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 z. p+ Z' y0 z0 a x6 b2 @
globals
( F9 u* t4 `3 z' m[
1 ^! O/ W& W: Z8 x) d max-grain 6 f3 x& D- F, p' ^8 P
W( ~+ q6 }& g( D5 @ {; r
]
- D1 o ], _" O5 m
/ @) C! P, J8 {% O7 L1 Z) {, H g$ ? Xpatches-own
5 ^7 y0 w8 c+ [& I0 l( F[% A, }4 J" C: Y& p% ~# Z0 ?
grain-here 2 j* j8 o# t/ l8 h' }! S
max-grain-here
# g3 j9 M, ~# B3 `1 m]
. _" {$ u- O3 X
) G8 M5 x( |5 X1 R4 H5 oturtles-own
" u: P' Z( C: h4 @+ v[4 `. U D) c* \$ D4 g1 w7 d
age
( K4 u* g0 Q$ B' S. B wealth % Y: B( }; x9 F$ C% H6 ]# Z4 S8 q
life-expectancy
8 u8 ^3 B8 @# m8 D$ s' s metabolism - @& e7 q% b7 X: T
vision
4 _0 u! e( L7 h6 r: C/ z) w3 E inherited
: `! w5 N( e+ ?# I% ~]/ B" ]4 p4 g- d+ o( R3 V
7 f. [* O9 I- J5 n! @( X& Y/ W3 B4 G( V( A. j! P [( X
to setup4 k# ~0 x. G9 G& ^5 ^# |! n I, M9 k- K* `
ca- p: }% e7 ]. |' z* D
set max-grain 50& {* o- ?7 ~8 ?7 E
setup-patches
/ l2 L# X; v' p7 w0 `2 h setup-turtles
6 v8 K4 s; |% X% [% E setup-plots
$ Y7 v) ~6 R# w3 a0 Z& h3 Q4 q update-plots [& x. J9 ~+ @4 U; k
end
+ Z0 F+ N- ~& C8 ?: Y5 q6 n! K6 Jto setup-patches8 Y3 j- Z- a4 _
ask patches5 @$ i" m u+ _" u) u
[ set max-grain-here 0
7 D! P) x2 c/ L1 B if (random-float 100.0) <= percent-best-land# J. ~( {6 v5 e5 l# N8 l# V
[ set max-grain-here max-grain0 E+ r# _" H9 d R/ I; ?1 ?+ u) `
set grain-here max-grain-here ] ]# ], y' |8 O2 F3 z
repeat 57 ]' ^& r' e# K6 Q* V
[ ask patches with [max-grain-here != 0]
|, W* d1 i1 p$ a1 \; B" |. E. i [ set grain-here max-grain-here ]
: {# v9 h6 W3 _1 x diffuse grain-here 0.5 ]- \6 m+ H% ]8 }
repeat 10) f1 v" ~ `$ G
[ diffuse grain-here 0.5] 9 j- Y! R$ V3 m3 L, F7 r
ask patches" n' m D6 P/ t$ Y6 ~
[ set grain-here floor grain-here
0 U9 V0 F0 N* c; _" e" Q* \+ p! u set max-grain-here grain-here
T0 y7 v& p& L" }4 u9 T2 h V recolor-patch ]
& c8 u+ L+ f% X6 d+ T- m! Gend
3 C2 k+ b2 d% r% h6 ^/ [to recolor-patch
) i0 Z. ~8 \1 R4 O) @( T8 s5 { set pcolor scale-color sky grain-here 0 max-grain0 `; \; ?8 b1 B0 H
end4 Q- w: o: N' ^" c: {" o1 a
to setup-turtles
; ^: B- c0 m+ [. ~- T S( Z" j, d2 C set-default-shape turtles "person"% T0 a2 F4 q' A
crt num-people7 R0 _* `/ u: p) {1 A
[ move-to one-of patches
! U- |' {9 Y5 G% Q5 m0 ~ set size 1.5 & K) b! r6 Z" g1 r4 L6 X/ i
set-initial-turtle-vars-age
: A7 E" L6 ]* H set-initial-turtle-vars-wealth
. b3 I. Q' h2 D6 h set age random life-expectancy ]& \7 U* z, x" C9 t e
recolor-turtles
8 B5 R1 ?9 V! a! S, d: vend
2 {+ ]" I' o) D3 s' A% x) u$ t9 A
to set-initial-turtle-vars-age1 F% m/ Z2 N, k. `1 K" Y
let max-wealth max [wealth] of turtles
% d4 F8 ]* H) l9 d) U9 { 4 F; }4 k- B8 t0 `. [8 e1 h, _: D$ v
ifelse (wealth <= max-wealth / 3)
, l0 ]+ ~/ _) f$ n2 A! S [ set color red
5 \% {) V5 g- Y9 C5 a set age 0
+ z5 b+ r# j7 ?' K9 {! J- e) G face one-of neighbors4 $ J, Y+ I _6 l
set life-expectancy life-expectancy-min +
: c1 |% o" d4 F6 v; `3 Y random life-expectancy-max
& t( e7 O7 V& @" Z, _1 a5 U set metabolism random 1 + metabolism-low( X% T, r; @( y* J. F% x9 J" s& s
set wealth metabolism + random 302 b, `# I; L; _7 d; s, k
set vision 1 + random max-vision
( n8 p: J4 r# O$ q set wealth wealth + Wealth-inherited-low ]- Q9 v8 `/ R$ j& m" }3 z c" `4 A
[ ifelse (wealth <= (max-wealth * 2 / 3))
; o/ L; y1 j7 G# p3 I [ set color yellow
- e, v. v7 O" j9 T' c% t set age 0 t. E, p. i R2 R' o
face one-of neighbors4
( J: Z' Z( F; a. D/ l. R set life-expectancy life-expectancy-min +% \3 e3 _8 n7 ^( A6 j' g
random life-expectancy-max + 1
9 I4 v' D& a# [ s8 z set metabolism 1 + random metabolism-mid$ R$ Z% V4 j# Q. ^1 z" i2 o
set wealth metabolism + random 30
+ P3 b* i6 W. E% o; c0 q+ o. ~: n6 o M set vision 3 + random max-vision. }; `2 e% e7 }1 }8 c: n
set wealth wealth + Wealth-inherited-mid], o& X [. T7 @: t! Y
[ set color green 8 o8 c! E/ Z& ]* X% @
set age 0
9 `& b$ {+ j% Z. \4 u4 \ face one-of neighbors4 7 c) O" k( Q( [3 K2 @8 l
set life-expectancy life-expectancy-min +
& o+ D$ t" H8 \# ? random life-expectancy-max + 2, y8 p; S1 }8 E6 ?
set metabolism 2 + random metabolism-up3 Y, H/ H8 B+ q X( N- Z
set wealth metabolism + random 30: R. G8 j$ W7 B1 Q1 h. j4 O
set vision 3 + random max-vision6 b( S! M v2 }! p7 `( |3 e
set wealth wealth + Wealth-inherited-up ] ]
- g( V8 C; d) I
; K+ z, v0 H8 nend
. `4 S. L7 w' `9 }) nto set-initial-turtle-vars-wealth
2 o* H0 V+ ]. B/ A2 s% D let max-wealth max [wealth] of turtles6 g1 E; y* d' b
set age 0
' I+ S+ F* P# l4 x, z4 W: @. `5 |# Z face one-of neighbors4
& e9 _1 ^: S7 d" x A7 @ set life-expectancy life-expectancy-min ++ @. ?$ |" E" y% E9 ]
random life-expectancy-max ! ? ^" Z: a' b3 j2 ~& R& u# E
set metabolism 1 + random metabolism-up
7 C: p+ j9 p' r) R& @6 ]3 n set wealth metabolism + random 30) h: i% K. ?: I: Z- ]1 }
set vision 1 + random max-vision
* u b/ y* Y2 [0 ]/ L4 M Lend3 J9 {5 Z T, H6 T
to redistribution$ d2 i9 t" `# e
let max-wealth max [wealth] of turtles/ l. L: [0 Y3 e8 M9 [
let min-wealth min [wealth] of turtles
1 R5 x! ~, ~( c3 n. I! Q: p( xif (wealth <= max-wealth / 3), e+ j1 M2 e% a5 x! D8 g3 k( F7 @
[set wealth wealth + Low-income-protection ]" P/ }# X* N9 u) Z: c
end* C X! A% {2 g6 F
6 x8 X, u" R9 w8 m0 O$ t
to recolor-turtles0 {! {3 R+ p+ d; M
let max-wealth max [wealth] of turtles7 e% ?# t" Q/ {; R( W
ask turtles
, H* g* c+ [. F: s' D% o [ ifelse (wealth <= max-wealth / 3)
5 [# A0 ~) S# O) P4 ^ [ set color red ]4 [0 \9 v5 t: G( D2 Y
[ ifelse (wealth <= (max-wealth * 2 / 3))
7 {0 O' T4 W# T: \8 @0 ^# D [ set color yellow ]. z" Z9 x# Y& n, j. X4 r
[ set color green ] ] ]6 ]' B& W8 m: [0 A/ q# c8 j
ask turtles [ifelse show-wealth?
& Z; i; O; D3 d# E3 d# C [ set label wealth ]' F* w+ t% u# U- q. u- V2 G$ p
[ set label "" ]]( [! M/ {6 w5 N) w& }$ I, w; t1 o
end
" ^. z8 k$ i. x
8 @( `% A: c* H. ?to go
: c3 a( |' F9 X- F- { ask turtles( z& `/ X) F7 Q& ~6 g5 L8 r6 s
[ turn-towards-grain ]
: T5 T. I4 Z: ?, ?9 v" G8 P3 d2 l harvest2 f6 N! [/ q' s6 ~' `9 y
ask turtles( G7 R/ }' \( m3 M/ j) D" f
[ move-eat-age-die ]% w" j) @, l+ m
recolor-turtles
" t, v/ L. r5 S" c9 l+ k- T. K* M if ticks mod grain-growth-interval = 0; `6 U. I7 {0 }& C/ P W3 K: x2 h
[ ask patches [ grow-grain ] ]
' s1 ?' a( s1 z% F/ {
& X" F8 C( H1 T4 _/ ^ if ticks mod 11 = 0
- B) H4 `4 U) s: i' r [ask turtles/ T9 G% U) a. X/ H8 x, m9 A+ N
[ redistribution ]]' f1 F" u, x9 T. F
if ticks mod 5 = 0
: \& v' Y7 m. C2 e$ T9 C3 P [ask turtles# O/ z5 u% C+ L, T+ k
[ visions ]]! l2 h* }2 w- `% D; T& Y" M8 W* ]
tick2 H3 j7 E$ M1 r5 h6 g2 B
update-plots
: a; u- A a; g" R. wend
/ F% O5 n' ~ S. ]to visions! {1 j W3 o. o9 N% z
set vision vision + 1 ; M# c# q! C% d$ [
end7 K. I! q$ G B& O3 v& Q3 ], R
& ]* g$ l0 d" c, G
( h- Q$ c: }4 u
' ^. D7 L! G8 A) o3 f' Cto turn-towards-grain
/ Y& q. L/ O8 s- v. Z5 C7 ] set heading 0. d8 U7 X/ W+ P8 f6 ?$ `6 i
let best-direction 07 s j- q; v# S, ?5 T
let best-amount grain-ahead- r' L. I& v9 K6 D
set heading 903 @: N- v* Z9 |5 Z" B: K
if (grain-ahead > best-amount)1 M, P" y- v* n1 ?% _
[ set best-direction 90
- p" a( P M2 M, V set best-amount grain-ahead ]6 k) B! j" N$ I7 p1 a
set heading 180" z& `* }7 Y" x R' h( Y% m
if (grain-ahead > best-amount)
: I2 I6 c3 o7 C, Q [ set best-direction 180# N* v7 j$ f8 E2 P3 q9 [ F0 L; ?
set best-amount grain-ahead ]5 f. O# J0 R5 g& Q1 n& j0 x
set heading 270
7 @: z; g+ H1 W; |2 z if (grain-ahead > best-amount)
' p: q, u- ^5 w$ b) a [ set best-direction 270 D7 z; k% n5 i- ^# `6 y |
set best-amount grain-ahead ]9 \. U4 S! m9 I+ r6 Z) \* s
set heading best-direction
3 M4 L* I$ c( E2 G/ U+ bend. y. _- G' b- C) o; G, @* [ `
5 e& a! F8 I1 g: ? d4 d# x: r
% Y' `) j8 u. v* I& g
to-report grain-ahead 3 m x6 ^, W. w% K% ^; O1 R Q
let total 0
6 i4 K, p2 H9 q' r5 U: T* b let how-far 1+ l3 s2 X( k/ L' z) G1 X/ \/ }
repeat vision
( v/ S3 X: t% t* Y4 A( E- K( _ I [ set total total + [grain-here] of patch-ahead how-far) m( D7 ?! I1 p/ q, ?' n: z
set how-far how-far + 1 ]( z, w& i: ~, @4 S/ O$ e
report total6 }$ I9 ~1 l3 _6 j+ v
end( `; P1 |$ }5 y5 U/ g1 K
3 a, ], }- B4 R
to grow-grain 1 Q5 ~# B: v; C
if (grain-here < max-grain-here)
0 {7 v2 R' d5 S2 K( U [ set grain-here grain-here + num-grain-grown' b) t# R4 W; e- L; L! g: b' {. f
if (grain-here > max-grain-here) 8 S2 K I$ {( Q% n9 u. Y
[ set grain-here max-grain-here ]
: ]7 v; X4 ?+ C recolor-patch ]
. ]/ q" |! J# `; B8 V5 Yend/ n% A: w! Y, @1 X! j" ~2 p
to harvest0 G; c; p. @: a8 d' S- ~# V
ask turtles: D0 N0 g- v& o; ^4 r
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
5 v+ g- Q- |! x ask turtles0 T) `+ x# D" E" M* W. y9 l
[ set grain-here 0
( _3 e$ Q" I% }7 | recolor-patch ]
% |7 U3 `" L' v) r) @( r8 [2 n# W
1 c7 @/ c- H- Z# g1 a0 _* G1 Zend$ ~0 J' V! `. Q/ k
5 E- w: j l* N( ]9 F! I
to move-eat-age-die
( B3 c | N- n8 ~ fd 12 Q+ X7 r- |( L& m% q$ H* H6 b
set wealth (wealth - metabolism)% O$ p' j0 y7 t9 Y" x0 h
set age (age + 1)
; G5 O! U" D$ N: x9 l" G if (age >= life-expectancy)" b- r+ D8 Q* q
[ set-initial-turtle-vars-age ]% h) _6 q8 s( S! v0 s
if (wealth < 0); T$ I4 O1 }, i' L+ L, f9 M; ?
[ set-initial-turtle-vars-wealth ]' g' ^# b+ e" [+ T6 z* _
, G: }) C6 o+ V7 l+ k) N
end! \7 ?3 u0 G. a) N5 `9 t" M% K+ m
8 t8 H% v0 i* y+ C" ~8 M! }: b4 `
0 ]& l5 Q& J& s# m
to setup-plots9 Y1 L" L5 n3 C+ E& m0 n
set-current-plot "Class Plot"
7 j# T( V. t: M! j# Z set-plot-y-range 0 num-people: {/ h* j, }! {4 ?* n
set-current-plot "Class Histogram"! a9 W, E% I0 J; I4 j# C
set-plot-y-range 0 num-people
4 U9 ^4 Q7 ]7 Z: b. Dend q: O1 }; e/ ^4 C& {
Y9 Z$ V1 {; o
to update-plots `7 e' }9 h# }. i
update-class-plot/ Y, \. J0 G3 u( y# d; P N4 x5 u
update-class-histogram
& g+ W; _' f, h* | update-lorenz-and-gini-plots, D; S! t! E! e: o1 @) u
end
8 K$ c8 `& [( k- o" Y1 c8 k8 O
6 O# }) W# n: _4 D$ p2 Wto update-class-plot
1 J7 s3 O1 L7 | V8 P4 N5 |1 r set-current-plot "Class Plot". m1 T$ w9 z X5 F- M. P
set-current-plot-pen "low"# R, m$ S+ W1 K1 M9 Y
plot count turtles with [color = red]
7 d& j6 I, ]; y/ F6 E set-current-plot-pen "mid"
! i1 \' A) [2 I+ I$ N4 o plot count turtles with [color = yellow]: w) i. Q6 }9 |
set-current-plot-pen "up"
$ l) @7 Z$ i- M/ l% y1 f plot count turtles with [color = green]
* x$ s7 e, i5 s, I$ J. |+ k4 Y1 Pend
' f( y# p/ I1 `$ k) a3 y1 u2 |! F' A
to update-class-histogram
6 R6 s* ?' g& V0 K" j set-current-plot "Class Histogram"1 H3 ^( t* S6 g' {9 F' n' Z
plot-pen-reset4 ?8 x% D1 s! E7 G0 Z5 t
set-plot-pen-color red7 d9 }4 H4 a$ m3 E- I
plot count turtles with [color = red]
1 U$ n, M" N0 s- i4 R5 {6 w set-plot-pen-color yellow% e" ]$ Q7 K! o- j9 M+ K$ a
plot count turtles with [color = yellow]0 T) l& w) j1 k t! S( c; e
set-plot-pen-color green
( q p. b$ ~* a' y3 w8 u$ p plot count turtles with [color = green]3 T9 @& K( u4 C' m
end- |7 H' g- Z. i/ \. V, J
to update-lorenz-and-gini-plots h1 \: F% P: a, ]2 C3 U; w: j
set-current-plot "Lorenz Curve"
/ e; r- u! P, {9 g4 l* }% H clear-plot
; c2 r/ `5 g% s, d, [; f3 C. R" h9 h0 O' s, s: ~ A
set-current-plot-pen "equal"* ?* D) m( l/ G5 K+ K# G! I/ ^
plot 0
4 T- t' W: W8 v) g. B' {2 @ plot 1007 L% \' e$ S/ _8 a0 X3 p) P
5 p/ V2 k# N) g! C( k4 w set-current-plot-pen "lorenz"* q2 h) T' {- l3 a
set-plot-pen-interval 100 / num-people
3 f3 y2 i5 ^. m2 |4 S: w) h plot 0% @9 [. l% l$ d$ K7 M4 J. S) T
+ @% v* h$ T8 d) x/ }
let sorted-wealths sort [wealth] of turtles
5 ~4 Q7 v( L" M let total-wealth sum sorted-wealths1 Q$ @2 f6 P& F9 P1 H
let wealth-sum-so-far 0
: e3 ]3 r3 ?7 r let index 0
% y2 o* {7 Q- c6 b1 u: J- F. I let gini-index-reserve 0
( A# E9 g8 N2 k( N, V( G* h6 @# Z3 K2 D: V& @: p
repeat num-people [5 y7 L9 H/ b# |. Q7 z% ^* Q" p7 ?1 L
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
) U, [% Y/ |- ]; z# e: x5 S8 S plot (wealth-sum-so-far / total-wealth) * 100
$ _+ v$ S: x8 y3 @( Y set index (index + 1)
1 @7 F0 |- |' D7 F! [* ?# V set gini-index-reserve
0 m1 f. u& e- D+ x gini-index-reserve +) n2 K3 _. f* @6 y' ]- k
(index / num-people) -
7 x5 Q( l2 z1 y, E (wealth-sum-so-far / total-wealth)
( }3 n/ ?1 p( F5 v* P: J; v G ]% r' Y' a3 m% |- u
" G& y6 l. ^+ C8 }# y
set-current-plot "Gini-Index v. Time"
0 S" [- C' ]; h' W7 G' d plot (gini-index-reserve / num-people) / area-of-equality-triangle
* h! g, f/ s# X/ m- {; B( {" jend
7 Y p: N5 e& V! A2 D2 b, Oto-report area-of-equality-triangle
9 Q# o" G: [, {; f0 E' ^2 n4 T, _7 T4 q8 F report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
8 O+ w4 P% h6 O8 b9 M; l1 [end |