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
& T- c: M6 t" Q7 c; C9 m6 n9 {globals
2 Y2 Q6 D; u/ W' T" y[
/ G- L% a( f- |0 _- q max-grain
2 G+ O- f/ Z- V- d3 C& Q% Q2 G6 m5 p4 J* x! x& v \3 C3 {( X
]3 f2 N: Q8 u \ D, ~) y) l( h
( w% z7 Z' P' J; b; j) X
patches-own
, k8 Z2 |& u% P9 g5 o. p0 a[5 [! C/ B7 T. ]
grain-here ' @. N0 j# X. l- r; X
max-grain-here
% }: U: W% g: F* ~' D- Z]
! \( S5 |) \0 D5 \- e9 X0 J# ]4 v# {) d. E8 C- B' ]
turtles-own. O% v% X8 P7 F% O! H' L: y
[2 V6 r& `) J7 X/ S+ D! d* X9 ^
age
5 u3 }- A$ ?, O3 j; h% R wealth , O# K3 O5 ?1 D7 L0 I- p# n! S
life-expectancy
6 V* @7 N+ P. v0 }4 Q3 g8 m metabolism 5 I/ }4 I. p% n, @
vision; P# x g3 r2 N5 x- L1 o( Y; ]
inherited 7 D5 Q7 f# m" Z; L: a! W
]
' X* f3 v+ M6 e6 L/ Z: e; k- r0 G- l$ Z: @5 A! k+ F+ ]2 K
7 Q- r7 i9 F4 F! F; Zto setup0 `% _% D2 W. X4 \
ca4 h7 w: F" _- o" ^1 ]
set max-grain 501 Y+ D4 W3 Q+ ?1 g
setup-patches. j2 d% N9 g8 b+ N1 A8 p5 R
setup-turtles' O' s9 w9 N* v! w8 v4 ^( q2 r& k
setup-plots2 z9 q r, t# Z) o
update-plots
- y: s) Z: w" u( @end
, F u* U& x+ I! ato setup-patches
- |7 ]( k- A O& |3 ^1 e ask patches
* D9 v7 z, @5 I* [: R [ set max-grain-here 0
0 V8 G" q) j( |0 C5 L if (random-float 100.0) <= percent-best-land
: @) C7 w* S* T4 ~4 i, S [ set max-grain-here max-grain
- ]+ N4 A% }' Z% E" V8 J, x/ ^6 |$ l set grain-here max-grain-here ] ]
# Y& @5 o* m; s) `7 o/ R repeat 5- U0 g8 z' s4 `* w
[ ask patches with [max-grain-here != 0]( ~. N4 w* l3 G6 {4 t+ x1 p
[ set grain-here max-grain-here ]! y% t# ^5 C0 W5 S& u9 S6 z& K
diffuse grain-here 0.5 ]
! f$ a# D+ R+ X5 \7 M repeat 10; J: `) h; a5 o6 e, F5 q9 \
[ diffuse grain-here 0.5] $ y! q; L1 B# j! }. |4 Q5 p" ~1 Y, E7 g
ask patches
7 M! f% j3 a, E7 G [ set grain-here floor grain-here * h# p& X, j$ t8 U. K7 C; A
set max-grain-here grain-here
! q: L& k$ Z6 j/ m' ` L recolor-patch ]
2 t+ Z6 p) ^9 J- Bend9 {* l' g2 y6 [$ Q1 p
to recolor-patch " ]) [" f7 R. L+ E
set pcolor scale-color sky grain-here 0 max-grain, h3 v/ e. t2 R- y) k
end
3 t. h# u+ f, w/ ^/ ato setup-turtles
, v5 q! f. n6 A6 B5 ]& Z set-default-shape turtles "person" [( P+ v% {! \/ P$ J9 [5 D" e
crt num-people0 n( D2 ]: q# m0 C
[ move-to one-of patches
- M3 u& d* p7 Y$ d* k* ~: H set size 1.5 ( A0 i* {* z; a0 w+ r) j6 V* j
set-initial-turtle-vars-age6 b. p( Q( t# E7 x3 S. _) C% Z H# x
set-initial-turtle-vars-wealth
/ U9 I5 E8 m, v" }% h- e set age random life-expectancy ]7 O$ A4 w0 K k& X% J
recolor-turtles7 s, f' h& d3 v' l5 n* L
end
0 c4 ^: P7 h# P$ o) ?. @8 y8 v6 S$ V, W
to set-initial-turtle-vars-age
7 w3 |6 m- H# W4 Y1 c/ p0 w let max-wealth max [wealth] of turtles% W* s7 T0 Q. ^9 [9 u
# B" E( S4 o0 W9 O3 Z8 D2 z8 f ifelse (wealth <= max-wealth / 3)
4 [. k: ~2 ^' G+ q1 h, K/ } [ set color red ( [6 p$ Y3 ~7 ~" t* H% b& N) `
set age 0
: ?3 n9 v" S' B! S }+ b face one-of neighbors4
, V1 [/ Z4 P! j- Z8 r set life-expectancy life-expectancy-min +
0 v5 \ s' ~5 O$ H random life-expectancy-max
5 d" c4 w; Y7 u3 y% \ set metabolism random 1 + metabolism-low% m2 P6 z$ N, Z) K0 K' ~2 p3 X5 ^3 U/ q
set wealth metabolism + random 30
) @8 N. }6 c- D1 J0 H3 \7 C5 [ set vision 1 + random max-vision/ K- ?+ H' T! p
set wealth wealth + Wealth-inherited-low ]
, ]1 W: N/ R) V, o8 o [ ifelse (wealth <= (max-wealth * 2 / 3))
* |* a& j- W1 h5 F- b [ set color yellow
$ z0 v+ o4 p3 n/ C! ~; E% \: f set age 0
' S6 t W" `- a face one-of neighbors4
7 r+ }# }: i1 x) f# C1 | set life-expectancy life-expectancy-min +
$ x0 R, m% q6 u% ~: T' [' M random life-expectancy-max + 1( j9 y# D9 Z7 _7 g6 H) W {
set metabolism 1 + random metabolism-mid Z9 S8 V( }+ o2 `) p
set wealth metabolism + random 303 d5 I2 K3 l0 m: c7 g! V
set vision 3 + random max-vision
1 j0 a7 m$ d- T7 y7 m; L0 \3 ` set wealth wealth + Wealth-inherited-mid]
+ ]! S6 Q* w! Z D' w( j [ set color green
2 F# }0 _' L9 \/ Q) y+ F' ~ set age 0
- c% l, R/ ^: N i$ d face one-of neighbors4
x7 y/ q6 y6 ]# S! ^6 f/ { set life-expectancy life-expectancy-min +
& \' K) B! h$ o random life-expectancy-max + 2- }: i7 x% _0 C. n
set metabolism 2 + random metabolism-up
2 [2 I% S( s$ M: a/ F set wealth metabolism + random 30: n5 A8 v) c$ L$ E4 ]
set vision 3 + random max-vision
. r" |9 l1 w/ ?, O3 y, B set wealth wealth + Wealth-inherited-up ] ]
# T" Y9 v! T+ o
# {$ U: K0 J8 P% I, L1 }end* N. g) i! @0 c, ~7 |; o8 n1 I
to set-initial-turtle-vars-wealth
) A& {: \8 ^7 g$ ^3 \ let max-wealth max [wealth] of turtles* G N) `0 G& }* V6 U- l6 N& _) l# J
set age 0% ]3 O; i" Y! j9 i
face one-of neighbors4
+ G$ |8 s% q( S3 |1 a set life-expectancy life-expectancy-min +7 s3 X+ h5 u8 V& c0 A" L
random life-expectancy-max 0 X9 l2 U; w) T/ I+ {
set metabolism 1 + random metabolism-up
. [4 t" `/ ?# { Q& _ [% }4 j* [ set wealth metabolism + random 30
. i; v, a0 H4 K5 ?$ `8 o4 B& _ p set vision 1 + random max-vision . p& G3 S$ v; k' i3 k
end
( |/ W: \% T3 H0 P; bto redistribution4 M2 v+ B. e! ~+ S: r
let max-wealth max [wealth] of turtles9 J; K9 f8 b' j
let min-wealth min [wealth] of turtles" u! Y1 ?5 B* ]6 ]) [
if (wealth <= max-wealth / 3)
3 d6 l' h8 L+ a7 f' m: t [set wealth wealth + Low-income-protection ]
& D) k* B: s4 U! y" Eend
# U: ?' x V) D( X* V% ] 4 f6 f8 E$ {! r* K
to recolor-turtles" V% V' C$ ~, B
let max-wealth max [wealth] of turtles" s ]/ k# a; ^ O+ {) K
ask turtles
& B2 S, y0 J8 j, d4 Y4 A [ ifelse (wealth <= max-wealth / 3)
9 I: M* f+ q5 @. u1 D0 Z [ set color red ]
0 m+ H* @* e3 j6 m9 y; v- R/ F/ q [ ifelse (wealth <= (max-wealth * 2 / 3))' y8 s; D% X! {5 t8 B
[ set color yellow ]/ ^: n& b) G( V7 Z* r# F& N
[ set color green ] ] ]# y& n$ R0 X# B' n9 e4 X
ask turtles [ifelse show-wealth?, X9 k4 Y9 I* J
[ set label wealth ]: p7 B4 d3 g0 @% A: k3 J: I
[ set label "" ]]! M) o' x0 p0 E# B4 @, h$ W/ I
end
! S* `2 ^( Z1 S" Y; s% [# o8 M
: U0 A! S( Y9 u- ]to go
2 _8 U* U8 y% Q" B, Y7 n ask turtles
& H! z4 p$ G; T% { [ turn-towards-grain ] 9 l* j) f( a) i" x
harvest
/ z7 z x; W" B. v ask turtles
6 F; C1 k p- y' p [ move-eat-age-die ]
& O' g* L; S$ p7 } recolor-turtles6 _, M7 l& \- }' |+ N
if ticks mod grain-growth-interval = 09 q+ x6 D7 s* U3 v; B
[ ask patches [ grow-grain ] ]
( H7 t' E1 q0 k$ `; F- r' A+ |! ~
; A# i4 w, j- W+ H3 N if ticks mod 11 = 08 ?7 v, h9 C1 @
[ask turtles
2 z- S* z( x E2 M# I [ redistribution ]]/ }& c! [/ B. g/ ~$ A/ k
if ticks mod 5 = 0- z/ X( ?; s3 ]7 T. ^* Q
[ask turtles
, o- q% a, X* F x9 c [ visions ]]3 K( [# C' A4 c! [9 n: o% v
tick
, d' ?" J+ C" b$ B3 n" Q, j update-plots
3 ~5 V3 z* @) `1 Xend* h# N; K, V% d- ~2 B
to visions7 Z7 L+ y$ o7 V I
set vision vision + 1
6 ~3 r) H, r+ T6 @! x+ oend. R$ v* \5 V% \( K0 p/ M
! {! V! S" y4 w Y5 T; X
/ Q' \! q1 K2 _# h1 i
+ x) g8 q% P, l. Ito turn-towards-grain
8 Y0 r% e$ I. a- `. w set heading 0& Z/ \# ?( b" b* S$ R
let best-direction 0
3 Q" N2 s3 F( I+ W. ] let best-amount grain-ahead
' O, R- Y3 X& J8 m F: Z8 i set heading 90% K- ]) H9 L7 S5 f
if (grain-ahead > best-amount)8 M+ |! E7 b5 C e% n0 J* k
[ set best-direction 90
0 x7 E/ n# C* g set best-amount grain-ahead ]
9 B8 m& M) h3 i set heading 180
7 j7 H" a7 d( C+ t- E4 A% ? if (grain-ahead > best-amount)
" w1 C8 S. R3 W0 X [ set best-direction 1807 c! j6 f: Q( V9 k
set best-amount grain-ahead ]9 e4 k4 U8 H3 t2 D
set heading 270
9 t7 h7 y! @1 @6 V! O if (grain-ahead > best-amount)$ l0 |$ m+ c1 j/ m% c( A
[ set best-direction 270
z# w. Q9 i) C6 X set best-amount grain-ahead ]1 T& w/ j9 i( f% i
set heading best-direction
. u$ J$ [% n2 ^" C! Uend
. d+ G$ x: g' v3 u+ E9 R }( K4 Q) U1 E* ^8 s# S1 R/ ~* I" K
7 H( _5 I3 A1 d7 n( b( O$ q
to-report grain-ahead
( F5 m2 X* b5 ~! H# x1 A let total 0! {1 J5 X# D" |8 k2 u
let how-far 1/ u( q, }3 ^2 I2 z' d+ D2 P
repeat vision
- I" b* o4 H8 @( F4 \ [ set total total + [grain-here] of patch-ahead how-far& D, ?' z/ v* b0 Z' h
set how-far how-far + 1 ]0 m8 y9 a* o! c, _6 D! c
report total
7 i& |% ~; O. F( Hend
5 B5 m" m9 u/ y3 M' q V+ K5 O! `
3 G! ~! P' [9 d* @+ D bto grow-grain : q; o' d7 t7 c* i' s! I. Q* s4 E# P
if (grain-here < max-grain-here)
# G7 @/ n2 i; w t [ set grain-here grain-here + num-grain-grown
9 f* t: B3 ]9 e if (grain-here > max-grain-here) ! G4 ]9 d. @$ N: J, L! d4 m6 @
[ set grain-here max-grain-here ]
; R3 p- S% a% u2 ] recolor-patch ]
: n7 U; M/ y+ P' m* ?* `0 Hend
3 u% L z- \5 L3 Q/ I Pto harvest
3 t! C3 I% D) `8 o2 |( ~ ask turtles
3 l- F$ V% `- W8 L [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]4 \% ~- R: c7 t) V5 z
ask turtles& k) q& K6 w$ i7 \# D% I, I2 Q
[ set grain-here 0
] Y+ b6 ]' g! a1 N" @' q recolor-patch ]& y; n. w7 l) I. l/ m3 m) R
! D/ n; e. d3 {* @3 [6 L1 B. `
end. Z8 X9 R4 \- h# {
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to move-eat-age-die - t1 |% `' ?+ b& M
fd 1
! L& U) U9 r% Q! V set wealth (wealth - metabolism)1 f& B% e5 R1 C( j7 r
set age (age + 1)
% a( V4 G( N" Z/ @ if (age >= life-expectancy)# J* H' q! i: a; Z; n
[ set-initial-turtle-vars-age ]+ o5 C& b- |1 Z& Z, D' e+ g5 C
if (wealth < 0)& x. Z7 q3 F: g v O, ^: z
[ set-initial-turtle-vars-wealth ]
4 @# R9 d1 r( D" ~; K + F% P$ O3 Y5 d
end- E! b/ X. j9 H4 Q; u& |* m
1 |, a9 F6 D; d3 f
* @& e2 z" s: k; ito setup-plots
( }0 D+ _1 e; x: [# n' e: M! W# g set-current-plot "Class Plot"
9 o; E* E# P. G+ ]2 T' D- G set-plot-y-range 0 num-people
3 M: a o0 m1 u% p& h0 P3 e set-current-plot "Class Histogram" n. `' K' ^3 {$ i
set-plot-y-range 0 num-people
2 a% \* ? x7 \. Wend! r1 x9 x8 K) I3 z4 D
8 f/ s: z$ ?% ~6 D
to update-plots+ ?9 @( a- ?) ~! n4 s$ {: o* I
update-class-plot
! z, |7 s" |9 j2 _* A- G' u2 p update-class-histogram/ ? R) X$ Q5 D4 F6 O
update-lorenz-and-gini-plots% F. V S# P' I/ ^, X( ?7 Y. G
end
& W. G3 k M( s, `0 q
9 ^/ b% n) K1 L9 Z4 g1 ~to update-class-plot
% ~' i! f5 d$ n, e" j3 h' G1 Z set-current-plot "Class Plot"
1 E' h7 a% Y* A2 e* j+ {9 ~ set-current-plot-pen "low"' f B( N9 C) k6 M1 |' M
plot count turtles with [color = red]
% y- i" T5 d# F* [: e6 s# p2 S% m5 O set-current-plot-pen "mid"3 V8 M& [$ s# z' W
plot count turtles with [color = yellow]
" l+ P/ V' Y: o/ ?3 l& h set-current-plot-pen "up"0 g$ P$ S A1 E: Y7 A! y6 ]! b
plot count turtles with [color = green]! H1 I n Q4 L) w
end5 c! g! @' ?$ z2 D& Y
$ w& v% d, }- p7 W5 \
to update-class-histogram) L% ?; g2 ?5 [( Z
set-current-plot "Class Histogram"
8 J& X% A/ H; |( M plot-pen-reset2 E) [6 L/ A/ B# b) ?& ]0 i
set-plot-pen-color red7 s& V2 o/ k! X q
plot count turtles with [color = red]$ c% Z/ Z1 J1 k
set-plot-pen-color yellow
% ? Y' n+ g: L% q plot count turtles with [color = yellow]7 a+ G K5 B7 a1 m3 @" T4 c
set-plot-pen-color green: m# g* G5 T) w( r+ Y, @
plot count turtles with [color = green]
3 s$ @1 X3 [% m; o# e* Fend
) \* ?2 _1 }7 z( R. }to update-lorenz-and-gini-plots" F4 U' r7 @& N3 N
set-current-plot "Lorenz Curve"
: K R9 e' ~& G" M clear-plot
7 X# }4 L/ l. ]3 a m( D7 @3 @ h- D+ s: r0 o
set-current-plot-pen "equal"
9 T* I" j0 Y3 L, F4 F0 }6 R o; @ plot 0
* l6 y7 q0 G3 u1 q8 \7 ]; w0 u% ]) g plot 100
* N7 p* c, ^9 c- E1 y$ Z. L4 N# x0 [
set-current-plot-pen "lorenz"
- ]7 ], L1 q: D set-plot-pen-interval 100 / num-people; F4 o4 D$ t9 ~
plot 0
4 {7 F9 |* A8 {3 x# C; h( H. X/ E2 [' I5 p
let sorted-wealths sort [wealth] of turtles
. T6 R: H1 u( P7 e let total-wealth sum sorted-wealths& v* @9 _6 ]2 J5 w" i6 A
let wealth-sum-so-far 0
2 R7 w1 Q1 H; L% A/ C8 A3 I) e8 S4 P let index 0
$ K/ h7 ^0 X0 X. a let gini-index-reserve 0
# a C( E# Y' F# I4 [2 U4 w C7 K! d) f' X
repeat num-people [. U% d7 o5 X4 d5 T6 z; _
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
* n$ z+ \6 J; L: @' K w- ? plot (wealth-sum-so-far / total-wealth) * 1001 d; |5 s1 @4 k% k* ]
set index (index + 1)
7 K0 ^; X! E, v0 h% o6 ~ set gini-index-reserve
1 N7 c$ I; Z; H! t gini-index-reserve +6 C& v3 N! O0 b+ h6 o$ b
(index / num-people) -
f( C1 g- j( a. y1 _- E (wealth-sum-so-far / total-wealth)2 Y$ c$ y5 ]5 \7 Z
]! p( Z7 Z# h1 S4 k1 P% T- z
; f- P) c1 a ]) n2 N. L* {
set-current-plot "Gini-Index v. Time". d0 J: Z8 i" g/ U6 o, f
plot (gini-index-reserve / num-people) / area-of-equality-triangle3 a; d! u/ |# g4 O: g
end
& r1 X7 L$ Y! n8 Q' \to-report area-of-equality-triangle
* |( E4 w7 _$ s+ |2 [ report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
2 n9 y- y8 e7 V$ ^0 ^5 z+ yend |