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8 I+ T+ n. A- u& m7 R P
globals
/ _" b) a' d3 `9 C M7 b2 K[, Z( g2 A# p6 ?; T& n8 q5 Z
max-grain + o( ?1 i$ \5 T1 x" H5 n+ i
. B, L# S9 h$ S4 r. E]% I- Q R3 n+ k1 M2 O4 a( n# R
; ?9 b4 I7 ~' \0 fpatches-own
" K/ L/ L i) Q* t: _! _3 y[4 }& O# f$ K! ^% B; \
grain-here ; M _, f! y2 a1 B1 Z# S
max-grain-here
" z3 s# ?4 y9 a]/ z# U$ Q8 o- ]! T" e
' r' o; i. h1 ^2 t0 C7 L! c, aturtles-own6 L: O! {) j8 A
[, P7 L) Y6 U4 u: K+ |8 X
age
6 Y& B# ^4 v. K/ b% }) s wealth ! N; g- U6 }/ U5 `
life-expectancy
4 ` @. k- H7 U% i9 n( t metabolism
9 b/ x, M8 x5 Z* A; a vision' n* z4 w4 H! T* b4 q8 {7 Y2 q0 A
inherited
* u" u; {$ |4 K. k% ~; C]# ~& q7 _1 S. m: h
3 ~) o7 N* F# q- U
4 Z4 S' c. S2 y$ ?( e: Eto setup
9 B: q1 u5 K6 o* _ ca
0 W: J( Q, _) R4 a6 ~7 ^ set max-grain 50
; j7 X- S8 v& G0 w9 {+ @ setup-patches
2 d+ _7 Z2 A. W7 Z- N" b) f setup-turtles; ~; E4 n, Q( Q
setup-plots8 T4 ~( K, n$ ]3 A5 [* O* k
update-plots
7 V. I5 u2 b) Z# c, H jend1 U! e4 i6 A' R+ w
to setup-patches1 [1 V* S2 J* d
ask patches& A% E% E# t4 Y2 n O
[ set max-grain-here 0( @( B# s4 J, c& S* F" F" Y4 ^1 w
if (random-float 100.0) <= percent-best-land6 n% `; B. `/ p) @, j
[ set max-grain-here max-grain
7 [" R/ m6 j: D" G# z set grain-here max-grain-here ] ], w8 T/ W. `/ r
repeat 5* v8 w4 ]4 x6 P7 B$ x6 m
[ ask patches with [max-grain-here != 0]3 Q" F" C8 J' f$ a
[ set grain-here max-grain-here ]& |! i$ X- X4 I; X
diffuse grain-here 0.5 ]
& v: N+ t5 V5 H9 y repeat 100 B: K0 [( }# C; C" l
[ diffuse grain-here 0.5] + n# l# d8 f" b/ N
ask patches4 j$ S) `1 [( ~( s$ i
[ set grain-here floor grain-here ) V! T1 o7 o& o* Z4 @
set max-grain-here grain-here
% ]; ~7 l0 u6 ], H) L% ? recolor-patch ]
% E" |1 Q; K) X6 ?end7 J4 r3 m% R3 @9 b/ m5 x
to recolor-patch - w& p# A6 n1 x, a# M! S' a! x: a( c5 |: G& J
set pcolor scale-color sky grain-here 0 max-grain
$ Q4 a6 Y P% u1 gend
0 `! e3 k" r0 E; [* D) M( Ato setup-turtles
$ n W2 s3 R( t% ?$ L* \7 O3 E- ^ set-default-shape turtles "person"
m. G6 B$ m z8 u. f5 G8 d crt num-people: H$ ^3 G0 O1 x7 G
[ move-to one-of patches ! t' `0 n7 }/ f4 K/ S! D* t
set size 1.5 . y; ~5 h6 g# Z' J- @9 |/ u
set-initial-turtle-vars-age
/ ] Q5 |! M0 R" B, R3 q8 K; o set-initial-turtle-vars-wealth
5 G2 x4 h0 _; `8 k" k& b( I set age random life-expectancy ]
! K. m. ]( S' D recolor-turtles
9 l) t" x! b4 k. [1 {9 Vend i! Z" U4 I3 S7 l' m4 d( a- |
, j/ T5 o; D: D" S: R5 s4 \4 J: V6 L2 T
to set-initial-turtle-vars-age
2 j+ f2 F3 b |: F5 D+ G let max-wealth max [wealth] of turtles
$ d4 t, C2 G6 [: L# a
( L1 x: q5 d- v& }! E' i; m/ k9 V ifelse (wealth <= max-wealth / 3)
) k0 k6 u. S5 G6 X2 Y* z [ set color red
% r; @9 v- d" d set age 0
: h9 n' [! r2 v p+ e8 Y face one-of neighbors4
7 P5 G- p- V3 Y, n" M6 `$ { v set life-expectancy life-expectancy-min +
* z" e" ]# f% M/ {2 a2 \ random life-expectancy-max
3 `5 |1 @8 \. C8 p; v; g: y set metabolism random 1 + metabolism-low2 D$ N! L( ?3 P8 k* f
set wealth metabolism + random 30
9 c+ C% Q p, @+ k+ F6 s4 Y set vision 1 + random max-vision! j8 H' C3 R5 a8 U" j, _
set wealth wealth + Wealth-inherited-low ]
' R$ c2 R% }4 D' j8 P: H- ~ [ ifelse (wealth <= (max-wealth * 2 / 3))0 c" K9 Q; t! V! T$ h7 I; p
[ set color yellow
t9 k1 S2 J6 e0 n. L& v9 i* X set age 0
! A/ q: b+ R9 h" I) W3 Y face one-of neighbors4 / R2 T( J7 ]# F# o/ H7 c
set life-expectancy life-expectancy-min +. K1 o: S9 I6 Z1 M7 N8 ^, h9 D
random life-expectancy-max + 1
% J( B! E; {& f. K set metabolism 1 + random metabolism-mid
2 k0 J1 O0 E- T1 Z0 ~3 t8 T2 c set wealth metabolism + random 30
6 n0 b& r2 u' r3 g% L/ P( g% ~! j set vision 3 + random max-vision& p9 C, q8 S, b4 g) }
set wealth wealth + Wealth-inherited-mid]
9 C- D( C) O+ R* Y+ @9 P [ set color green 3 i; ]* {7 P6 m: m) @$ C
set age 0
. c5 r1 g9 f& k Y- q# j/ X face one-of neighbors4 ) H" O7 j! B8 D0 r" f
set life-expectancy life-expectancy-min +8 x. }$ S. D8 v) n
random life-expectancy-max + 2
% l$ w; J9 ]# L+ Y$ G set metabolism 2 + random metabolism-up) W9 S: h3 E( J2 x# q
set wealth metabolism + random 30
& ^% i! \; V* W4 J& t1 B: `, P set vision 3 + random max-vision8 [1 |1 i0 V7 L7 c( \7 Z+ c* m
set wealth wealth + Wealth-inherited-up ] ]
! G' Q8 r' J c1 F8 L' L/ G
/ F" X& h: n6 ~end
' R" ]/ f" x! @' ?" K T4 nto set-initial-turtle-vars-wealth
4 L. q( F. }4 Z9 e5 ]. p let max-wealth max [wealth] of turtles2 `! h) k' U6 P; r/ N7 Q# l! y7 s
set age 0" C& Y, G2 B& i: G( S
face one-of neighbors4 [" w: Z2 x0 c# I0 I7 F8 B" L
set life-expectancy life-expectancy-min +0 ~, [3 [; _1 K
random life-expectancy-max
% R/ S9 `* U$ g4 e& o) Z set metabolism 1 + random metabolism-up
/ Y. N) y5 [" i; U+ r0 N0 ^ set wealth metabolism + random 30+ o& ] {2 ^* I$ M- f( P& q/ B
set vision 1 + random max-vision
3 F7 c5 r- N& e1 Z" r) Vend
* k+ K3 `7 @0 O$ h" ~0 `7 ^to redistribution3 B) z; g" P) N7 T; V" R4 P
let max-wealth max [wealth] of turtles
5 K3 a% o4 ^7 H0 K$ k7 a% _7 X8 n& mlet min-wealth min [wealth] of turtles
* s+ [: E ~+ j3 z* z' Sif (wealth <= max-wealth / 3)7 C3 a8 A% P( x& \/ ]/ G+ \
[set wealth wealth + Low-income-protection ]2 {' N0 k+ \, e9 H+ g
end. [+ I1 W, ?2 D) w
& H7 B: d" T8 D8 ?: F$ ]+ s; t$ X% Yto recolor-turtles7 P) Q* f+ [/ E- W/ r
let max-wealth max [wealth] of turtles
9 r5 W( F/ p- w! d m5 L ask turtles/ c4 w& J, [7 ~) e, X9 n& q
[ ifelse (wealth <= max-wealth / 3)7 E7 L) p, B" N/ p
[ set color red ]
- @$ v$ y/ `1 `! g, a [ ifelse (wealth <= (max-wealth * 2 / 3))
# |" M* |; ]+ Y# X* p7 J- ? [ set color yellow ]; E. y7 t- g/ r+ c8 H
[ set color green ] ] ]
' `- T7 X8 U: H2 G2 H* d ask turtles [ifelse show-wealth?
* W' W( P3 K | E" d& Z" i [ set label wealth ]$ o/ H( J1 m# c5 `
[ set label "" ]]6 S1 |- L) Z9 F
end
5 l9 L0 }+ T1 G; T
1 C( b0 H6 @1 F; N) t! ]1 s$ ~to go
1 ?+ |/ @7 V# L% |: r: l6 |! D ask turtles+ J3 z' F, w2 p& R' ^
[ turn-towards-grain ]
. U- w6 W: c5 f& ^3 P& f harvest
4 Y, ^6 h2 v8 E3 @: q ask turtles) N3 @" ~9 ^( c- I: T! R2 U
[ move-eat-age-die ]* E( e8 h8 V& f( F/ f. f
recolor-turtles/ x2 i* L2 f0 `, R
if ticks mod grain-growth-interval = 0
+ f0 ^/ b) Q2 q' j( { [ ask patches [ grow-grain ] ]5 T$ u/ b0 J2 n: }7 H e
% ^2 L; S7 o: y+ m$ W3 }
if ticks mod 11 = 0! G( c4 Z0 O- k+ z
[ask turtles3 Q m s) b, H7 e, Q. s* U8 ]
[ redistribution ]]
" }( L; _4 K( r W* C if ticks mod 5 = 0
& S* g7 z8 N& T: g [ask turtles' C/ ^( K" U$ f, V# G
[ visions ]]& ?' R! {. ` j) C: b. J7 N, T
tick+ d# v! ?6 g% {8 j
update-plots
. T& N' d' `: H( D1 nend! [- h0 X" h- K) ^' ? `' J8 w P
to visions9 l# z; `; ]' t% q- i
set vision vision + 1
' L; _* S2 p$ bend B# {2 r8 k9 e; P
- E3 x) K5 N7 q5 O+ r! K' T% S) p3 |
- G4 w! J/ A& L% H
s/ p: U3 _3 t( G
to turn-towards-grain ( O- c+ B! i: @8 A( ?$ _. N
set heading 0( c/ d* s) b) E( L9 U
let best-direction 0% \* T/ V5 w( [2 d/ y
let best-amount grain-ahead
* v* N" h2 H6 x3 H y, F5 U set heading 90: o6 O0 K' s: y
if (grain-ahead > best-amount)6 }. _( ]# [7 P2 S
[ set best-direction 90
9 S! o( c+ n- j2 z- o" o7 N6 g set best-amount grain-ahead ], d2 _0 H/ s" o3 L; M+ q& \/ E
set heading 180% Q [9 l! |# e
if (grain-ahead > best-amount)
. J9 x+ x) S! A [ set best-direction 180$ P: ]" L, L. Z" P5 y' C( X
set best-amount grain-ahead ]
& w' U1 d) a$ f% k- F set heading 270
+ e/ D" a/ I/ J- k O0 r' c if (grain-ahead > best-amount)+ C2 X( ?- G! ]: B+ E) k
[ set best-direction 2707 ~* c) d+ v4 |, `: ^
set best-amount grain-ahead ]
) e U. V4 D J set heading best-direction
+ h- k! r& O1 W, @end1 Y3 s6 {' {2 d9 d& I+ z$ L
4 ?3 N/ a" q3 O
- l9 I" [) {/ P1 M5 qto-report grain-ahead
0 L( U0 K: N9 K. v- j' M let total 0. h& d a$ U; \& H) P
let how-far 1
3 m9 P% x$ C* ^$ z+ ^/ s0 b Y ?3 O repeat vision" F5 k. \* @# n7 g4 Y: i# E+ O9 {; U
[ set total total + [grain-here] of patch-ahead how-far
& W" R! b/ V8 w- a) J* J, h set how-far how-far + 1 ]; G. }1 z" Y; s, D; C' H, V# |
report total
& |% E+ F# e+ y" T2 e1 zend6 \" g/ c# J4 M* H `
# a% ?/ I- A+ Kto grow-grain
. h' N6 P5 P) W' N% Z- X2 a6 b if (grain-here < max-grain-here)- L1 E( B0 [1 [+ ]
[ set grain-here grain-here + num-grain-grown
; A$ w* f% f0 M; ]& X5 b if (grain-here > max-grain-here)
$ h, I" F) ~" h3 H2 k+ [ [ set grain-here max-grain-here ]
. I% O2 R y. }- x recolor-patch ]/ y0 k5 V7 D6 E. q$ s
end4 l" B* e: {3 D( Z
to harvest
9 X: ~6 D) R: R ask turtles
$ ~: G2 u* S8 R/ Y; o+ {, H [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
. l8 q k; u. L- k ask turtles
6 {6 b& A% Z8 S d [ set grain-here 0
# {7 {4 F; h1 t8 h7 F8 a recolor-patch ]: i- _5 _. n2 c" K5 {6 }) d
; l2 e& {3 @( ?3 ?' I5 V
end
$ t/ C/ ]# P) x _6 Q5 I1 k1 W2 Y: t: I0 }/ e
to move-eat-age-die * m/ m( \6 H' Y* H7 F$ y7 b. G# l5 W
fd 11 e6 t) `( f; u* F
set wealth (wealth - metabolism)( h! ~8 n# Y6 ^; N/ T7 k+ @
set age (age + 1); e0 a8 T7 q y6 M( u) r
if (age >= life-expectancy)
# l% [) S4 R2 M$ U0 m [ set-initial-turtle-vars-age ]; i1 ]+ D: A) K8 f
if (wealth < 0)
& v4 L: N+ n) x1 ]6 T0 } [ set-initial-turtle-vars-wealth ]
# o+ R/ Y8 M+ Q" K 9 ~/ Z4 r0 g( m8 n1 U9 a5 X
end
( D5 E$ r. E2 S$ F1 B0 B6 R
* Q: L3 B0 R+ l: Q* K# t8 Y: `5 G* E7 I& ]3 Q) o9 H: L
to setup-plots. ~% F- o/ e# }% l5 ~
set-current-plot "Class Plot"
: i* d& D2 h- I0 r, i set-plot-y-range 0 num-people/ h j* A, \0 v6 L
set-current-plot "Class Histogram"
, L, |7 ^. w* j* l$ n; k' T" Z1 j set-plot-y-range 0 num-people! K! [9 N2 J$ |2 A( N5 V
end- F4 u3 }6 w) @) a# P9 U5 ]. z0 P
" b/ \/ r% n/ c( L2 eto update-plots7 O" T _7 o" S* Q$ d1 v+ [
update-class-plot* ^3 a2 J3 q# x: M# t( a( W+ t
update-class-histogram
& N$ [' M' c4 D6 e update-lorenz-and-gini-plots% k; N$ L$ Y6 l6 l4 t& }& X/ E
end
+ t$ h: M( d4 l2 ]0 y7 Y# Z" Z* w! C( v
to update-class-plot
8 T7 |. s! @$ W6 u$ ]* {0 p6 I& q* g set-current-plot "Class Plot" ~/ J" ]9 A0 J2 Q: E
set-current-plot-pen "low", g+ ?* O3 j* k' Y) y" Y V
plot count turtles with [color = red]. I' P$ u% Q& p+ @" J O2 f
set-current-plot-pen "mid": n3 Q) A6 ]! t9 q8 |9 M, X
plot count turtles with [color = yellow]% r& k' G+ n2 M0 B& h! A' B
set-current-plot-pen "up"
% x5 m% ^" f1 a2 f3 T plot count turtles with [color = green]- o, s. a! t$ m; J8 n: U
end; P0 z. `' w0 g
. M# w+ {7 U h- `2 jto update-class-histogram- V s1 ?! E! t/ m+ `/ j0 q. m% P6 G! h
set-current-plot "Class Histogram"
# g! A4 x- e4 F+ f# ~; m( O; a plot-pen-reset
7 j- Y1 D0 A( x set-plot-pen-color red" U8 l* C) D% }. p) Q( f' _8 o0 s
plot count turtles with [color = red]' [) _, z) b( \9 F& \2 k- _/ ?0 `
set-plot-pen-color yellow
+ b1 e) m2 f. w# i, J a9 W a T plot count turtles with [color = yellow]; a0 L" v- C9 }* w' f" i3 r1 t
set-plot-pen-color green
4 W* U# q: H# g. f# F; V: @/ U plot count turtles with [color = green]
' J9 X& e2 V) b" Lend
3 r2 P$ g/ n0 L0 _1 v+ H5 C& yto update-lorenz-and-gini-plots; e* R* h* [" w' N& r0 e* o2 v* L
set-current-plot "Lorenz Curve"; k, k; n2 y+ U* v7 `5 T
clear-plot) ?1 A% N# Z* M2 K2 n
8 R+ S0 B) Y+ J- [
set-current-plot-pen "equal"
; v9 m2 Y; h8 e& w3 j. b ^ plot 0
4 y5 ?: w1 p/ k plot 100% c7 P& I/ g6 v
5 @" D* e/ s( F8 D set-current-plot-pen "lorenz"' d- @& f+ f) P+ B. H
set-plot-pen-interval 100 / num-people7 C- A/ S8 b3 K; O9 w
plot 0/ n# s1 k# {- O) O3 g
$ h5 N3 o+ I9 ?0 S. ~* E, f let sorted-wealths sort [wealth] of turtles$ g1 B2 T/ A: o9 i
let total-wealth sum sorted-wealths$ r. d" P4 n2 n) Z% g0 Z
let wealth-sum-so-far 0
! G- S; t: c' d let index 0
3 F" |* ]9 W' e6 o+ o+ d0 B* B let gini-index-reserve 0
% \$ x3 s# m8 P X2 }; u! B# a* M O
repeat num-people [
" H! n& ], M- ^7 O: x# k% j set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
{$ {0 f' Y0 M6 ^9 ~, l plot (wealth-sum-so-far / total-wealth) * 100
8 O4 R5 w9 o" p/ }4 H+ e# ]+ {. ^( c8 S set index (index + 1)
6 q/ N+ ~8 N) X, m set gini-index-reserve6 c6 A3 I6 f& D# K# U4 R9 q. }
gini-index-reserve +- e+ R" J" \% ~4 J
(index / num-people) -) N3 K% Z7 w" O" R! P
(wealth-sum-so-far / total-wealth)
# E/ ]0 E( `9 O: \! |( g ]
, `! ~( k: {+ `! f1 V6 m4 G! I0 Z9 o0 ^( e4 [4 U
set-current-plot "Gini-Index v. Time"
, @4 {1 s9 \* Y c plot (gini-index-reserve / num-people) / area-of-equality-triangle. d# M* H( `: i/ W+ f+ T- q& ?% U
end
4 _1 Q; i1 p, Lto-report area-of-equality-triangle
% A: P$ Q1 f) u1 r2 J report (num-people * (num-people - 1) / 2) / (num-people ^ 2)0 o# f4 n9 `5 j5 d7 K; K
end |