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" n8 `: [/ T( A, w; G0 ?0 ?
globals) e c8 T% x& f7 v9 d/ E
[! ]/ m6 m5 l- F* F" u
max-grain ! |3 E% s6 f7 _* s, s3 P
6 x1 c! u$ ]8 N& |* K2 A6 R]/ f! F+ @- Z' l: a' M
/ _; z2 Y; U, v2 c. e9 U$ O3 P# q0 F" hpatches-own. [! }6 {( A- s0 ^
[
, v+ X4 m E, Y grain-here
, j- |4 b3 ]$ X8 }5 _ max-grain-here
; }/ q* i( s' [# Y( z4 G] P g: O( F4 j( o! Y2 H
1 K5 E$ Z. f1 v% {8 x( F9 x3 O7 w, @turtles-own
& S# @ j6 `! V; `& h& n" ^[0 h4 r2 }1 E# u1 a. C
age , \" d4 B6 }5 N) b4 W8 T. ^
wealth 3 a7 N( X4 j2 M7 v1 \ B
life-expectancy
- a% r) x* R- w7 N' t metabolism
9 L- Y* O. U( M vision
, u* f& M% y0 E( r) a inherited 0 R' |- [: V$ [% D
]$ s. C- V# G) v2 F U
0 q- u' b# p/ d1 H. m5 ]- B
4 P$ K# ]4 `5 O- s" d+ Yto setup( z8 M, n4 P! @! i% I) c0 i
ca1 b# ?$ j1 v- x+ {! D! N
set max-grain 50
2 {" g% h% E2 J setup-patches
~9 U' f$ o3 s5 s& F5 \+ a( \ setup-turtles' h+ K# l4 b6 E
setup-plots
& j3 V# d' u' b. _1 T9 D7 Q update-plots
8 E& [' Z& r* x: Eend
/ r w- o. H( T# B8 k* T- L; G" Nto setup-patches
& v/ g3 Z6 E* U( ?9 H( V* _ ask patches3 r9 T8 }3 }9 n7 k; S
[ set max-grain-here 0" Q! D* C0 K4 z4 M+ C7 a
if (random-float 100.0) <= percent-best-land
+ ~: d6 z8 Z4 S3 q7 O9 F9 @7 z2 k [ set max-grain-here max-grain
. g' q; @" ~; f j# d6 Z4 @ set grain-here max-grain-here ] ]; E h2 t, T$ t# d# _
repeat 51 ~) @8 \2 g" |( a% r# J, `1 i/ F
[ ask patches with [max-grain-here != 0]! V6 H3 K! A* W' e9 D
[ set grain-here max-grain-here ], W& N1 O9 O! E. `6 e. @
diffuse grain-here 0.5 ]
$ n7 |8 ]& H0 p* i8 {: `: M- _ a% }: @ repeat 10% a/ k7 _, _1 C+ E8 J2 S
[ diffuse grain-here 0.5] # F8 x4 u5 u' r8 |
ask patches1 y K5 y, y; w9 A. t" W/ v
[ set grain-here floor grain-here
4 e' d7 P! d( A" z) o5 H set max-grain-here grain-here + M2 |3 l, j, g3 k/ A/ a# r
recolor-patch ]
. c* D2 e0 ~) q" ~. wend
" q4 i5 r* ^4 o9 g+ i: ato recolor-patch
7 b3 \1 s0 o0 G' W1 g set pcolor scale-color sky grain-here 0 max-grain0 ]! [( u/ m4 S( ]9 ]
end: I! l* P* H- H$ J) H. h* e, J1 v
to setup-turtles
3 \, G7 K2 ^2 C5 S' r2 ] set-default-shape turtles "person"8 k0 W& H. |4 N3 x" A
crt num-people/ z4 w a h/ ]! @' S' `3 M$ N6 x
[ move-to one-of patches
! e |% _/ V4 W& {% T- B2 E& G; m: }$ w set size 1.5 # q9 @3 ^- N( c8 \: m# o) K
set-initial-turtle-vars-age
, H% l& _$ k$ T* k4 [- E; q' N set-initial-turtle-vars-wealth" \$ m. i4 V% d0 ?- r
set age random life-expectancy ]
4 `: w* B: T3 K' w" E6 p recolor-turtles9 \! |* @' x- ^' _) B6 o8 z4 _
end4 U# Y$ H }7 \3 \7 t/ G
~+ [4 }0 q+ H. q6 A
to set-initial-turtle-vars-age3 ^1 N$ t! @$ Y0 x0 Y4 ?7 L
let max-wealth max [wealth] of turtles" }. s# v7 W* L1 P2 A( K a: I' Z2 Z9 a
7 P1 V- P F4 F G* {$ r2 w) Z4 w
ifelse (wealth <= max-wealth / 3)
: D8 ^3 {9 ~3 [* c1 X; ] [ set color red / k2 a- q8 N; h* K) m- q
set age 0
6 r0 {* v9 O, w& k6 y0 A5 K face one-of neighbors4 / u) Y {$ B' [" n
set life-expectancy life-expectancy-min +
& J' a8 r& q O- G+ J) ?# W random life-expectancy-max
% ~9 i# z+ B3 [4 y8 W2 [( d set metabolism random 1 + metabolism-low
! Z* I9 [9 c7 {; V7 R set wealth metabolism + random 30
: ~* C. L: Y, N* a2 M set vision 1 + random max-vision8 l: g9 ~, A+ [1 `2 g
set wealth wealth + Wealth-inherited-low ]
' v% G4 l# k/ s* w' G. Q [ ifelse (wealth <= (max-wealth * 2 / 3))
5 p7 Y* Q$ I/ O, p: c [ set color yellow
' g) N8 Q' l3 s% ~2 a set age 05 g9 X9 n5 H% U9 M% [
face one-of neighbors4
n- g* i/ f9 j/ O+ O set life-expectancy life-expectancy-min +
5 [% y# `% g/ L' I; Z$ w/ O7 A random life-expectancy-max + 1! T' T* D2 I* [4 T7 M
set metabolism 1 + random metabolism-mid
9 B8 V7 B7 S( `$ P! g8 u set wealth metabolism + random 30
/ o7 e7 b- ~4 ?7 F. E set vision 3 + random max-vision: X$ G: H! s1 B' {$ }) Z
set wealth wealth + Wealth-inherited-mid]
# m: L7 k/ c% X# Y [ set color green
0 @8 g% ^2 n. {- z, m5 L8 q5 I set age 0, R7 G7 `8 |, Q! b9 Z$ F: c
face one-of neighbors4 " r% ]/ F! F5 A: M7 s8 z! b
set life-expectancy life-expectancy-min +# b% \% d; B1 m( `) O1 M
random life-expectancy-max + 2' s$ t9 V& ~+ i5 \' v$ B7 G
set metabolism 2 + random metabolism-up+ v4 x% }% l8 T6 T
set wealth metabolism + random 30- i; g! r4 p6 u; Z/ W
set vision 3 + random max-vision+ k+ o3 X) a0 [5 w# E1 y) ?/ ~
set wealth wealth + Wealth-inherited-up ] ]
2 r7 E4 o5 P( s# ~ , P: v& r% Z. ~0 X3 W
end
d* {, W( i, [- h* _to set-initial-turtle-vars-wealth
U8 J3 k( v! A9 N( m let max-wealth max [wealth] of turtles+ {9 o$ [; v& M, |& U* z% j
set age 0/ o- M* R2 O+ i) U- B3 T- w& U4 y
face one-of neighbors4 6 f. q+ v! i( v
set life-expectancy life-expectancy-min +
' ?2 _1 {/ q& ^( U6 { random life-expectancy-max
' ~1 x4 L1 @, u8 @1 l+ Q set metabolism 1 + random metabolism-up& ~9 ]5 V v- l% R' s5 G3 l. |
set wealth metabolism + random 30- k2 p; n7 p8 |
set vision 1 + random max-vision 8 Q" A6 V! a6 P W
end* X$ ^: N' l5 h; ]$ `3 @8 ?
to redistribution2 h- c( F5 C% n: w, o9 o3 z+ u2 T
let max-wealth max [wealth] of turtles) b5 b$ E4 w2 i+ F# o
let min-wealth min [wealth] of turtles4 ?: y6 h& L' X. B8 s( h0 @
if (wealth <= max-wealth / 3)" M6 c+ k( a4 c' v
[set wealth wealth + Low-income-protection ]6 m* K/ d. X1 K& U0 o" A& h
end
4 N! }) r3 |( w. w9 M
' V5 L2 Y2 q/ Y8 B! V0 f4 Bto recolor-turtles
3 u. [% a- x" v# U let max-wealth max [wealth] of turtles
1 e4 n% C4 q7 @7 [ ask turtles
6 Q$ N* l8 U# v# ?3 e [ ifelse (wealth <= max-wealth / 3)! |- p9 z8 S2 d; }
[ set color red ]
2 S. l. I/ N }" g9 u2 V5 r [ ifelse (wealth <= (max-wealth * 2 / 3))
8 J: }- E% h- M. i7 W6 n! X [ set color yellow ]
U6 H) r' r4 G3 B* w* _ [ set color green ] ] ]
; H: n% K6 |4 B ask turtles [ifelse show-wealth?; S0 N6 r' f, P9 ]7 E1 F
[ set label wealth ]: ~, L! \$ e6 Y+ e+ J
[ set label "" ]]
" r! d! J6 C' [' Fend
, O+ e% E) @2 ?# u/ i
% s6 t- a6 Z& A. V7 kto go
! p! ?' j8 l0 u6 q ask turtles
7 X0 I ]% [4 J; J( t+ e# |3 V# x, i [ turn-towards-grain ]
, ]2 B+ u, j' q: s) C harvest: t! J( |( X# x' c
ask turtles! e7 i( X( @9 p
[ move-eat-age-die ]5 F ~0 N2 M) F2 g# U
recolor-turtles/ l1 n6 B+ ~( U$ e8 j0 s: U
if ticks mod grain-growth-interval = 0
7 B" u2 l1 f$ i# }7 w' c/ L8 ?, r" g7 O [ ask patches [ grow-grain ] ]
/ u7 o2 r# j5 H' M$ e ) y( T1 d0 i5 z! o4 D, x
if ticks mod 11 = 0
# X! ]$ a1 g& N7 f4 j0 c1 e* I a [ask turtles
+ A9 j3 H! q& {; h- P8 M8 @; O [ redistribution ]]
f/ U) i, q$ z( M. h' r- j if ticks mod 5 = 0
! t# I, H/ z; S [ask turtles
! ^2 B+ T2 O# h2 G6 p+ A; M) y [ visions ]]& d' @1 a- J& O* @7 s8 V. l
tick
2 W- G1 b7 |- B update-plots
( k) U" D* ]/ j; i8 V( {end# J2 b! l! N7 }1 D: W$ K2 q
to visions
, r2 ~3 T, v9 w5 n set vision vision + 1
/ Y5 B/ N6 N. J; jend# x/ b* Y# A. R& P0 _' T4 K
, A$ x% ], V0 V7 l C+ ?6 D
3 e. j) Y- D8 l+ Y
- \/ A& C; l$ u4 [$ \' lto turn-towards-grain
2 {& `' x5 s9 _$ [; v4 k+ C set heading 0
- [5 D2 ~* z _, Q% T' t let best-direction 0% O2 G# w0 y9 N: E
let best-amount grain-ahead* Z4 I( x- Y; |* C; N
set heading 90
: c) |/ R; x5 J }3 s1 v5 u if (grain-ahead > best-amount)
6 Y8 p D3 M4 j8 H4 |! a [ set best-direction 90
1 x2 T" B5 Q1 ?4 d& v& N set best-amount grain-ahead ]
; k' ^$ q7 _7 Y, d( _ set heading 180
, k" ^; {0 v' F$ b' v$ a if (grain-ahead > best-amount). r' T' W, N' B% q/ W0 c: [- A
[ set best-direction 1809 O o/ C U0 o' M
set best-amount grain-ahead ]
# ?. y; T+ B9 |* u0 i& P0 s) M set heading 270/ P A: q5 m# Y2 J0 H& Y- V, U: k
if (grain-ahead > best-amount)
6 L; A" ]* y6 x, O- V [ set best-direction 270
! R% h' w" v5 `, x+ |& k6 V' j# M; M set best-amount grain-ahead ]2 H3 F. C! ]! a
set heading best-direction
- A! v7 `3 Z5 ^0 G0 z$ wend+ w, S. f: |) v& j6 I
8 f! M% ^. p0 U2 w d$ @
# l, g4 }+ k( q2 c9 ^3 }+ J- gto-report grain-ahead 4 N7 F* X" S, h9 k
let total 0' m* P9 }$ H! t
let how-far 17 n: S0 w; v) q0 b) B/ r# h3 v" j4 q
repeat vision
5 D/ z# J4 r) l" x- U) i [ set total total + [grain-here] of patch-ahead how-far
( P: Y1 N* c2 S- l: T set how-far how-far + 1 ]% K$ _7 A$ x: q" h- K5 W
report total( |- B; w8 e8 S6 ~" D
end# c, F5 u, G* z
+ Z- `8 K0 U* X7 V. |1 g
to grow-grain
4 E- a, U7 R, C9 N- P9 d' J- k, ^ if (grain-here < max-grain-here)
& u( ?, Z; A& q& V [ set grain-here grain-here + num-grain-grown U% R3 M9 V. }1 B8 L
if (grain-here > max-grain-here) 6 { N" V. ]. k! g9 u
[ set grain-here max-grain-here ]
3 n" N! ?( J2 V$ u9 Y: J& B2 _, d, p recolor-patch ]
' A6 N8 }3 R; H9 i rend
0 K$ |! \$ D! O( d- i6 ito harvest* @6 E- f& e. x' i
ask turtles
2 M, P1 W, ?" i- r0 Q [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]$ a5 l1 I+ t3 `( i& p
ask turtles' K; z* b x; @: v
[ set grain-here 0
0 ~: n6 F7 [0 k0 N7 A( ^ recolor-patch ]4 W0 G9 Y" G0 l- I D6 [. Q$ k* W2 E
$ f G" o- y) i0 n9 r6 zend$ S. U1 M, J2 d7 b& k
9 j( E- g2 E7 G2 |to move-eat-age-die _( y! c6 p* e }& w( K$ `
fd 1( Q- Z6 } j7 V: H) j
set wealth (wealth - metabolism)! O$ @, @' V9 y) G, x Z9 B
set age (age + 1)
; i" c% V9 r7 i8 y h9 u if (age >= life-expectancy)% t$ p. p: K, T4 y- @% ^, g$ [5 v
[ set-initial-turtle-vars-age ]/ ^% {, F y! [& J
if (wealth < 0)
5 I; L7 t& G) c% Z) J [ set-initial-turtle-vars-wealth ]
4 A4 f! {$ _8 e" X# f$ I
8 {: z" P9 f5 ]$ rend
8 `4 s$ h6 T% W3 m6 H2 N( z8 F; D% B& z3 _9 u7 t
|! b8 L4 k) i6 K5 Q- M I# o" T4 Xto setup-plots! d8 W/ h. `2 @: H# t9 x$ h
set-current-plot "Class Plot"* J+ s0 R) p& C: n: s3 r4 R
set-plot-y-range 0 num-people
e G# U" X9 w2 l set-current-plot "Class Histogram"
+ ~5 \+ {3 s2 }) `% k set-plot-y-range 0 num-people
' u" u' c. Q" n, t1 ?- Q0 V7 bend2 t; A% u0 v8 p. x
9 C. S9 [9 q4 c: [ v) P( R8 kto update-plots
! O L* Z$ F/ @& p% u) @. D9 y update-class-plot
" t) q5 O& m. m# z. K, U update-class-histogram5 b9 {1 V1 J4 Y$ }# l! R! {# |( L
update-lorenz-and-gini-plots
, H2 I2 y, G% C5 W5 `# vend7 a; O. r' o, T8 G1 Q
: k1 ]7 h# Z( I
to update-class-plot
7 G: P, M' r" ?% ^; u set-current-plot "Class Plot"$ ` j5 Y1 V# J0 P/ Y* K
set-current-plot-pen "low"
: e' ~. ` E6 r8 ]- T! I1 H plot count turtles with [color = red]
) b X: H2 i. f0 e% R set-current-plot-pen "mid"
* H* K8 n; M; \1 U plot count turtles with [color = yellow]
+ a! B( k4 h! {- l- H set-current-plot-pen "up"
# r( w6 f6 h3 M# t3 I5 T/ [ plot count turtles with [color = green]
! q7 D& y# x- p) j9 U( [8 ~ Zend) X! P7 t5 \% c* `, j
- m3 T3 ~7 z. {7 P2 U% ~9 jto update-class-histogram
$ ]6 l: C) X# ?. r set-current-plot "Class Histogram"
! c+ Y5 J' C9 n& J4 Y plot-pen-reset% ]+ s; k$ x) P- {
set-plot-pen-color red" L3 p) \+ r2 A# _4 V
plot count turtles with [color = red]
4 T5 r. n& J# ?' O4 \, |0 [& L set-plot-pen-color yellow( {+ N! v9 H" K+ z+ L: j
plot count turtles with [color = yellow]
& N. N$ r% e! O, E9 K0 n set-plot-pen-color green% e# R$ Y. E5 g9 p; t" ?
plot count turtles with [color = green]
" }6 D: a9 a& Vend
& _- g3 e- A8 x3 u6 mto update-lorenz-and-gini-plots
7 W6 M" ^9 h. x set-current-plot "Lorenz Curve"
& M* r2 c* x; V% ]$ G. @6 W; v/ y clear-plot& \ j. w" \- `" p9 s- J
. Y! `$ T5 z4 L" n set-current-plot-pen "equal"! i! O- g( A; K1 n$ _2 x$ ^$ S: P
plot 0$ e' [" Z( t. e0 L
plot 100
' ?# u: n; D& Y0 k# W, I9 L, Q" |8 `, e
set-current-plot-pen "lorenz"! I8 _7 d4 C! k$ e0 Q
set-plot-pen-interval 100 / num-people, _ z" J( G+ `1 N4 V+ z
plot 0, R% M# r; f: J" ^! ~9 W
1 Y' O6 M) u+ o, _" ]: | let sorted-wealths sort [wealth] of turtles
2 W* J( R' b: F6 J" I( k+ v6 d let total-wealth sum sorted-wealths
' M; M3 f v& p: G/ L4 h let wealth-sum-so-far 0
, U! I9 U% Q9 ^ let index 0# x3 E7 v& P: _8 Z) G6 W _" _1 b
let gini-index-reserve 0: v. ^( i7 A7 `! B) x8 D; ^
- q* B# k' Q" V: s `
repeat num-people [8 ]! F0 A5 I1 k4 V# t
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths), ?. X+ A6 k0 t6 C
plot (wealth-sum-so-far / total-wealth) * 100
8 X- c; u$ p; D6 l set index (index + 1)
5 e* o, K# P* c set gini-index-reserve3 J( Z. `! [7 Y* A U) Z2 m
gini-index-reserve +3 B4 s" M- Z' J5 |
(index / num-people) -5 {, \: _+ O6 A
(wealth-sum-so-far / total-wealth); O7 {9 ?' e2 K. I6 F) {0 F6 L
]. S" e5 y" _4 a$ i$ D$ b
3 J! u; {$ k& Y0 D! \- e+ w set-current-plot "Gini-Index v. Time", K9 _ U/ v2 p0 X2 i: W# I, B
plot (gini-index-reserve / num-people) / area-of-equality-triangle+ j, M9 j, u" ^) Z0 I
end
6 h# }0 Y5 e6 Y4 B$ mto-report area-of-equality-triangle
$ d& g- e, Z( S' V# z2 O report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
7 P/ O. h: ^% d) send |