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: ~2 p" P4 O! S- R; H, z
globals
. d) `& k) f, P5 S5 o1 \. }* m[
* u$ l! z& ]" } max-grain
* w7 X/ }$ ]- q" V) a5 M( N; A0 F3 ]
]
# L9 s; x( ^ ^2 K3 J: k3 b2 W' R
( v' X) v6 @% j* e$ s! \patches-own1 o2 F) X9 p5 a7 V$ q+ }+ u
[
2 d, }) g4 [" X& f grain-here
+ A7 ~. ?' W. }1 m max-grain-here
/ b; r8 e7 H. I$ Q& A9 g]. i( v& S z6 W( `+ a y5 ]% z) K
9 M& L' H7 G" H$ Fturtles-own
3 f& d6 i4 L3 N9 j/ }[
8 h, X, R$ [' i/ M age
0 E* I* A) @1 a1 o8 h# q$ d wealth
: I# l5 E* f$ ~ life-expectancy 7 f+ C3 _* n; D) F8 ?, ^' z1 {
metabolism
2 L6 W* }( B* ?0 r4 O% c' O- R vision
}6 N8 }3 b# }& K. L! L inherited ) ^/ ~ r/ s' z) j0 B; ^7 [
]
) f" j$ ?3 _* P! d: A4 y% c+ J% T* ^/ z
$ s+ N- q6 B1 w0 k' Y
to setup/ r% |& f5 E4 m( n9 g
ca
2 ]; f( C$ A# B7 b; J set max-grain 507 v+ Y8 _& ]- W2 s$ ]( G
setup-patches/ y' L- W/ n" ?1 S& e3 p- h
setup-turtles* t4 |& P" \( G& R* t
setup-plots
5 x. N! {. @+ ^, c5 B8 w; A/ L update-plots5 u# C; L8 B0 ^! j5 k
end
5 [* s9 ^7 |, v1 X( |to setup-patches
* ~3 y/ K5 y) \5 f$ X+ S ask patches, k4 Z' e7 m. ]. t# E1 _3 G
[ set max-grain-here 0
3 y" y) `8 a" G if (random-float 100.0) <= percent-best-land
! z4 ^/ H8 H1 L3 ^* }) a3 [ [ set max-grain-here max-grain
' p2 T1 p+ ?% ]% D. W+ B set grain-here max-grain-here ] ]
9 C2 Y! u2 r- v4 y: T, {! s# G- | repeat 5' ` N# m- l# O5 |- B ~5 @
[ ask patches with [max-grain-here != 0]
1 T+ |6 e6 m1 [ G* K [ set grain-here max-grain-here ]
8 g. e7 Q$ n' V' F1 ]2 _+ e diffuse grain-here 0.5 ]
3 ~5 H0 \) R4 A0 |, w8 g. R repeat 10
5 `- U! f+ K9 I4 W: O [ diffuse grain-here 0.5] 3 P0 `' ~1 g, N& R3 e4 a
ask patches; @( `; X, z5 B0 }; V( X
[ set grain-here floor grain-here
( C' Q; T$ j" Q. \7 z set max-grain-here grain-here + l& B6 x3 ?/ s, `1 K ^
recolor-patch ]9 q* L, _0 B8 d) K6 v2 }) L
end
; `1 m% _' j1 T9 S6 bto recolor-patch
* M- A. y" I6 _' J8 ~ set pcolor scale-color sky grain-here 0 max-grain
: q* e- T$ D8 C& s+ l1 I! Cend0 l# l: C" ]6 s- ]" ?0 o8 ?* t6 {
to setup-turtles
3 \) p8 O' L' {/ ] set-default-shape turtles "person"
7 J8 L+ D; x/ W crt num-people7 [5 z( A5 s5 B3 ]7 h8 y
[ move-to one-of patches ' b4 q, Z2 t: n# @! N; M
set size 1.5
& t4 K* L# v1 B& l4 U set-initial-turtle-vars-age
; @' C* O( U1 X9 K X; Y* H/ q set-initial-turtle-vars-wealth
, ^0 q+ E1 M7 C% N0 `, i( y set age random life-expectancy ]
* M- _8 F2 N& T0 p8 M" ?9 H recolor-turtles
+ S5 i1 Q8 l- b# o5 u/ B% w L pend
1 x1 `4 L) V$ N; @( Z7 k/ R4 w8 P3 ~0 A1 }5 q
to set-initial-turtle-vars-age
8 \4 m: N% k2 Z+ j U# `0 E7 i let max-wealth max [wealth] of turtles
& {( y5 u+ e7 _( G2 |3 A- N9 H
, N C+ E6 M6 Z' e# D2 _# m3 H; H ifelse (wealth <= max-wealth / 3). R& {# R- V- J, B! t5 o( ^
[ set color red + N; Y$ t4 a7 K, e- r
set age 0
7 g: b. r% _" J; Z! H4 @$ t face one-of neighbors4
! _' A% X% l0 T& F. `! b/ D set life-expectancy life-expectancy-min +
4 Q9 ~( R; X. s! {7 Y" K. k# V& k, ^ random life-expectancy-max 4 I. l, @0 w. `
set metabolism random 1 + metabolism-low9 w! e- }7 r" ]* ?9 ?* R
set wealth metabolism + random 30+ l0 M* J' Y: d6 e, G
set vision 1 + random max-vision
4 X0 B( M8 r( E- r* A: a% j7 b set wealth wealth + Wealth-inherited-low ]+ f3 w# I! r5 f7 ]
[ ifelse (wealth <= (max-wealth * 2 / 3)): X) ?5 i$ |' q. N
[ set color yellow 3 g0 j9 p% W4 _3 ^% X7 D& r5 y
set age 0 b$ v) F7 W6 V7 t r! x
face one-of neighbors4 7 B' G: v9 c* G& E8 v2 C
set life-expectancy life-expectancy-min +
, k8 [8 s. R, F8 E$ I random life-expectancy-max + 19 q* B1 v$ S6 w! `2 m$ l
set metabolism 1 + random metabolism-mid
% q) y" @% B' w set wealth metabolism + random 30
* T! s9 g! O4 h* R% @1 a set vision 3 + random max-vision
: n9 L7 E. S- x0 m* Q$ U1 z# R- J set wealth wealth + Wealth-inherited-mid]. a6 w- I- I) z$ w* H6 U: P$ H
[ set color green
( f" N1 z' P+ F* ^. u* ~/ @ set age 0 Q# e3 n6 i3 s' [# K: u ^
face one-of neighbors4
+ a7 Z; z% b+ I9 B8 P set life-expectancy life-expectancy-min +
" I7 p( H( S! r% Y6 G* T" z random life-expectancy-max + 2
, ]# u% T: {: b1 t7 J& R9 m' ]* ~& @ set metabolism 2 + random metabolism-up/ ~! _. c- w0 |8 D
set wealth metabolism + random 30" K5 F) |8 ] m6 p8 M6 w, o
set vision 3 + random max-vision
* y' u! ?- i! s1 o4 Z4 U# ^ set wealth wealth + Wealth-inherited-up ] ] + @& `7 O" \, Q+ u) Q
; f- B! T p# M- N+ r% A
end* Z% F; Q1 }* h: g- A( @) e' d& u
to set-initial-turtle-vars-wealth
" x+ Y2 X+ U) C7 I0 A! C, h let max-wealth max [wealth] of turtles* i: U4 T0 A- P' j* t$ X
set age 02 |, x6 y. ], j# e
face one-of neighbors4 5 q- g; Z2 y, h. D
set life-expectancy life-expectancy-min +
3 i! r- g v7 h, k4 E! } random life-expectancy-max ! h& L" B# `) d7 u. v/ F y
set metabolism 1 + random metabolism-up* B5 y' B5 H/ q f
set wealth metabolism + random 30
7 P* Z* m! ^1 T& q# m set vision 1 + random max-vision
4 p" ^/ ?8 A1 A+ Wend B" P" h3 e; z/ {% F* G
to redistribution# d; Z9 ^0 w5 c, z
let max-wealth max [wealth] of turtles- l* G$ i9 k0 M& }
let min-wealth min [wealth] of turtles k9 p& s3 j7 u
if (wealth <= max-wealth / 3)
1 H( O& A" [: B5 A) H+ _ [set wealth wealth + Low-income-protection ]
9 w0 C. ]0 s% M9 s/ G0 Hend
* n) e9 a4 m* N. [. k- X- t
' x& v/ }: [4 x, b' B% k8 nto recolor-turtles8 Y- ]8 E% T8 Y4 [) P0 ~
let max-wealth max [wealth] of turtles9 [& |. q9 g' E) J) P& }4 ?. ]
ask turtles5 j1 g8 Z. [( Q# c7 w# B* P
[ ifelse (wealth <= max-wealth / 3). U2 d* B6 e4 p7 [4 p7 ^ V% T* E+ c
[ set color red ]" M) T' h+ `% D8 D; O# Q
[ ifelse (wealth <= (max-wealth * 2 / 3))( U2 G2 q; F1 C/ A; p @4 @* D" v
[ set color yellow ]
5 `/ V( m; z* a' { [ set color green ] ] ]
A. n# t% L2 C3 X. a ask turtles [ifelse show-wealth?2 j9 h8 U3 }; G0 ?: A
[ set label wealth ]* B1 U2 j7 [( Q
[ set label "" ]]
2 E4 b8 ?2 M4 M9 [end
2 H& m6 f. ]/ E6 K+ x# `$ |. r) ]( Y( @8 }. B3 v; V6 l9 D) {
to go
8 V k5 v' u1 u" z# z; u ask turtles
. O1 N* S% i, x) t' r9 I [ turn-towards-grain ] ; L, l p+ A# {8 s
harvest+ E9 J4 V5 I t* G4 t* r
ask turtles( d9 r. x' L6 p6 \/ q/ K, H4 U
[ move-eat-age-die ]% T, m: F, |$ ~3 D9 i, }- v* a
recolor-turtles
0 o* i( u' i) t" \, ^8 I$ T7 i9 a if ticks mod grain-growth-interval = 08 B3 C( G# e. O3 a6 u
[ ask patches [ grow-grain ] ]- F* E7 L+ O4 ~9 a* I4 x- ?% ?; C$ E ~
: A4 ]: M* i2 M6 k8 k F6 s$ q# t
if ticks mod 11 = 0
: E1 d* j: [# H; t t [ask turtles
- v2 d5 p& Y# `: k5 M5 T' k1 S! a [ redistribution ]]
- E$ S; u" ~: E1 S) S if ticks mod 5 = 0
0 { V0 `0 k! v+ b5 U [ask turtles. V3 S- v6 U; ^7 |# J, S
[ visions ]]
& J/ H6 ]( Y' p3 [: | tick
! g0 p* ^& ^" l: \9 b update-plots: U9 d% u6 z" s$ y
end& g0 x, ^" }- C: S2 o" K
to visions
# \7 H- x/ d' e; {7 ~ set vision vision + 1 2 ?- z# g1 Q4 j% `2 B) H1 n+ m
end7 i9 f% j( [) z5 h
) C4 L! i) q9 d4 \. q0 x8 j8 n/ C/ i) d
! g ^7 @5 ^# g( U u
to turn-towards-grain * \# i6 }2 `8 S; L* G
set heading 0
: p6 [$ Q1 D0 ]: J' z8 X let best-direction 05 n5 W$ I' [6 I+ v7 \# P
let best-amount grain-ahead
0 h9 t" W! @) E set heading 90 q1 \* o6 N+ |7 s, d
if (grain-ahead > best-amount)
* x7 e: G; _& B6 [. E [ set best-direction 908 b R1 S: G" ~) h& T
set best-amount grain-ahead ]
/ z/ B' l2 j. i9 I! l) u; o, T set heading 180
: J" i9 I0 c" Z- I if (grain-ahead > best-amount)
) P4 c9 B9 {/ {& R. ]' L; C [ set best-direction 180
, O3 a' Y# B* J, | set best-amount grain-ahead ]! L, O- h9 I1 o& h; V8 K
set heading 270
* P5 o+ |6 ^1 k. ]1 {. I) ^ if (grain-ahead > best-amount)
6 E3 J- q. g/ u [ set best-direction 2709 E5 e. _ X) F$ z
set best-amount grain-ahead ]. K$ l: b+ J7 p! ?
set heading best-direction
5 M2 F# l! |) h( V. `3 Y* l" Fend
9 N. O: X2 |# E+ W4 f/ A+ |% e( f( X+ w5 B! g
' l: u1 j" V2 K& Lto-report grain-ahead _: Z7 d* P+ ?2 S) e
let total 0. n9 P' Z) i" P: U2 j# G$ y
let how-far 1
x. N" s3 L8 Z3 L$ a repeat vision
$ r/ \! {" ^% ]* r/ O+ i ` [ set total total + [grain-here] of patch-ahead how-far& l1 f7 i8 y) E. P: _( D" k1 `
set how-far how-far + 1 ]
7 g4 R8 Q' Z) k$ N$ W report total" n5 U) Q$ h8 i/ E4 V9 K$ X" y
end
2 Q5 n: Q5 C" o9 h7 B
- l. l' n% N& J8 J z6 s' Nto grow-grain
5 @9 ^7 i, _$ x, O* v if (grain-here < max-grain-here). z6 j& f4 _5 C' _" `
[ set grain-here grain-here + num-grain-grown
/ Q; y6 ^2 ?6 l6 b+ G, f1 K6 C3 \ if (grain-here > max-grain-here)
/ L; ?. S4 t& V [ set grain-here max-grain-here ]
9 ^/ S* |. }& i) o) K recolor-patch ]
& U1 D! ^+ y8 S1 N1 P! zend
, r' N. k. o& u( rto harvest5 N8 A1 i$ f5 O& v/ J6 S9 u3 y
ask turtles
5 y/ U. v. ]1 J% o [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]2 |5 z4 h! | c7 b* O7 h
ask turtles9 k+ [: I# H- Q9 x! V$ O
[ set grain-here 0
8 E1 T% J( \1 \* o3 J, e0 D/ T recolor-patch ]- D0 }; R8 c K/ ]; S" }' E
# b% m9 Z# G; s: w4 ^. B0 yend4 X0 x6 h' `: N* I- I& N% J8 J$ Y2 ~9 \
I) N& ^' ?8 K( e2 j7 L- Wto move-eat-age-die
/ f& i2 G# n8 O _1 V( i3 P fd 1
7 K" J# V6 f2 b- ?" m set wealth (wealth - metabolism)6 Y' p# [/ }: \& p
set age (age + 1)
" |+ ^0 s& D% t if (age >= life-expectancy)( U. o6 G/ C- g/ y* J
[ set-initial-turtle-vars-age ]
; W2 r) |3 |# F9 ?9 _ if (wealth < 0)
. H _; m3 v8 G$ l/ R! C [ set-initial-turtle-vars-wealth ]
4 b% F3 Y( B [( K* R 0 b$ N5 }0 F( w. G# \9 u
end5 b6 D% A# @( ~+ c
$ x! z' C F6 B/ A _& B
* V8 c; E( |6 tto setup-plots
t8 a& g: {# i* y2 m/ h$ X# G set-current-plot "Class Plot"
% ^/ d5 P& F% A set-plot-y-range 0 num-people. g* Y+ f$ k* j. w8 A
set-current-plot "Class Histogram"
) i1 k9 X7 J/ h set-plot-y-range 0 num-people
3 d0 I5 g# D5 s- g: _3 P1 k, l) fend" A2 q, e- L! f- X, Y
& R" O' A% }2 y, c2 zto update-plots2 h( B# L4 ]. [- q7 H
update-class-plot
; x, E2 b5 {8 o1 h# M update-class-histogram
$ s- f7 X" s7 k. c: x7 F5 r update-lorenz-and-gini-plots; U% ?5 c$ p G' s3 d% Z
end
) X- } C' F5 N1 P/ W2 @: x' T/ w7 W5 S
to update-class-plot; i8 W4 h. }- X! c
set-current-plot "Class Plot"! J% c8 ?) o6 F2 o! v/ K' H) {( c
set-current-plot-pen "low"
% W( c! \( u2 R4 h* ]" G plot count turtles with [color = red]9 M/ E6 N) T. e2 p
set-current-plot-pen "mid"
6 E& a" I- Z3 ?6 p plot count turtles with [color = yellow]3 W; f- k( U6 r. ^# ^' ^7 S* N
set-current-plot-pen "up"
2 l1 o4 G, }) L9 ]' V2 k plot count turtles with [color = green]. G$ I# k9 O1 ~/ \" h% V3 @
end
* X3 S+ d% Z1 P% J* d4 f0 _- |, ~% E: x% m U7 f
to update-class-histogram' c- O4 A# f5 \6 i
set-current-plot "Class Histogram", J' \5 U( Q5 E9 ~
plot-pen-reset. y0 j% q& r b5 W% R
set-plot-pen-color red
) |' W1 v1 p- t3 c4 ?8 W0 R plot count turtles with [color = red]
6 f) \# @4 Y; }: _ set-plot-pen-color yellow- H9 u2 i# H- D4 m/ B3 T3 S
plot count turtles with [color = yellow]
; F; Z; o, b" | set-plot-pen-color green# F1 ?4 A9 ?: @% F9 }
plot count turtles with [color = green]9 @' K4 R, X, K0 `* ~% \
end5 v, {7 y6 P8 H* O, [! O
to update-lorenz-and-gini-plots/ b2 [! ]; P* [: \
set-current-plot "Lorenz Curve", C5 |* G5 Z I! g$ Q- r
clear-plot" V0 o5 l+ L; F+ b7 |, Y3 y. Q) v6 r
# u) |3 Z; I: W* {# d( N C
set-current-plot-pen "equal"
. Y! n+ w/ [6 T9 N- q plot 0
) S+ R3 Z9 u! k( C0 ^0 Y plot 1009 x" P6 g8 e6 x3 @, g5 @
' V2 N6 Z& x# I0 }3 @" _
set-current-plot-pen "lorenz"' T! T) @& Q. i6 p' `8 W, w
set-plot-pen-interval 100 / num-people n6 D1 [; y% ^: C* b
plot 0
; I6 o( H; w- S' p
# ^9 a& G! Y. k let sorted-wealths sort [wealth] of turtles! s X8 r: q L. R4 c8 u6 S
let total-wealth sum sorted-wealths+ M( Y9 c! ^9 y" @8 T* |1 f
let wealth-sum-so-far 0; o; E/ v( n/ s8 M" F5 b" M. I
let index 0
$ J r6 l- p. I) V: O& D7 P2 S let gini-index-reserve 0
. e# w0 h# g, q& N: T( j
% _4 o+ i: e: F& Z6 l5 q: g8 Y repeat num-people [
( B1 q8 F9 T# z5 F* h set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)+ N( `9 N0 Z% {% q# {% ^
plot (wealth-sum-so-far / total-wealth) * 100, P9 ^4 x* w/ \4 D* a
set index (index + 1)
% ~0 ]: Q8 l+ D8 L& \/ \ set gini-index-reserve
) U2 L. l0 J9 i# j4 S: ?1 I gini-index-reserve +
! I" r E) H" E2 T (index / num-people) -/ }( A. p9 |1 @. B9 W. f
(wealth-sum-so-far / total-wealth)5 Y; u3 N# X+ i" l
], k* p" z+ S7 G) D4 j/ z5 S+ j4 V* f
# D5 C: U+ h- u, L
set-current-plot "Gini-Index v. Time"
/ R9 L$ Q0 L y: ]! g7 \, D plot (gini-index-reserve / num-people) / area-of-equality-triangle
) H: S! r0 ^7 g+ L. t& n( }end
$ u+ M; j* C6 P% b+ B. Vto-report area-of-equality-triangle7 G! ?4 i) f9 L- t4 p" Z+ M
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)" O9 w6 B: H3 v4 j
end |