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/ ]; k4 b: J- m. W
globals" W. W) W @1 c& x
[
% e( W) H0 f" ]* W3 C: U: `0 j, T* z max-grain
7 d2 l# {& i6 F5 L* n1 H* e" J+ Q+ }8 w/ y
]
' c( m2 U6 b) m1 a' Y9 ?. @/ }+ K+ Q' L; Q' y2 f' K8 r# Q
patches-own
/ n& Y3 A3 Z6 U2 L' ?[
$ Z8 O. D( O* k grain-here * A4 Z( m& B4 ^" Y. y
max-grain-here
* {2 N% Q) b- ]( r/ T]
2 A/ ?5 n v1 m2 \* G4 Q
& e% R& C' \5 u l# {turtles-own5 _8 x" p+ A# H: ], I
[
2 v p- L' {; y4 C9 | age
1 A/ [3 D; U1 T; Q/ Z+ L, v! H wealth
1 G, r9 ~1 l6 I5 T s3 f! b/ C% U+ c life-expectancy
; c/ n4 K: R$ a A metabolism
& ]/ R; R9 B7 a vision0 W: C) N) j& _/ u$ x; k) {5 p
inherited
+ ~( _# ]7 K( e, ]]# z" t! C: O9 q$ ~8 n8 R* x
- ^ F* P7 N. c8 t4 X/ ~
0 Q7 C6 Z5 O+ ^& s" Uto setup" E8 ?5 }! k( ^% D7 M0 C! {0 y
ca) u7 h: I B6 K
set max-grain 50
9 C0 _' R- o% w S setup-patches
+ Q7 q, K# d; H- U setup-turtles
0 w7 d! ]( `1 h2 F3 t r setup-plots
% h% x8 g0 I0 \+ [9 J- a update-plots
5 T$ N( k/ [1 t# P9 H lend: X* Y I0 J( t4 K1 M# X1 h/ s S
to setup-patches6 J5 _% G3 } F0 F& ]
ask patches( \; q0 J) G+ T. X; r0 |
[ set max-grain-here 0
4 U& `. C- t2 R L: J' j if (random-float 100.0) <= percent-best-land: w; |# `0 k% C- L! q \6 a4 E
[ set max-grain-here max-grain; K5 M( m$ p8 D
set grain-here max-grain-here ] ]1 X: Y2 M& _% A
repeat 5
1 s$ {1 X: E2 ] Z3 x [ ask patches with [max-grain-here != 0]+ b* j2 b( K1 {; U' h. W m! p
[ set grain-here max-grain-here ] v2 L0 q4 Q) |5 e
diffuse grain-here 0.5 ]
3 e$ k/ g* O( g1 o1 J; z repeat 10
4 l$ Q& z1 u6 e+ C [ diffuse grain-here 0.5] ) H$ Z8 T* g# r8 |6 [, e
ask patches
2 b7 y V) s4 l+ G [ set grain-here floor grain-here * v: ^+ b5 C/ h
set max-grain-here grain-here 0 E! s8 ~5 a/ c
recolor-patch ]" ^# v; m6 j( L) C/ G
end
$ ~, `4 ?( q& Z5 V, ^7 Sto recolor-patch
1 m7 O( C) X* u set pcolor scale-color sky grain-here 0 max-grain
V: N0 \" F; Y% g% rend, c. _ u: B& l& g
to setup-turtles
; v5 N, X& z# y4 S2 } set-default-shape turtles "person" |8 H, c4 ^4 O, i! i, @' M0 G
crt num-people
8 ?% s* v7 `3 |' @) D: @( [ A [ move-to one-of patches 4 k& S+ @/ _- L/ {0 o4 d) U
set size 1.5 . p1 V5 w5 Y. }3 z' m
set-initial-turtle-vars-age8 i$ u& d* \! }8 a# E e
set-initial-turtle-vars-wealth! [4 X* B% T! S4 M& r" |( _
set age random life-expectancy ]9 K2 C8 @; p- Y7 V, X6 P4 d
recolor-turtles; U* v% M4 A5 M) D6 K
end
5 i6 u6 Y- Z& m; ?- s4 a, x5 ~
' q/ Y, R5 Y, D0 z0 O1 q6 _to set-initial-turtle-vars-age
1 l$ K- @& n! e0 D let max-wealth max [wealth] of turtles: V! I: ]7 r) m* T0 q
+ ? e) _5 f) D1 E ifelse (wealth <= max-wealth / 3)
( b# X6 O# ^$ R8 j7 f5 N [ set color red
+ Y9 A8 b& Z* B0 H+ I! ` set age 0
$ {0 U5 i( d" Q7 o face one-of neighbors4 # c9 G% n/ Z) Q5 y7 P, m0 r; l
set life-expectancy life-expectancy-min +0 _2 j4 Z- z0 P6 D% R6 J: H: `9 Z
random life-expectancy-max $ r9 D& A# w c3 Z7 r
set metabolism random 1 + metabolism-low
& A& F0 x6 S3 s) J. v# t set wealth metabolism + random 30
7 O# b& p& a: K7 C" R set vision 1 + random max-vision( v% y5 v- a7 D9 M" G
set wealth wealth + Wealth-inherited-low ]1 Y- `- ^7 w" q1 o7 B; ~. ^
[ ifelse (wealth <= (max-wealth * 2 / 3))# c& Y2 W6 r0 g8 m" p) w
[ set color yellow 8 i6 |$ H8 Q5 c
set age 0
0 O/ i1 e" |) I( t0 P: ^ face one-of neighbors4 $ c# ?0 p! g9 k+ ~8 Y, Z7 F5 s
set life-expectancy life-expectancy-min +: k2 P+ v9 c$ p/ [4 M
random life-expectancy-max + 16 W; h7 g2 K r+ a
set metabolism 1 + random metabolism-mid
# _2 v0 r+ T3 i9 M8 b0 c! K set wealth metabolism + random 30
/ C; I5 l( \, V' e6 d9 W {8 y set vision 3 + random max-vision5 v& j' O; Z: W6 o. E4 R% ~
set wealth wealth + Wealth-inherited-mid]2 D- v1 o3 h$ Y
[ set color green
) x" y% o) f( ]) y. q2 X. O! d8 ^ set age 0
# M. Q6 f8 X+ \ face one-of neighbors4 ! e1 B$ ^: m0 u' h( f/ f
set life-expectancy life-expectancy-min +' L4 o4 Q z8 I$ s- F) N
random life-expectancy-max + 2' d& v: ~& Y% j! r& F9 I# h
set metabolism 2 + random metabolism-up: L7 v- C, D# O' E6 B
set wealth metabolism + random 30
_; K0 _9 x5 Q set vision 3 + random max-vision- X0 N4 L8 K: B$ O6 S, _
set wealth wealth + Wealth-inherited-up ] ] 8 ?+ D2 U6 A) _! D/ Z' p2 h
$ C0 E0 A( p6 H) N; ~( F% @end
8 C* d, Q: `1 k- F, jto set-initial-turtle-vars-wealth2 I' j* M- A* Z" ]1 n; W- M
let max-wealth max [wealth] of turtles
' _! e) @! o8 v: y* k set age 0# ^0 E! d; M1 g4 A$ E8 G
face one-of neighbors4
# E0 ~: i+ G2 O set life-expectancy life-expectancy-min +
5 i7 l' H$ t, s random life-expectancy-max 5 u$ w, U, P$ B; F) f& p
set metabolism 1 + random metabolism-up
: U9 d7 }5 N" n+ X set wealth metabolism + random 30
+ A$ A) P* |( l( Z set vision 1 + random max-vision
; x% @4 I: K# q K3 L8 v& [" Vend
0 V# _+ q3 q* _$ }; h; \to redistribution5 R0 S4 q- [% V7 s7 m
let max-wealth max [wealth] of turtles
3 }8 W, h7 j; X [5 xlet min-wealth min [wealth] of turtles
1 o* _& }. W1 ^if (wealth <= max-wealth / 3)
! b' s* }2 w2 ^* R: a3 S% } [set wealth wealth + Low-income-protection ]
" C5 y8 P- g) q2 `8 V9 oend- o6 S2 a) S7 |. H7 E7 H
L; M. b9 ]7 s: l0 w
to recolor-turtles; h5 k' Z+ b0 M' ^ T
let max-wealth max [wealth] of turtles! U( `2 \" l' e$ L
ask turtles4 J9 |: p! K" R4 W/ s6 ~+ z
[ ifelse (wealth <= max-wealth / 3)
# k1 D" e* Z( x7 x" S [ set color red ]
( `- ]7 B: k5 G+ _2 f [ ifelse (wealth <= (max-wealth * 2 / 3))9 D3 _ {$ I$ i. Y9 B- X+ Z* g
[ set color yellow ]
9 y- ]) M4 Y# n @, d5 F [ set color green ] ] ]; v0 z5 V4 E( I8 n4 C3 X
ask turtles [ifelse show-wealth?3 r8 ?1 A, ]- u* n% n, n7 C n
[ set label wealth ]
' g& W: w; B5 g* } [ set label "" ]]' j7 D% Y+ m ^% E* o
end8 I3 B9 c# Z; ], w3 x, D' e
( `8 f H( |8 V8 zto go/ e' s. J+ T. X, L
ask turtles' ^& l+ N* e9 f# O& `$ j1 Y
[ turn-towards-grain ]
; N/ e# F. g0 q w8 _" l harvest1 ~2 q- s- E1 k
ask turtles
+ E& Q2 q/ T9 c1 V3 s0 n [ move-eat-age-die ]
9 [7 d' L6 I9 ~( |% Y recolor-turtles2 Y# E+ d4 w" E- N
if ticks mod grain-growth-interval = 0
: x5 Q/ Q6 R j4 M7 X [ ask patches [ grow-grain ] ]6 r) W2 ^6 o$ X8 x
! o6 {( j3 ?+ C* l" P) P if ticks mod 11 = 0
3 h! t; j) b7 B) N9 E1 m, \ [ask turtles
( s1 `% u% D+ i [ redistribution ]]9 R' H* t! p; g/ o/ p& ~4 k% a1 g# j9 ~0 f; G
if ticks mod 5 = 0
. L9 S8 f( ^$ k [ask turtles: V, }( y/ N6 u# {' V
[ visions ]]- F4 l5 M: G$ \5 E9 Z/ F' q- g# B
tick
: E; u) o" K$ ^ update-plots N4 e: H1 D3 I1 ^( @) d
end o! Z& }, `$ e. I# s
to visions
1 }/ S3 y/ G# S8 q5 C1 X' ] set vision vision + 1
[! ? p( s1 M( y) uend
; I. ]! a& O+ l7 v7 ^
; f O( ]1 P& H6 I, l' M3 i4 M# K- |! h! j
8 O: `5 V) y4 D" n- P9 O
to turn-towards-grain
2 K. s: C$ |7 m set heading 0
; E1 b0 d8 `0 H let best-direction 0
* x! B1 `' E) R, {: |3 {0 H- b let best-amount grain-ahead
* g6 V$ Q$ W1 L set heading 90% F6 b- k2 R: H
if (grain-ahead > best-amount)
: m* V; a1 Z+ H" I# {) Y. C [ set best-direction 90" T/ N' l- i8 G: r8 J+ w# @
set best-amount grain-ahead ]3 o$ x2 U& ]8 g0 Y
set heading 1803 E! q" z+ R0 H k
if (grain-ahead > best-amount)
" p7 w6 y3 H+ K$ S0 I [ set best-direction 180
0 V8 S J: g. K set best-amount grain-ahead ]
: g+ V. |% t) s9 d- h set heading 270
: F T# K! A' c) }! o if (grain-ahead > best-amount)
2 ]: R7 |0 O* V$ `4 ^2 w$ { [ set best-direction 270- F- ?8 W& I4 D+ F3 H I' ]
set best-amount grain-ahead ]
; I& n0 u) i D' A! j/ ] set heading best-direction
, m) t# X, T7 } R+ bend
( s+ Y, i6 {/ ]8 Z0 X' P/ T
" x5 r/ F- [8 w$ i$ L. u$ ^5 r- V% r! J% X) Q: i% m
to-report grain-ahead
8 n" m" {$ z7 _6 Y+ S% t3 }6 _ let total 0
3 C( y+ f6 S* B7 p let how-far 12 `; ~/ W1 E# t5 a! ^" r
repeat vision/ \3 l2 a5 ?7 C; v
[ set total total + [grain-here] of patch-ahead how-far
; x/ Z( B. L1 U& Z" P1 L set how-far how-far + 1 ]
" V) W4 i+ Q1 f/ g o+ Y Q$ H& c4 p$ q report total
; [8 D: A5 C2 q. gend0 G1 X- Y0 l' {$ i; U1 B
5 z- I2 ~3 [+ [/ t, P4 x
to grow-grain 4 K* ~% C. ?& L( X/ O
if (grain-here < max-grain-here)
( t% H. x8 P4 K4 E3 ]# ] [ set grain-here grain-here + num-grain-grown
. s' k0 Y( x! ?- |; ]' ` if (grain-here > max-grain-here) # t9 R/ X7 `) e* L0 E) [
[ set grain-here max-grain-here ]+ |3 ^. F- o; {4 g, ]* \
recolor-patch ]
/ H$ x8 |8 Q6 ?end
+ {- M6 T4 F% i9 z9 @4 ^to harvest
/ O( ~, g0 }7 X& D/ J% R ask turtles
( ?2 r) v5 X5 N8 t4 `2 ? [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
. Z+ E$ q2 S. i2 c" W2 } ask turtles) I- o2 H# N0 I5 P) h
[ set grain-here 05 C, Z w. Z9 K/ A) B' y
recolor-patch ]' i; h- f+ X. m6 h
7 z/ { ?$ n5 ~$ ^& g" Y! |% tend
& d/ T; f y o/ c; ?
7 j' p- E8 V& w; [* G! qto move-eat-age-die
* c! @* p8 B- ~3 e, ^+ x W fd 1
6 f8 t, l( V+ Y8 n1 j set wealth (wealth - metabolism). O/ s5 z( }! z5 Y; H x
set age (age + 1)6 Z' T3 f+ X9 k# a
if (age >= life-expectancy). U. @# l! A4 ~; t! V. t3 m0 t0 S
[ set-initial-turtle-vars-age ]
# d# d* s9 q2 i/ p, G: i3 f; I: {# w; p if (wealth < 0)
1 N x+ o, K* V [ set-initial-turtle-vars-wealth ]
& N. f; w9 a4 T
" x9 t I# N7 \) ^5 I) w3 h6 n8 Bend
1 y; E2 p& G' t" U1 k# c! R6 O. _: K" g, S* M
& ]5 w. B# k2 j8 l) v9 Uto setup-plots
' b9 g# c& B& @7 J! |; a( a set-current-plot "Class Plot" n6 |! L4 D h
set-plot-y-range 0 num-people
x* a8 Q. i. k& f1 D6 d. f set-current-plot "Class Histogram"6 _- D% E+ z9 _+ ` d0 k
set-plot-y-range 0 num-people
3 F( P- G" X1 z2 C- @* D+ Y$ aend
; F! g3 R2 }) o# b! z% A& L$ J
$ C1 W0 x4 r% [( K$ _- R/ Nto update-plots( c& A! m7 ~& a( @* B
update-class-plot
" r; n; f: z4 n9 q update-class-histogram
1 e/ u. q1 ]9 ]. ^ update-lorenz-and-gini-plots
1 S! C d% h$ j: [" R0 qend
8 W; H9 g) a5 f; o1 p2 K' [% `1 d8 b. M$ q
to update-class-plot
! Q0 O" G% {$ g/ w set-current-plot "Class Plot") |8 h+ G' e' Y& X1 M( E' d6 p
set-current-plot-pen "low" m1 [; v) H$ p
plot count turtles with [color = red]+ w% l- B2 |5 l. |
set-current-plot-pen "mid"
& g" j D& Y3 L! i m- i plot count turtles with [color = yellow]
2 u( [ H! c: w3 T$ t8 T( O5 v set-current-plot-pen "up"+ u7 U6 P5 O5 O* l6 p
plot count turtles with [color = green]" c$ }3 S; E; ~" L+ J
end8 c$ z$ q" X7 h2 ]! S6 r! x
+ o0 {# E; q; R: Q2 y) Hto update-class-histogram
6 C; I7 N* j7 @ set-current-plot "Class Histogram"/ ]3 l" b6 `- U: m. M2 G. X
plot-pen-reset
' f; @4 Q/ ]; J8 p7 o set-plot-pen-color red+ H' n8 C8 j$ w6 |& m
plot count turtles with [color = red]
! T; \/ L O- t& U5 C& e R9 ~ set-plot-pen-color yellow
1 l" g8 g! ], t' ^1 u plot count turtles with [color = yellow]% V) m) W! P' _- H4 S$ F3 H# R& R1 Y
set-plot-pen-color green
) q1 X1 K# i2 N3 i- Y$ \) s plot count turtles with [color = green]
- f& _& ^. v. C6 xend
5 g+ q$ W3 c: Y& o3 W+ mto update-lorenz-and-gini-plots- [0 I% o) \7 ]1 S+ R/ L* Z2 V
set-current-plot "Lorenz Curve"
( o% K( B5 Z" U: G clear-plot
! @6 b! j# o9 a9 s& f6 ]) l A2 M- c% _4 N9 v$ |
set-current-plot-pen "equal"! g! M' V, `- U/ b) W! O
plot 0$ G! {, a7 I$ K5 f- J3 R/ z
plot 100
* @! G* q6 U( J5 x
% j! u. u! b a1 f6 J* r6 R* t set-current-plot-pen "lorenz"& B0 N' _9 ~4 A0 u6 K' x4 Y, Y
set-plot-pen-interval 100 / num-people& J4 S9 f9 n7 ~) x! H n" }
plot 0
; Z8 B# c1 T% V2 I m% J
; z* X$ k; u) d; q3 X let sorted-wealths sort [wealth] of turtles6 Y9 S& p# l: a! k$ B; ~
let total-wealth sum sorted-wealths5 D$ }9 K, t7 I+ {
let wealth-sum-so-far 0
% y6 J( v7 N# Y let index 0
0 I6 P) t, r0 @, t6 s let gini-index-reserve 0. i1 ]: f' a4 z0 ^
; M `% a0 L& F( k2 j repeat num-people [2 ]% `8 y3 @* f: o" }4 R# T$ a
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
' G7 `' C6 N/ s$ H' Q% Y& M plot (wealth-sum-so-far / total-wealth) * 100
& f6 ?( O+ n5 a0 W8 ]* s5 F set index (index + 1)
! G. m- Y& Y: o0 n set gini-index-reserve
H5 _! [* n4 n# J; q% S8 x. _ gini-index-reserve +
, @. X2 K; B# {; n (index / num-people) -
" z' o( q' L K7 _& e9 E; J- H! N (wealth-sum-so-far / total-wealth)
7 p+ t8 `7 I. g& E- Y ]
( E7 z9 l5 ?5 ]/ M I. A, c8 a6 c
set-current-plot "Gini-Index v. Time"
# l( D$ H* u8 i( f plot (gini-index-reserve / num-people) / area-of-equality-triangle
. M% Z1 M& I1 d. {' N) dend
/ K( S& I% @1 ]. Bto-report area-of-equality-triangle
" _+ x! t- t" o* ]$ _ g report (num-people * (num-people - 1) / 2) / (num-people ^ 2)- l: u4 O, E& ~/ v2 ]/ t) N, l
end |