6 b! p5 R
set wealth metabolism + random 304 Z5 q2 q) f4 @# \# K
set vision 3 + random max-vision- m2 k/ _! b5 S" M/ Y% U, @0 b- S
set wealth wealth + Wealth-inherited-up ] ]
8 F, C' @( x& W" B1 O 9 a/ y1 [8 @' q- ]% g( t9 h# h
end% S4 M, [# ?7 i! y- _
to set-initial-turtle-vars-wealth# N* ]$ f0 M* Y2 T- m$ j( |
let max-wealth max [wealth] of turtles
5 s' u0 d& p3 B set age 0& c# m% F! y& u) Y8 g
face one-of neighbors4 5 O% j% x; g9 V
set life-expectancy life-expectancy-min +& z3 d8 U1 y) @) c3 d: Y
random life-expectancy-max 0 |9 ]! |7 T# h
set metabolism 1 + random metabolism-up5 x8 X4 [# p. d5 z
set wealth metabolism + random 30& E4 m6 ^2 |6 i- Z. @5 m9 E
set vision 1 + random max-vision
& _ P$ P3 A9 q$ M! B9 C tend
5 H( c: R0 U4 S0 W0 @1 t! ]to redistribution, ~3 \6 c! s W1 s5 ?, ~1 S
let max-wealth max [wealth] of turtles8 a {+ a s0 @* S& E
let min-wealth min [wealth] of turtles! M0 h5 {8 n1 r& j
if (wealth <= max-wealth / 3)
9 I O- P. N8 i( T/ ^' M [set wealth wealth + Low-income-protection ]
6 k: U, |) C4 h" C' ~9 X3 G/ D9 H$ |end& w* c* M( p& n) ?+ g9 i# U
8 l7 X* I9 @ Dto recolor-turtles
7 y/ a: _2 @% H3 X$ F* t. s( H- P- _4 h let max-wealth max [wealth] of turtles4 T! y7 S2 i+ `$ `: I
ask turtles2 _9 h" F; {% j7 P( L4 O
[ ifelse (wealth <= max-wealth / 3)
# N* ]1 y8 @* T& ~ [ set color red ]
0 ]) v+ T1 h/ @8 N; | [ ifelse (wealth <= (max-wealth * 2 / 3))( v' }% L9 o- n+ T1 N% x
[ set color yellow ]0 g; ^8 r/ ?2 G7 u/ s8 b
[ set color green ] ] ]
* V f# Y, Q2 g/ ]6 \% \0 p/ m ask turtles [ifelse show-wealth?
* l3 i/ P1 C4 I# ` [ set label wealth ]
0 u3 i7 ?( _, R3 L [ set label "" ]]+ S9 E3 N3 p6 |6 j& E1 L
end" l8 G# W; l% P
/ P3 X3 }$ ^% R0 m z* l2 s* Ito go+ l8 ~6 I9 g* e# P) B6 y; K
ask turtles: h2 [* _' i1 w8 L# d
[ turn-towards-grain ]
& F8 u. `; `* q0 O& o harvest2 N" ]8 w+ D& A% w' k u6 a. u9 P
ask turtles& y6 o, f" B w7 I% ^
[ move-eat-age-die ]7 l( j8 I0 e6 j8 N
recolor-turtles
* ?8 r1 j/ `' b( V3 W$ ` if ticks mod grain-growth-interval = 04 M" n/ H @( q' T# G
[ ask patches [ grow-grain ] ]
; ]# R! j' C2 V) q, _0 T % t' b6 a9 b+ n" N" M* M
if ticks mod 11 = 0
; b3 m* \/ Z, Q* [0 n8 P- d8 G [ask turtles
8 A" }2 I+ \& e- r% o8 z [ redistribution ]]1 T, ` I) b1 S- T$ b8 t
if ticks mod 5 = 0
, E9 W$ f+ x. g1 K) K9 b) T [ask turtles6 v) N# ]* ^5 K+ ~4 d' ?
[ visions ]]& S% S- [+ ?% q( r* q. I r1 E
tick; }, Y+ c9 D* g$ a8 i! ^; M; x% N" ^) x
update-plots
: |2 l( ?" y% P' M) e: gend
9 c$ | P( U' F1 a2 [" \to visions ]: C" y/ y0 s5 m
set vision vision + 1
8 r5 l9 B+ P1 ]) Q4 Cend7 [0 O, B4 G, ?7 w
0 j& Q9 M" o0 `4 c$ j- q- |: j* D+ G+ c: f" k
" M# F o# s% F" x
to turn-towards-grain - n* U( |% Z( T6 S' [/ i3 T
set heading 0
" J0 }4 {. g$ k5 f' U2 u5 L let best-direction 0
# c9 D) h/ W! k9 H let best-amount grain-ahead, {1 A* t2 v( R" [- [6 J
set heading 90! u3 j6 {# _+ _& ~- _
if (grain-ahead > best-amount), C3 o0 R# S# V1 {* z
[ set best-direction 90
$ T7 e) r$ `# ^4 N/ H2 b! n- L set best-amount grain-ahead ]0 Z5 Z! _2 b% @' y2 O A0 D$ q
set heading 180
$ e; x4 L3 o8 _0 { if (grain-ahead > best-amount)& @! s$ i* }9 f& o. d
[ set best-direction 180
7 N3 n8 A" B+ d8 ]: ^1 h8 L set best-amount grain-ahead ]
9 V5 k6 |2 `$ t( g' V5 a- [ set heading 270
' w9 g' Q! s( I: e. q% n7 D if (grain-ahead > best-amount)
5 \2 I$ h" l; u [ set best-direction 270! q6 t/ J1 K( p! T. t; N) h/ g
set best-amount grain-ahead ]8 {' A" X5 g) U
set heading best-direction, p/ @2 A2 W, K L
end
5 q' H( L2 h6 \: x$ C
7 p+ N5 h) E$ N5 ~; y* y/ }% E7 d6 X' U( r
to-report grain-ahead ( a: A. J( U# o1 ^: n. W Z7 o; O
let total 06 _. |4 T4 `( d( C5 | ~* _
let how-far 1' m2 j, Q% k. x* e( ]4 l |6 C
repeat vision8 q$ B$ `& H0 _- x8 I0 V, L
[ set total total + [grain-here] of patch-ahead how-far$ c5 F6 v" ?9 r1 f
set how-far how-far + 1 ]
: u6 Q2 ]# s' V; q! X report total
( T% S5 T3 W+ @" U O% lend' }, V5 {6 \- r! d
7 Z4 B) j6 w+ z) kto grow-grain
- b" l* o& F& W3 c; T8 U: h if (grain-here < max-grain-here)
1 u9 D4 O- u6 z" @: r [ set grain-here grain-here + num-grain-grown( t- j' X- _& ^. V* t
if (grain-here > max-grain-here) ) i- k6 W% M' Z" }$ p* A7 j
[ set grain-here max-grain-here ]
4 P3 P. X+ G4 `# Z, n recolor-patch ]
" h+ x3 i& f9 K3 O! M% [end
5 P, S! O F8 Uto harvest
7 Q' D" z& I- y" i ask turtles* ?- L# h3 t# ?1 {5 \$ m
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
3 [0 X$ V9 e- K" \# m ask turtles
: w7 t5 {- G& W( l6 l4 u* d [ set grain-here 0
# R' K" ?+ x" _7 `8 n: Q# [ recolor-patch ]
( ?1 G8 d5 j4 T1 z) B
8 q7 {: |( U* y% T* Iend
. }8 t9 ]. L4 u' N+ z
* c' y. T+ G3 h) H9 G) b2 v1 jto move-eat-age-die
- Z0 ~' k. e" p5 m8 n fd 16 t8 ?! J O- w; b. `
set wealth (wealth - metabolism)- g* ~5 V; |8 v4 v; N
set age (age + 1)- g: e; ~& U. J0 Z" ?
if (age >= life-expectancy)
& R% d" y& g7 P. Q1 Q [ set-initial-turtle-vars-age ]
) a9 J7 ]) ]1 g4 }' {) S f3 L if (wealth < 0)
c; w% N" J0 B& W [ set-initial-turtle-vars-wealth ]1 M, X% H* {+ p2 G; l
8 m" |- Q/ e* |) n1 d' Tend& a4 ~% q) ~" l4 K
! _# L. t r: U! }
: `5 o/ s* t* q/ A e/ Eto setup-plots
8 D* ]7 D' X. Z9 D a set-current-plot "Class Plot"
# V& P1 ]2 `1 q set-plot-y-range 0 num-people! I: j* _3 ]2 P0 w6 V* p; Y
set-current-plot "Class Histogram"& e2 A6 ]+ n2 K0 E( D- @% b+ c
set-plot-y-range 0 num-people& K- |8 j) w/ w) k. S+ t! Y
end
4 O. O$ |. y+ z* B1 X
; ]+ Y o6 `2 T) X R- E! bto update-plots: t7 Z8 `, R9 ]( |+ v
update-class-plot
+ I. h1 j6 P x( t {) Q update-class-histogram7 O2 j: O$ i; c& f) q
update-lorenz-and-gini-plots$ u2 A+ n# l: A2 t% B9 J& c
end) M% W' }9 {5 Y- [
$ h% u" M$ G9 v3 U$ j6 z( i9 j. p/ B
to update-class-plot. [6 |, o! T h' d& s$ Y
set-current-plot "Class Plot"
. Q. H1 C$ H( M H: a, E1 h$ x set-current-plot-pen "low": n9 P+ K1 c" I, q' [% T$ x
plot count turtles with [color = red]
$ D- W- J7 q+ Z3 G# \+ ^, u3 m set-current-plot-pen "mid"
2 B4 v; o" g9 l% q( H plot count turtles with [color = yellow]
) _0 ~$ ~0 M1 g set-current-plot-pen "up"8 o$ V" d3 z/ H
plot count turtles with [color = green]
& m% ]+ T7 R9 s0 ~9 Vend9 e u! f( `$ a& K+ g1 S
2 p/ `$ c& o) A. W# N, Q% n" vto update-class-histogram6 {" h" g% x R7 g& T
set-current-plot "Class Histogram"; y; q" e- y4 E7 c1 e
plot-pen-reset9 m5 ]* {+ J; a% j2 D
set-plot-pen-color red
2 }) m3 k) O! d9 l3 x/ `1 i plot count turtles with [color = red]
q) O$ x2 l; `3 l- C set-plot-pen-color yellow! ~: R! W. ~9 e0 p
plot count turtles with [color = yellow]
, b, _& I5 f/ {& x( \0 x; o set-plot-pen-color green
0 t- I% I o; K, z6 k) r plot count turtles with [color = green]
6 A) ^, S" O- F' X5 A0 Z8 _1 Kend
( v: D6 @1 a6 |3 W1 e* ?to update-lorenz-and-gini-plots. p; _7 U x/ h* K
set-current-plot "Lorenz Curve"
$ ?5 n6 l% e/ u( q" | clear-plot
_* W7 S/ S7 q' j/ ]
4 M4 C- @2 Q0 s. F+ C% [ set-current-plot-pen "equal"% `. G9 Q! q3 O& ?
plot 0! Z2 t* z# H/ ^9 V
plot 100
. Y6 h1 ]! h+ t1 J t9 m( h
8 q8 S2 z8 p" |1 } set-current-plot-pen "lorenz"4 M+ `. J2 _! S( R4 ?3 D0 m8 l' x
set-plot-pen-interval 100 / num-people0 v, u, h$ H. [. ?
plot 0
! |. Q$ }+ u2 d' G0 Y
) W L# b0 y6 g, G' [' b# R let sorted-wealths sort [wealth] of turtles) m J/ I0 u% ?7 H# [
let total-wealth sum sorted-wealths
( l$ r6 F1 y! w7 i- o let wealth-sum-so-far 0% G+ k W; U& J5 Z( |2 p. }; S! U
let index 0
3 W* C. B( t c7 S3 E' x- E let gini-index-reserve 0+ P0 W) v& W! a1 O, m8 V" _
t! z! W2 h2 L7 y
repeat num-people [
" _, c6 c$ \/ \6 _/ h set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)3 f8 @. r+ n1 j4 c: Y! i
plot (wealth-sum-so-far / total-wealth) * 100 `7 u/ _6 u, Q7 o: Y1 w3 x& ^# m
set index (index + 1)
7 ~; ?& |8 W8 p! `3 z( S2 Q% G set gini-index-reserve
7 P! W6 P& L; g gini-index-reserve +8 N, W6 W& P' Y ?' v3 g. k! e/ R
(index / num-people) -# w& e* f! R2 ~9 [" G# J
(wealth-sum-so-far / total-wealth)
* d9 \* K' |2 a7 H+ U I* j; S ] p2 K, N. E- A( _
, [: g: J/ T. C
set-current-plot "Gini-Index v. Time"3 n/ [3 X i/ c) Q9 G3 Q) _8 Y& ^
plot (gini-index-reserve / num-people) / area-of-equality-triangle
! X% X7 q8 G+ @) Xend
1 U4 j: ]! u7 `! @9 p* H4 ]* Fto-report area-of-equality-triangle7 R" z5 {. H" k+ s( a. \
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)- e7 r! z8 s) k0 c, Z
end |