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 H' {3 X0 A( Z, c% b
globals7 e, @# d& ]- t4 T8 y6 F
[
7 n ]9 V' u4 _0 F1 ? max-grain 1 R' b- Q1 o. F- V! u
6 x, N0 s3 c# i- T, ~
]2 p' z$ Y9 o- O# s# [/ x6 S
% l' g9 S8 n4 _" {& f/ Y, n1 B
patches-own
# |& t, E* A6 }[
1 [: ?& r9 ^! L grain-here
* }6 z6 z+ N) d& V; B" ` max-grain-here
3 h/ w7 L2 a! x @1 \ b# j]
3 ?% w( u' A% `2 n% J+ a- o( N1 z' U, f
turtles-own/ W. b; m! ^% r& H: A3 y
[
- t9 Z* k/ a1 E8 t4 v& r M/ b3 a age
D. j: j$ c9 l wealth
% B; L6 M6 X5 v: D% G life-expectancy
' ^: K) X5 N$ [: M metabolism
- V* y5 l* v/ p1 q ]$ X vision _) c9 x s5 V- u
inherited : ], J: b u; R/ U) ?, S5 M/ M) s
]' [: i/ j" D+ [4 D, \
% f* y/ ] C- s1 K% m* `+ |
0 f: i' N! D; Z- f5 q" p' Hto setup+ ]4 v/ E4 ^/ p* ~4 g( ?7 s
ca5 I3 p7 }! K2 n6 s. H3 l
set max-grain 502 L; O" p7 J9 _" O
setup-patches O9 x8 I2 }) U4 _: N
setup-turtles; k8 |4 q$ _ X" i1 A
setup-plots
2 i9 _# |5 }* P' h2 c1 ? update-plots
' Y- E- i( B+ {/ @! U( H; z. p: B/ {! Jend ]0 [3 R8 C* {( {8 r; w! }! R
to setup-patches2 ]8 G8 W- b( c. s. ?/ N* `! L& k
ask patches
$ c1 I" I8 s0 c, ^1 b/ j4 ^; [ [ set max-grain-here 0- c: k" S1 g; [
if (random-float 100.0) <= percent-best-land9 S0 N0 ^8 V7 z+ b- h% s
[ set max-grain-here max-grain! d: \. R! b( m1 Q( A: k* O
set grain-here max-grain-here ] ]
/ z2 E4 `. L3 t& Y) D8 J* ^- K1 _ repeat 5
: R4 ^, x5 {! M( g' z8 J+ N% s3 G [ ask patches with [max-grain-here != 0]
4 @' L; n- @+ x) |$ K3 I0 y [ set grain-here max-grain-here ]
5 ?3 `2 s3 k0 f! t9 g- u diffuse grain-here 0.5 ]4 _) f4 c; a3 c% t! H
repeat 10
- M- K. S" R6 m0 ?$ T4 E% w% v; q [ diffuse grain-here 0.5]
: v' J Y4 `: P# m `& M. \ ask patches5 B8 P" Y9 u. P# G
[ set grain-here floor grain-here * x$ ^. W! Y; x3 [% P+ m8 Z+ P
set max-grain-here grain-here $ w4 Y1 ]$ d' ]9 b8 `
recolor-patch ]5 [$ ^* H" M4 a+ s
end8 x9 Z' b8 e7 F8 t# O/ {
to recolor-patch 2 [; N r) C; L- B; L
set pcolor scale-color sky grain-here 0 max-grain& n8 n3 K# q3 g- g" f8 m
end+ `" n: y% }9 e- h3 j9 p# t3 P7 D7 E0 O- t
to setup-turtles# j) |3 V. r& l. \0 O3 w# H, t
set-default-shape turtles "person"* a3 g- Q+ _9 p0 O" |
crt num-people
( C6 n+ J) N+ S# C6 \ [ move-to one-of patches 7 c7 C( G; g8 a
set size 1.5
, w6 s* }* N3 b. a0 W" D# w8 c2 R set-initial-turtle-vars-age0 q- F6 H& I' p- g% z: h0 ?
set-initial-turtle-vars-wealth
. O5 O& n" {: j, }6 m* }7 s* } set age random life-expectancy ]
% p( _+ {9 ?# P, o/ d- ] recolor-turtles
# [ M( H( B9 v' o: ?( w1 wend4 b; F: W' R! N6 Z' b# C5 w* Q
- G6 z3 Y' O0 A3 e+ o+ X! C. o2 `/ Gto set-initial-turtle-vars-age1 X9 g" v4 x0 J6 Y& Q9 V
let max-wealth max [wealth] of turtles
; R; @( {% _ p5 H- N$ m
8 q8 ~2 d& w& m# d ifelse (wealth <= max-wealth / 3)
" [& S* I2 s( i' r5 G5 {( O* ]# I [ set color red 7 e2 m6 Z+ f% A8 X" O
set age 0
! i7 T3 r7 R; o9 H4 W face one-of neighbors4 j8 q# q6 I! e: l
set life-expectancy life-expectancy-min +
2 {9 z8 n- o6 N5 D random life-expectancy-max & N! E; `0 a; D. t$ A7 A
set metabolism random 1 + metabolism-low" b0 B4 A) a! H& {0 k
set wealth metabolism + random 30% Z+ ~; K) S: {' M
set vision 1 + random max-vision
: n5 f5 W5 m2 B set wealth wealth + Wealth-inherited-low ]
; V5 e" \. _3 _9 D1 I. z" o [ ifelse (wealth <= (max-wealth * 2 / 3))
8 d, Q9 Y' c: z5 j [ set color yellow
A" ]" U, o' { set age 0& n& x* z3 Z/ o% U6 I
face one-of neighbors4 $ g+ p. `. d0 @. u. z
set life-expectancy life-expectancy-min +
: y( d) A: k# ?$ x random life-expectancy-max + 1/ y9 b- y' x2 v) w. Z- C, O
set metabolism 1 + random metabolism-mid
' V7 ? O5 ?1 p7 K1 L8 p! u6 j set wealth metabolism + random 30
0 z _+ w& b& `4 ]7 Z, ?. n# H3 K set vision 3 + random max-vision( |8 S, b% b9 w' X S' z$ E
set wealth wealth + Wealth-inherited-mid]0 F, W& H6 C+ x
[ set color green
. J3 `( V/ k8 ?0 L1 M2 b set age 0
! o* H! P# u9 z, f' }; } face one-of neighbors4
8 O( b' @2 u" d" K8 P$ x set life-expectancy life-expectancy-min +4 j6 u" G$ }# h- K1 I4 D) h U
random life-expectancy-max + 2- Q; w) ~( l2 P: a |# L1 s8 {2 s4 G
set metabolism 2 + random metabolism-up
2 D8 {. H* q4 F4 R4 D) |0 z1 g set wealth metabolism + random 30
9 o/ a9 A7 r8 k! W set vision 3 + random max-vision/ H6 W. O* T8 S6 H
set wealth wealth + Wealth-inherited-up ] ] % p Z" t- A& _% a) r' w$ S
/ I* \% ?7 L" g/ o+ jend+ n9 O* g! j, {8 h5 S
to set-initial-turtle-vars-wealth
2 z: ]* w& o5 v' v5 c' g, ] let max-wealth max [wealth] of turtles
1 u4 N% b" g$ A# b# V- a set age 0
6 x# d+ X! } Z face one-of neighbors4 , t; J; V1 e' |6 l$ o* K, X
set life-expectancy life-expectancy-min +( n" k" Z' O1 t' S5 T0 G6 R% V
random life-expectancy-max
5 @/ t/ q+ H* b- V E0 g" r set metabolism 1 + random metabolism-up
2 x8 Q a6 E6 ~; r6 I7 N% y set wealth metabolism + random 304 u( M* `' j* w
set vision 1 + random max-vision ! U* ?1 H1 @8 c; @! V
end
8 F7 r( [6 @3 F4 i3 z! u" [& Uto redistribution, x8 ]) l" P2 @( O7 y3 b
let max-wealth max [wealth] of turtles
5 ^# \2 H A, U0 Q. Slet min-wealth min [wealth] of turtles7 i+ M8 Q8 a5 Z/ `9 y
if (wealth <= max-wealth / 3)+ N" o, h; ?. E( E
[set wealth wealth + Low-income-protection ], r, L/ Q" J! A6 |* A2 H) D- F! [3 D
end
' Q7 J% ]1 y- ~! x
' {6 h7 I- M, y1 bto recolor-turtles) \& ]& [, \) N, v3 l" d( P2 H
let max-wealth max [wealth] of turtles
. C! v g; B1 u ask turtles; V& l# ?) [2 W# A
[ ifelse (wealth <= max-wealth / 3)
* b' R* z7 S; l [ set color red ]0 {" K0 d( p1 z% Z, r1 s
[ ifelse (wealth <= (max-wealth * 2 / 3))
1 \" s( \/ W m" t6 } [ set color yellow ]9 B7 b4 P- E- f/ ]: H
[ set color green ] ] ]$ k4 ~( F" @) S& k
ask turtles [ifelse show-wealth?
% u9 l) S4 \% e5 ^2 z L3 k) S5 n [ set label wealth ]! Q4 m: N* b" C/ V- V X* y) _+ I
[ set label "" ]]
3 X" I% A! D7 q) |) _ q: Mend3 Y0 M% ^. j s. i6 v, U& Y, f9 D3 \
, Z+ U1 V8 C/ B
to go
, y* w# o0 y/ A! f7 R ask turtles3 V/ k. Q$ l5 k0 P* o( o# O
[ turn-towards-grain ] 5 ?! Z) k- k, S9 Y" ^) } j0 `( S
harvest D0 C4 L3 g2 K% D& z7 x
ask turtles
3 \8 x* Q9 N+ g _! y [ move-eat-age-die ]+ b0 q% r$ }/ H5 E, @5 V
recolor-turtles
0 i4 m/ B5 h8 M. S- g if ticks mod grain-growth-interval = 0
' F# T6 o/ X$ A' U2 T o" _" S- J& k [ ask patches [ grow-grain ] ]
7 V3 K" _" P/ |0 G+ Q! S3 r 1 X _9 Z4 @4 U
if ticks mod 11 = 0( \9 D7 ~! t$ p" t: o$ }) m* n
[ask turtles
* B9 R5 @' o% c2 X [ redistribution ]]* R; i; x% n3 |' D- Z
if ticks mod 5 = 0
) k d: u8 E2 D/ T/ | z* s6 i [ask turtles% H' W# k/ `9 c8 i) u( \
[ visions ]]/ Z; i6 X, W4 m9 ]$ D) z' ~
tick
; o5 j5 c' v5 Q4 U! @ update-plots7 _8 E ]" B) P6 Z7 H4 Y
end
0 s x" `6 `. ~& o" ito visions; k; L0 B$ C- V0 A1 `& t
set vision vision + 1 , @7 n5 s L% l8 s" m2 n
end
! C/ `1 h& f9 x! d* p
- P; b* W$ b: K- c2 d5 [: N' x' `9 P M6 R1 c
. o2 p; Y) N( Kto turn-towards-grain
: D0 l B s! c: n5 o3 ? set heading 07 S3 n% l, B) k# r& U
let best-direction 0" {; \- b$ U2 R$ v5 t- K8 b
let best-amount grain-ahead2 \, \, v* l9 T# w5 S. O
set heading 90
% T" X4 H( [! r4 R4 X' q T if (grain-ahead > best-amount)
% f! }" ?4 D, k8 Z5 t# P3 c8 D [ set best-direction 90; e7 `, a9 L& J: ~. q r
set best-amount grain-ahead ]( `. J. ^. t) _
set heading 180! S8 L% Q% S% V! O5 A3 w* h) L- S
if (grain-ahead > best-amount)
9 ^/ w: i1 S! e! F: a% a3 K [ set best-direction 180
2 F) d8 S& K1 | set best-amount grain-ahead ]
l. n& b6 I6 Q6 v% r! v set heading 2708 L& }0 ^8 `: ?6 Y# n' C
if (grain-ahead > best-amount)
3 `5 a p" O9 L" J5 C% Y9 x [ set best-direction 270' ~( L- \ X3 [ t0 c& G; O
set best-amount grain-ahead ]- K9 K, N: S$ {! i
set heading best-direction4 b2 \6 i8 u3 w4 f% q* n
end
7 x; p$ t: g+ g! B/ c4 w$ c0 C0 {
8 X7 I$ b6 {' X- d+ |9 \2 P) f# D* C7 [
to-report grain-ahead
7 I$ @; V- c, q let total 0# ~. f5 B: G' Q; ?8 g( E" Z
let how-far 1
& F+ l6 [& |7 x3 L+ J) \5 Q repeat vision
) u3 t; U E' I* d [ set total total + [grain-here] of patch-ahead how-far( M, @/ K0 g3 \. l# A" p
set how-far how-far + 1 ]
$ u4 }3 f2 q" i5 M report total3 ?6 _! A: P1 B4 O9 e( C5 p7 s; l9 k
end0 i) S+ E* e" Z5 |9 q
5 j- z( T3 p9 y: s5 A B: o6 jto grow-grain
/ P: F& f% a* F# e. R if (grain-here < max-grain-here)
" y5 u- J* Q9 T6 o3 u& `7 A& t [ set grain-here grain-here + num-grain-grown
" {0 Z. s% a5 ?4 `7 A- `9 z9 c' z if (grain-here > max-grain-here)
8 Q- ^3 r! M U O2 Q4 e [ set grain-here max-grain-here ]9 p5 ~# f) K1 s( } j9 [- I
recolor-patch ]* E6 ~& o( v# W: k
end- b; z7 a. Y$ y+ N' K
to harvest
4 J, T( {& }) U" u# t# |' h ask turtles
2 \& J1 z) E4 C! ^( I" N* d2 a- o [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
0 Z) [) ], N ?* Y ask turtles
0 e! a C3 I' a [ set grain-here 0
- J& i; i4 `) ]* s0 _* ` recolor-patch ]& O4 U& U! X0 M7 l _8 O3 `
V' C2 E" |) N& C4 H0 P
end( f* x j+ J. S% Q9 h2 J4 g5 [" \: l
3 v2 y0 R, ~$ u$ X8 J* Sto move-eat-age-die
0 J E4 t! t; c: X& _1 _1 h8 x- ]" T fd 1
6 \9 x0 Q4 t6 L- X6 l1 X, y set wealth (wealth - metabolism)
! Y1 w) h" @, E( v) C) z: [ set age (age + 1)
7 D5 y* R# s1 T6 b, Q9 f: E' Y if (age >= life-expectancy)& b) x1 l# ~5 j2 k
[ set-initial-turtle-vars-age ]
$ n7 T2 s: A$ [9 k( h if (wealth < 0)
5 P' V W% y! S! T [ set-initial-turtle-vars-wealth ]
8 U: j: V" A& d7 G
, J& q N1 W( z, g, T* d Qend
. l$ q2 |# r- X1 Z+ O( a+ V/ [/ T# Z# k
4 j& }8 Q o% k" D. Fto setup-plots
. w) J) S7 w% H( r; Q set-current-plot "Class Plot"% r; c9 u. W g/ I
set-plot-y-range 0 num-people. a' e3 N. R! H5 \, O
set-current-plot "Class Histogram"* ~: ~( R1 \5 Z5 y3 w. }
set-plot-y-range 0 num-people* T6 \ i2 M6 x
end. s" g& A9 [# v( C; s% [3 o; K7 a) i
7 {9 e0 Z" z/ ^8 x# J; Y) S% }
to update-plots$ s0 [, i3 @* N# X
update-class-plot
) {6 A3 |$ k3 b) R$ J) J update-class-histogram1 M- l9 i! o9 w, w7 D5 K
update-lorenz-and-gini-plots
9 g3 l, z/ v2 p1 Z4 h. X7 nend9 g" d9 F6 t) T; P0 H
! g" S6 S; g) B* j% O1 P! g$ C
to update-class-plot. a" _% N2 d% h
set-current-plot "Class Plot", |* R" Y s9 _1 z- ~
set-current-plot-pen "low"4 ^" o% r% D0 h9 \, ^) n
plot count turtles with [color = red]
8 ], @$ J: u5 T9 Q set-current-plot-pen "mid"
3 b8 ^6 B4 _; I1 ^+ W" V! ] plot count turtles with [color = yellow]+ y# Q6 `0 V9 |
set-current-plot-pen "up"3 ]7 R/ P" K4 W# {# X' q+ _& | C. N
plot count turtles with [color = green]
$ o2 a9 J, D- G* @3 a2 d9 h9 zend) g9 b! o$ h1 c6 Y, Q0 D5 z
6 T* h8 k5 p2 I) l
to update-class-histogram
6 B4 j# n& r# k' n0 x5 W set-current-plot "Class Histogram"4 r" W, |) H* E" F, E! w2 I
plot-pen-reset5 e0 P8 V" I" R3 M6 Z! G# o$ A
set-plot-pen-color red& s6 [1 K2 _% T( N
plot count turtles with [color = red], V) ]/ d5 i8 x
set-plot-pen-color yellow% [7 R' A) b. \+ g# h5 B
plot count turtles with [color = yellow]
5 E4 d' ^4 |: l1 x8 B1 O3 ? set-plot-pen-color green
r) q* F" L% N) @ X plot count turtles with [color = green]6 Z4 R" E& |" `3 _# u) ]( n
end
( Y- n2 U% z7 q- q5 V/ Yto update-lorenz-and-gini-plots8 j7 [3 Q) B/ M$ o! c. |* Q
set-current-plot "Lorenz Curve"1 Q" `8 k* |& }# P' d
clear-plot7 c5 x5 I# P2 F- O
7 F) [& P% n1 e! Z) g5 I F2 X
set-current-plot-pen "equal"
1 v3 A9 C0 j3 [% ~: G plot 0
- F+ @- d# J: J) j( c& g; Z7 N0 P plot 100; M3 J2 v9 x- }3 J6 u
0 y/ f* j( K6 |3 ]+ Y7 A
set-current-plot-pen "lorenz"4 h, V, u' j$ _* {6 d
set-plot-pen-interval 100 / num-people
7 F2 T: }7 f: U5 F6 L, E, T1 p plot 0' _! k: F, ~- Q4 U9 E1 [/ G! ~& v
! S) p8 y% r% b( E N; ]
let sorted-wealths sort [wealth] of turtles: o- f- m, n+ R
let total-wealth sum sorted-wealths
) d, } v2 S7 d7 z# e let wealth-sum-so-far 09 f: L6 ~) D' E, K( M4 Z
let index 0( t* k' p3 ?+ P! Q
let gini-index-reserve 0
, _, f6 {% J3 e( y) d `/ C
+ m2 T! Z+ v% B3 y. Z% W6 Y6 | repeat num-people [! X: E" N' l5 U4 L8 Z3 n0 E9 X
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)/ ^" R2 E7 H+ ^7 ~. y( E8 @
plot (wealth-sum-so-far / total-wealth) * 100* w3 @! n8 i. e0 y
set index (index + 1)
' w. @% L2 [. P* Z, h set gini-index-reserve
3 z4 z) i9 h4 t+ D1 s gini-index-reserve +
# l1 _! {: G% A (index / num-people) -1 I" u% O7 o& Z. M% u0 l
(wealth-sum-so-far / total-wealth)
: Q; Q: n! p4 L" w ]. {8 x7 l3 ^" }
# n& a6 |5 F& l+ N) J
set-current-plot "Gini-Index v. Time"
3 I: I) F4 [, R' T8 G plot (gini-index-reserve / num-people) / area-of-equality-triangle
+ |/ w0 l) N) M! ~6 D! P, l- D, _end" T! j- i9 A! E4 u5 `0 _8 @# k
to-report area-of-equality-triangle
3 D( L; k0 j0 e7 v* G& q7 E: f report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
- V1 a) u& d, I; Y2 Y& E$ gend |