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1 M, _( }/ M/ a' k M. P) |
globals: V% Z, g% T& z" f: y0 f
[
& n5 g4 S! L: M2 A0 A max-grain
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2 \# l# u' }% x7 R, {]
; ^5 a7 f/ ^2 Y4 ^3 `" E) M: y8 F* E# a& z0 `0 D
patches-own5 _6 s8 f7 e# ~0 e" c
[( D9 b& C1 b6 g5 Y" @0 w
grain-here
& T* ~5 A5 q' J* Z max-grain-here ; v/ b* O# T! d8 Z* b
]+ F+ C# |5 X o+ s. }
/ _" D( O) G, `7 z' D& _turtles-own! S- e% k! B+ b& [
[8 b) ~5 A2 f" j0 ~
age " j7 |2 S8 i/ Q8 h' l% J" k( Q
wealth 9 Y. l! S. q& D. P" V. n7 R
life-expectancy 4 Y) M0 }4 K& k* H, Q7 O8 a0 K9 P
metabolism & z$ R2 Q2 Y4 z: i# P% j0 z) l
vision
" {) l; @. V0 x% C2 U. I: S inherited + B; M1 v; o6 h+ B. x# }
]
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; {' P& Y. C# k- Y3 O! sto setup
q( \8 Q9 R! ]6 R9 [5 }6 k4 y- q ca' `3 m t7 g" _4 @2 K
set max-grain 50! `2 ~ e+ C/ _
setup-patches1 a' m3 ~6 G4 `: u S
setup-turtles
2 E8 h7 `" O$ X setup-plots
7 z2 q; H- ]. @0 O update-plots
6 y/ @5 }4 N! N$ ?( o9 Pend
2 s( E! {/ L7 Pto setup-patches& Q# U# `, T' X7 `: o. D" M
ask patches
4 L4 E% R# q% X# p [ set max-grain-here 0# t+ p5 |/ f* M, C/ l; t/ ^! k6 j
if (random-float 100.0) <= percent-best-land, Z. A' ^1 x& s9 E
[ set max-grain-here max-grain
* O9 p1 d5 m- ^. y" E. \, S set grain-here max-grain-here ] ]
' G8 o' D! l0 ~' m; f& g& \7 Q repeat 5. o. O8 ?6 `* k8 J Z/ @: ?
[ ask patches with [max-grain-here != 0]
% D; Z( Y) s& H) v [ set grain-here max-grain-here ]
8 x8 h, W5 U# o4 x diffuse grain-here 0.5 ]1 ]( L% \$ ]" S3 C
repeat 10- I- V! }: B* w" |9 r& e" r
[ diffuse grain-here 0.5] 6 A8 x, m/ _8 ~& z! m! `
ask patches5 j! l) R) w$ w) {# h: ^) \
[ set grain-here floor grain-here
6 y" L! Z$ }! B* G; r3 N% W set max-grain-here grain-here : O1 L2 U% K; a. A3 o
recolor-patch ]
% G/ c8 Q% g* C7 Oend4 h1 `. T; `" X9 T7 q
to recolor-patch 5 r2 Z( {) M; d( o! J
set pcolor scale-color sky grain-here 0 max-grain# ^* Y0 H! o1 G! {! P: P
end) l/ ~8 Y! ?8 ^, X5 [+ }
to setup-turtles, r6 T/ ?8 \* l4 z: V! `
set-default-shape turtles "person"
# E% x5 B/ U! ^. A# |1 \: g crt num-people
' Z0 c0 L- z" Y7 R8 L% ? [ move-to one-of patches 4 U1 C1 K% g' {- ]- M2 k9 B; O) [
set size 1.5
) l& d6 R& r4 r5 L* N) u- o8 H: v set-initial-turtle-vars-age
- |7 Q) G8 w) H/ i set-initial-turtle-vars-wealth
9 G, I. r7 V3 T( E+ r set age random life-expectancy ]
2 O8 n/ O- I' R: c recolor-turtles. z5 F+ `$ O- M3 I# f
end. a% d2 d+ i6 P* I
) @4 R- h N9 K0 @to set-initial-turtle-vars-age
. c1 e) J5 h4 @, {: X8 u* Q L' q4 C let max-wealth max [wealth] of turtles& `- q, J; V: \6 M
`. h; v1 j3 n; f ifelse (wealth <= max-wealth / 3). Z, \" x! Y5 b3 i, M3 g
[ set color red + N4 M* b0 I \: N6 P. J4 X! j- x
set age 0
2 v0 c9 p" J# s2 z) v# V4 W face one-of neighbors4 - W- n0 \9 i, [" [" r
set life-expectancy life-expectancy-min +
6 ?1 G3 R# A) E/ q: V. u random life-expectancy-max 8 r+ E r2 z- g4 J# K2 d
set metabolism random 1 + metabolism-low
6 d9 e! E( j# f' h6 x( ? set wealth metabolism + random 30
; _0 Z! I! w9 C set vision 1 + random max-vision
b/ S/ ]! T/ S$ P0 t& d& r. \ set wealth wealth + Wealth-inherited-low ]3 I2 {- T9 ]* Y. g; j1 M) w
[ ifelse (wealth <= (max-wealth * 2 / 3))
. X8 t, D8 ?" r. C [ set color yellow ' P, E" v1 {8 w# W5 E1 q
set age 0
# { v7 P& H1 g: G/ u) J4 i face one-of neighbors4
& i0 }# ?" ^# X1 s/ b0 A& i set life-expectancy life-expectancy-min +
7 i x$ D" z. e( a9 n5 u& E1 ` random life-expectancy-max + 1
/ j1 H. j( q9 n$ V4 Y3 ? set metabolism 1 + random metabolism-mid
$ {# L9 w, d% |. ]& z* s4 h set wealth metabolism + random 30
& [# p: R/ [$ [1 X set vision 3 + random max-vision
3 x7 ]3 X) C6 T. e5 ]- @ set wealth wealth + Wealth-inherited-mid]/ O+ X9 {# E2 {) r1 M, n) w. W4 X
[ set color green " p/ q5 A6 e5 i
set age 0
4 _8 i0 @8 h8 D0 z4 h8 q6 n face one-of neighbors4 , j" U3 j4 Z* P/ V
set life-expectancy life-expectancy-min +
3 i5 F3 p* v2 s random life-expectancy-max + 2
0 z+ B" T* o4 j* v, u! r8 D set metabolism 2 + random metabolism-up
1 c- {8 J( d+ `; b/ Q7 {' Z0 N set wealth metabolism + random 30
# x3 w7 ` K. [2 g, J set vision 3 + random max-vision% c y) ?! l: t
set wealth wealth + Wealth-inherited-up ] ] 9 e `- P+ G! m0 x( s* Q
. Q# `3 X7 R4 Aend+ m$ W& P9 k: u
to set-initial-turtle-vars-wealth& z4 ~* O4 B/ d2 { j- t4 R! m* u4 ^
let max-wealth max [wealth] of turtles
0 T1 p1 N5 ?# v- H7 M set age 0, {6 T$ J3 O) A
face one-of neighbors4
1 |1 h: h4 X$ R set life-expectancy life-expectancy-min +, y J. T* A9 X: ^1 h; Q* G) w
random life-expectancy-max / s2 \% J* C+ ?
set metabolism 1 + random metabolism-up# n8 O, r5 _. E6 v" z9 m
set wealth metabolism + random 309 F. u: p4 C/ n4 X8 R/ W
set vision 1 + random max-vision
3 s- D e' K# v; N v% Q6 p6 p$ hend
2 B8 {4 z5 z- a" O2 }to redistribution
, A- {1 Y/ C. `. [/ alet max-wealth max [wealth] of turtles
5 b& p3 {% v2 A& ~0 Q9 ~( D7 g5 N7 a/ Ylet min-wealth min [wealth] of turtles
+ O5 s7 r }5 e( S5 a& Zif (wealth <= max-wealth / 3)' z. p7 p% s' l; F
[set wealth wealth + Low-income-protection ]! }0 [5 O4 Y& D( H/ b
end
& m6 y% F( r* A2 i : a- R' P5 q% _' v, N: b) j7 X
to recolor-turtles
9 i5 z2 s/ y, [1 J, H let max-wealth max [wealth] of turtles
" o+ C) }; ]2 _7 W4 o g$ X ask turtles
7 ]/ P- }6 ~8 C& X$ D. i [ ifelse (wealth <= max-wealth / 3)
5 h8 W6 K7 g3 S/ q [ set color red ]
& ] T! n1 ^% h% ] [ ifelse (wealth <= (max-wealth * 2 / 3))/ R. b$ G7 O9 j4 d1 D4 Z& m
[ set color yellow ]4 X- u' k0 i& V( ^. A
[ set color green ] ] ]
! l3 a8 j' \& D2 q: b0 l' m ask turtles [ifelse show-wealth?
7 q; K0 Z% l/ l# w [ set label wealth ]
* l) U! z9 U- W, q6 o [ set label "" ]]
7 E% a. [" R$ eend
4 @' S, @2 ~% f" b2 j8 x5 O, d; y4 |) Z. v/ _% T+ T9 ~2 \- _
to go
$ w6 ~( q( U3 J ask turtles
5 z8 X( b1 S" W% } [ turn-towards-grain ]
: a# L3 c& b6 K$ {. I harvest) x( |' A. t( _- i
ask turtles
( O/ M ]7 H) F, k [ move-eat-age-die ]0 p+ m. p# X! N0 w
recolor-turtles9 g3 M$ O. \& s, C S
if ticks mod grain-growth-interval = 0& \0 Q% u/ s; Q0 P
[ ask patches [ grow-grain ] ]
0 N! ?# ]* r: @% @/ V! w4 W ' w0 a4 ]( P! I) l$ K8 w1 E0 K
if ticks mod 11 = 0
0 h. m/ E) I+ L$ i [ask turtles
* ?0 o% Y4 P3 M# S9 R% M [ redistribution ]]
5 z3 I6 G/ w" X- W1 r if ticks mod 5 = 0 @$ A( M2 w! ]4 V' s$ S
[ask turtles
2 p( [. b8 f* Z; k. a) l [ visions ]]
- d$ N) Y4 r& l tick
" J1 Y7 V I' ~( H3 f5 H3 o update-plots! z& L/ m# v+ p* Z: h5 ]
end! t, W$ l# `% s2 V- ^
to visions7 |: V+ x9 @; y- c8 Z( s
set vision vision + 1 ! X: C# y7 b' E- G3 b4 C2 w$ t7 O
end
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, e+ F3 y2 t* J
5 {& H/ m: T$ U$ f+ _
to turn-towards-grain
/ G g4 ]' r( A/ q/ j set heading 0
& i7 p0 ~/ J, F! _ let best-direction 0& n! P# d$ R, I, G
let best-amount grain-ahead
j' s& k1 v" t2 x0 _8 W) \ set heading 90! |* W. l6 a' y, _4 f5 y
if (grain-ahead > best-amount)+ T. R6 T! d( L; F6 J3 @6 E% l8 e' H
[ set best-direction 90! F2 D, [ N6 Z" Y# R6 ^2 i) g
set best-amount grain-ahead ]
) @( x* q3 h) I4 E" a' A set heading 1806 _( h2 v/ v" P, D
if (grain-ahead > best-amount). W, h7 g. t }/ K. w" i+ A. S
[ set best-direction 1803 K1 ^# g. z$ h( m( c
set best-amount grain-ahead ]
. \: j& a% E; @2 @ set heading 270
* P8 k" ]3 [5 U( c if (grain-ahead > best-amount) E: c2 C. T+ \4 ]; `9 n
[ set best-direction 270
' V* Q( {+ ~ B) ?! a- J$ y+ ~ set best-amount grain-ahead ]
5 s" q$ k6 t U' m$ r! \" t2 u set heading best-direction2 Z/ T1 g3 o1 V: v
end
3 ]3 x2 W# b( O6 H6 P) S: o. x @8 k" c4 n. H& N9 K8 D% G
* U+ g S c* G7 f* X# Sto-report grain-ahead
/ ?+ G% N0 j8 a# [7 ?, K" _ let total 0
: r p4 o+ J' ^ let how-far 1) Y9 F8 d5 D* \2 Y
repeat vision7 N( N0 F. J6 g2 `& Z
[ set total total + [grain-here] of patch-ahead how-far
- X; \( D# N* O& i) x) n% v set how-far how-far + 1 ]
$ W) k& {$ `. r# m& H report total5 {6 N1 o# e7 O8 j M
end3 s6 @; b) U, Z
: Q: N [" z8 z4 |4 [/ c" J9 T
to grow-grain ) M: Z& G x, ]6 q; Y# ~5 G) a/ V
if (grain-here < max-grain-here)
! c2 _- J& T8 h" i+ b8 i4 P# x" J [ set grain-here grain-here + num-grain-grown5 I9 q' ? j+ a+ ^" x' K
if (grain-here > max-grain-here)
$ [0 Y. c$ Z; A [ set grain-here max-grain-here ]1 q* v6 d8 \7 [# Q* b' f! H. b
recolor-patch ]3 F8 B2 i# H# v4 ~
end+ k8 x0 k& R. R# n$ S" K
to harvest/ W( B5 W* `6 H
ask turtles
9 v# q0 g) V" T7 R7 {. F [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
2 H$ R# U% S5 Z. L3 o3 y" q ask turtles
: t. z) P% ~ |0 u2 X [ set grain-here 0& C" y7 G, z) a0 t7 B6 {
recolor-patch ]
0 s7 ?. O3 V( G- f1 W9 F
& a6 D/ T2 w# z. k8 A" gend+ r+ g0 N. Y, T+ @' ~- r' G
. N" h5 D0 F' \. rto move-eat-age-die
; e; s1 ^* @0 y3 L3 V5 W fd 1
/ S$ H, s; @: o4 u' m5 ^ set wealth (wealth - metabolism)
7 L! L/ N1 T% R, g1 H: ?/ p5 v0 \* Q set age (age + 1)' }. j! a! d, Q4 ~% t; |% D
if (age >= life-expectancy)0 A; A* C& H _4 `
[ set-initial-turtle-vars-age ]
; R/ J5 W9 b+ \- F; q1 W" Y+ y if (wealth < 0)7 j4 I b3 D, [$ y- j
[ set-initial-turtle-vars-wealth ]
! |. @* U ?9 f) }$ s % o$ `' N* ?2 V& J3 @. M+ [- l; b
end" J9 c2 ~0 `& |% L
: i* `% O( R& D" y1 z3 `9 G) c& }$ X
$ Y0 a! d+ \$ s( d" _* z; {* Zto setup-plots% B* |5 q+ F3 F& O( e
set-current-plot "Class Plot". M* _% y C3 l- \6 [1 J( {
set-plot-y-range 0 num-people4 O$ I7 W' V, ^4 D
set-current-plot "Class Histogram"/ h1 l2 I5 t& H% X
set-plot-y-range 0 num-people
* E5 f; f. G& j8 Uend" S# H7 S- f( d8 D7 l6 F8 F
3 O8 l+ ~5 l* a* S- |
to update-plots6 \5 J6 y- d8 `+ i
update-class-plot) I, S4 J. Q' l: u0 Z
update-class-histogram
$ ^! i# g. C" K6 b l update-lorenz-and-gini-plots1 _9 n ] ^2 H3 a& p F
end
$ X2 `- o( e/ @+ Y0 {$ o( z Y. I }
to update-class-plot( ~$ P! @4 j* S
set-current-plot "Class Plot"
+ B9 S+ D( I4 X& f set-current-plot-pen "low"
& m2 z$ |$ p R! g plot count turtles with [color = red]
- H" I4 m$ Z u2 q1 F set-current-plot-pen "mid"
$ K, X$ q( t: v% O plot count turtles with [color = yellow]
f( F9 \5 }- ]& T. D% H set-current-plot-pen "up"2 n+ S' V _3 a/ j, _
plot count turtles with [color = green]0 D: e& e8 v& x8 F& X
end. ?' f \3 v6 D: q' N' g1 | s+ a
9 P4 M! Y$ x' b9 S" e1 Dto update-class-histogram
5 V2 X! l; k( S set-current-plot "Class Histogram"$ m8 r9 f9 S7 v/ E6 r/ T
plot-pen-reset
% h! S+ z5 a7 X) @( o4 r" f! p set-plot-pen-color red
& L1 E( Z2 j1 n& {! B c8 | plot count turtles with [color = red]* t/ A4 [7 P6 M: `9 O9 b# }
set-plot-pen-color yellow* d: s+ K1 K+ p# {; f7 C
plot count turtles with [color = yellow]
8 T P4 @0 Z6 h" j3 ^: G set-plot-pen-color green; e0 z7 ~: O _
plot count turtles with [color = green]
& X$ F" a5 u# b% h0 j' Nend1 l. u- [& U6 Q: Y
to update-lorenz-and-gini-plots
5 D$ h; |" Q K) A7 M set-current-plot "Lorenz Curve"" J0 I7 I- M$ t3 Q
clear-plot: b# l# L. m2 @! d" k$ m
" t1 L7 w4 _& y0 g" u2 r set-current-plot-pen "equal"* h9 D. |" g9 k! f& X
plot 0
- Z) k* ^9 F- M4 r& L+ D1 R' z$ Y& O' r plot 1006 ^4 t6 j0 e% K6 h$ f) p& h2 X
* }$ m0 m" ~& Z9 w
set-current-plot-pen "lorenz"- M8 ~5 G$ X; _) g4 |" S9 n9 F! \
set-plot-pen-interval 100 / num-people% ?5 A8 p" N1 ~, A. S1 f- T
plot 0/ x; j* R6 J" {! G3 u' r( t
5 m" [8 V" ]1 a$ n$ l let sorted-wealths sort [wealth] of turtles& e) B% F, M4 K
let total-wealth sum sorted-wealths/ [) [; }8 U1 o' a4 j
let wealth-sum-so-far 0" S6 W3 ?# _( }% f! l
let index 0
' _, \# x* ~$ Z& o& X; q let gini-index-reserve 0
# K; n# l: O( Q
) E7 M" ~6 x9 A7 m, T repeat num-people [5 |( o5 d8 `2 {' C
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths): B( ] B4 p' A Q( F
plot (wealth-sum-so-far / total-wealth) * 100. E: L9 \" r2 V6 Y$ d% `
set index (index + 1)
* l% X% z/ I/ G! S! k/ {0 X6 r8 l# B set gini-index-reserve
( V2 h9 c2 W5 G! D, W: ]: X: r gini-index-reserve +
5 ^, B4 b4 _- w# r$ M) o (index / num-people) -
' E: M2 T5 l2 M0 r (wealth-sum-so-far / total-wealth)
8 f! c3 O W; ?! ? ]
- @' u9 h+ B" ]+ q: n }2 u/ h
. m/ w& R9 h" c; L3 o set-current-plot "Gini-Index v. Time"8 a" u1 [, B0 ~7 R
plot (gini-index-reserve / num-people) / area-of-equality-triangle
: h2 G( E. R: _: f( nend* a( s; r/ {+ V( i! ?* k @' g; b' d& h, x
to-report area-of-equality-triangle
H: G) E" z' E2 F3 t/ n5 M report (num-people * (num-people - 1) / 2) / (num-people ^ 2)' i/ Z$ N) H! b8 ~1 s# J% w
end |