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
% ]3 I) J0 d( A9 t3 X. }8 X# uglobals
" U* ]+ ^% |# e[
( o* n5 D" V. w! u max-grain
7 v3 K: R# D% ? i8 }
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1 D ?' y; }- P2 b
patches-own
4 D( n- z; [9 U. h3 D0 L+ D \[
! v& W% u. k# l) V& V; D4 n0 r grain-here
4 V, P2 N: m7 } max-grain-here
5 {. m# S$ M: N! W( f]+ p) ?6 p- W4 U% v* J7 d# k$ x
, I% c. O H# V! B
turtles-own
* e3 F9 b4 s4 F& {& _7 \[8 R1 j5 x) V9 E9 s) G5 i- O
age / q* K( U9 B k8 j. r$ y
wealth
4 s' M# Y9 A, N; j# \6 V# d3 X life-expectancy 4 [6 f" e" r' _/ d e+ A E) Q
metabolism
3 [0 w+ n Q: I vision
+ k5 W, A. {- J6 S inherited 2 ~8 V" M7 x9 p' S( s0 O, l
]
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to setup3 b% `: w, i$ g
ca
8 j6 I' N) Q5 M3 s& U* @ set max-grain 509 G( `2 d' {( b# Q4 t8 a% m: ^; |
setup-patches4 E+ T# w% B( m U
setup-turtles
* V5 y5 X, K6 K" H* m setup-plots
* R+ c O% i* R, k2 Y: D3 X update-plots3 l0 W( p# e7 ?
end
, ^! _& ?8 v z0 E- ?to setup-patches
9 ~+ f* a' [# o9 B) E ask patches
, C5 H# M- Q" I3 r' r [ set max-grain-here 0
/ D- Q4 ?7 Q3 X0 G& f if (random-float 100.0) <= percent-best-land( K$ R, ?! R2 A) X8 l! w0 ]
[ set max-grain-here max-grain- {" C1 c T: V2 ?. t5 s9 B0 j
set grain-here max-grain-here ] ]. }% a- l M4 {: a! J
repeat 53 S7 x4 V9 o& o! q S/ e# w
[ ask patches with [max-grain-here != 0]- O2 ]. p$ {- p7 L! R6 @2 z p, W* q, f
[ set grain-here max-grain-here ] x4 F L! j; o8 ], k
diffuse grain-here 0.5 ]# A& R B& L; `- C7 V4 W( R
repeat 10: m' O5 u) R' o3 L3 V) u
[ diffuse grain-here 0.5] 9 `+ F2 c( |$ ~3 d: S. e
ask patches3 o. Q- q4 o& y3 a7 M
[ set grain-here floor grain-here
& M8 C! M" k1 a+ e& n set max-grain-here grain-here
# ^2 f% D& v8 ~% I' k( F recolor-patch ]9 {& C y. L; F; r) V/ I N/ Y# t
end4 ^! ?$ `' H$ `5 }2 ]# _; B6 d
to recolor-patch 9 S, a1 `% T3 @/ j9 U
set pcolor scale-color sky grain-here 0 max-grain. n+ K" k! g7 P9 H; i8 e
end
( u, P5 D' g/ A/ E+ p, S& ^, ?to setup-turtles% d- _ Q* \4 D/ O, {
set-default-shape turtles "person"
8 j+ I# o. {# i6 H crt num-people
& x& ^% T: ]; U5 S5 L9 g3 d7 R [ move-to one-of patches - T- P* J6 n _' Q0 |
set size 1.5
0 v8 Y4 |3 l6 K4 f0 ~) A0 c set-initial-turtle-vars-age
7 G& J$ w( l' q3 `7 U- ?2 d4 k set-initial-turtle-vars-wealth
0 o: ]& U* A; h$ x: J8 b set age random life-expectancy ]+ q9 T5 z* U& N" D4 W
recolor-turtles
; Q( i E1 U( c* z# f4 jend6 Y/ b- O @( M5 d# u: Q9 I
7 G+ e' D2 C' J0 _; w( t5 bto set-initial-turtle-vars-age
: \) P2 F C& W! i# U& g let max-wealth max [wealth] of turtles' _+ H7 \3 \+ W* S
9 A# A1 H: i& \0 V9 m7 a ifelse (wealth <= max-wealth / 3)
1 c' \4 c. T7 N; }' w [ set color red
5 ]' W( w. K( i0 s7 g! j; s set age 0; _! i. J2 L" z. g8 G/ y
face one-of neighbors4 : w; m* ^: o/ G
set life-expectancy life-expectancy-min +4 @; n/ @. [4 k: Y% ^% v
random life-expectancy-max $ U0 v2 X: i7 Z' U7 _
set metabolism random 1 + metabolism-low. }: Y; J. Z# _; r( l' c
set wealth metabolism + random 30 u* b6 \% \7 g
set vision 1 + random max-vision
2 W# x- T) a, c0 E3 s% V set wealth wealth + Wealth-inherited-low ]/ N3 q: n+ L3 @& B5 [
[ ifelse (wealth <= (max-wealth * 2 / 3))
6 {/ _7 u5 ~8 j1 m9 G+ q5 y- `4 g [ set color yellow * \) a. Z+ O2 p: `$ N- E) n& a2 x
set age 0
3 c3 L5 I c3 a7 ^ face one-of neighbors4
( |# u* z( Q9 r& k$ x set life-expectancy life-expectancy-min +
9 o/ Y0 D$ e2 _" t5 a random life-expectancy-max + 1" y9 S6 o* Y% T- \$ u3 M+ P
set metabolism 1 + random metabolism-mid
8 w4 G) o2 Y* u* v- ^( T1 v set wealth metabolism + random 300 }* T: l; \8 y; P
set vision 3 + random max-vision
5 R, s3 g7 @- K' h# v set wealth wealth + Wealth-inherited-mid]- W( q9 f2 _" @$ u1 Q# F
[ set color green
/ v8 d- f' T; t( b set age 0 X* m5 G" q( [3 J
face one-of neighbors4
) v1 z. g# g3 o p+ u1 O9 ? set life-expectancy life-expectancy-min +/ R( D2 b, C7 \/ J
random life-expectancy-max + 2
6 p9 @3 C# R* P set metabolism 2 + random metabolism-up
& B! J$ a+ a9 L' w# n set wealth metabolism + random 30
1 _5 B5 g4 H' y6 O set vision 3 + random max-vision0 N1 F. |6 ^' e9 o
set wealth wealth + Wealth-inherited-up ] ]
0 Z/ B3 ~4 L/ J2 M7 n7 }+ Q C/ W4 i3 W/ F, \
end
" m) E) S) s+ H) \to set-initial-turtle-vars-wealth; I3 S1 }- S" E( t q9 G2 z# r
let max-wealth max [wealth] of turtles
2 ~ v# w- U2 N! |5 `3 l set age 0, Q+ [; }5 v4 l0 t. \# _6 o" k6 U5 P
face one-of neighbors4 s% k& \4 c" r
set life-expectancy life-expectancy-min +
( Y! G% e* @( o; J) s: S; _ random life-expectancy-max * \* B5 x0 p% x! b$ o3 x
set metabolism 1 + random metabolism-up( _0 Y" a8 u" w6 I7 }5 I! J
set wealth metabolism + random 305 W' }& q' q! R
set vision 1 + random max-vision 8 `7 y; p' d, Y" ]- E
end7 d% V1 W b7 o* E$ \) ~7 d
to redistribution
4 c' k5 _; I/ J' C+ F* i/ a( V+ Jlet max-wealth max [wealth] of turtles
/ r4 b& u8 I) e5 v3 glet min-wealth min [wealth] of turtles
0 C* Z* l: r/ d$ ?8 w1 Y5 Dif (wealth <= max-wealth / 3)* u: }' E) @1 d+ _' Y* R
[set wealth wealth + Low-income-protection ]! R& g0 i! }$ n& _% N
end
+ j. F$ Z0 w# I$ s; s1 S ! i0 Z/ N. A- t: W' g
to recolor-turtles" d* d. Y3 m8 {1 ~; g
let max-wealth max [wealth] of turtles L. E8 y7 R* T" H2 D
ask turtles6 ]6 p7 a0 I; s
[ ifelse (wealth <= max-wealth / 3)& [- h3 r, C$ r. m6 c0 ~; m( L
[ set color red ]$ l: z$ F1 n# }3 c% ^* _
[ ifelse (wealth <= (max-wealth * 2 / 3)) U& C# l: N' G5 x
[ set color yellow ]
$ }$ ]* B: F. i [ set color green ] ] ]
! r6 l0 k; W9 A. V ask turtles [ifelse show-wealth?7 k! i3 E, b. }5 J5 c- I
[ set label wealth ]% _5 b6 r8 ~# s5 z" Z6 L% t
[ set label "" ]]/ [8 l) d5 G3 {% \2 e
end: P7 l5 K! e) e! w
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to go, a' D/ q# @" F& v) ]4 Z. A
ask turtles2 w% l$ x+ Z; ` P
[ turn-towards-grain ] 0 C2 f- @$ z4 K+ z
harvest
* ]8 |8 t& @( C% z. ^. t: \ X ask turtles
# e0 i$ s K* Z) Q$ Y: m [ move-eat-age-die ], J5 ~/ ` p i; r3 G
recolor-turtles
, R: m% e- {. X" w4 P; E6 P if ticks mod grain-growth-interval = 06 W- U8 z% R) i, f' n) K, P! Y
[ ask patches [ grow-grain ] ]
2 {% ]5 ?+ {; K ( @$ R1 K# K! w1 p3 s
if ticks mod 11 = 0& ?+ U3 ?0 k* p {+ k& X
[ask turtles
5 q" l( F' n" A+ `/ n4 _ [ redistribution ]]
' H% ~/ Z' D7 Q3 }" B if ticks mod 5 = 0$ X. G/ z- E _3 C
[ask turtles
% f6 B7 o0 c& a) m/ Z' \ [ visions ]]% m- _! q0 A) x7 R& Q: d: ]
tick3 y* b& r+ j7 |: T- l& _( b
update-plots
3 W3 ~3 K& r* v6 i8 R( Jend
+ g8 P; g. q6 i/ e. P) Lto visions
% w! ]4 V m( S; I. I set vision vision + 1
9 U. w3 ^) x( `0 Oend. P0 m; k ?, V
$ q) L. {8 f7 m% M
8 S9 S! B0 L9 k; d4 Y& W( H# j- `5 v. i1 H& i5 u
to turn-towards-grain " C Z: F4 v. C& F, ~! ^- P
set heading 0& z* O1 |5 @! n$ I( t. u/ C& _
let best-direction 05 A8 h J( Y$ @9 y2 X9 h
let best-amount grain-ahead) o+ }0 X& Q2 Z/ ]. p E
set heading 90
/ q% ~; V& @. b B, g if (grain-ahead > best-amount)( p& k" G8 r! |& o( M0 ?3 `" m: l
[ set best-direction 90
& ?! T1 E# ]: t' u5 w7 X" @& \# C set best-amount grain-ahead ]
- N9 }/ H- A2 {) u& ]/ U set heading 180
+ I; b( V# o0 A8 S H" U$ k% z5 L if (grain-ahead > best-amount)
+ ]* B1 p' o; n4 y7 [% b7 G9 j [ set best-direction 180" F" L/ P3 t* n6 [0 y7 `! S
set best-amount grain-ahead ]
+ _! V, Q: s8 t/ v5 J+ y. v5 Z' j set heading 270
% Y2 }8 B! e3 o3 X: T$ \ if (grain-ahead > best-amount)
- g. q- V$ y2 R$ k* O [ set best-direction 2705 O" r. _% r' ~2 f" K
set best-amount grain-ahead ]% i' a- g# F$ l
set heading best-direction
. `* e: R8 @# D7 Fend1 D# y3 j& A, s7 p6 H
3 e1 Y4 s+ o3 |- g
: i, x! o8 Y k4 ?+ Dto-report grain-ahead
0 x/ z9 F% r: `# y let total 0
4 E( m) [# V9 D2 k7 b let how-far 1
1 t9 K* j$ F; S repeat vision% f, I' v, E+ b' i6 X' t+ V
[ set total total + [grain-here] of patch-ahead how-far
! |" ?: c+ N2 A) \7 i/ u set how-far how-far + 1 ]2 [+ g* ^7 o Q: [" }: K5 ^
report total
/ b _6 h4 U/ @9 B" p( a& cend
' n$ @3 g. Z) i2 B& V& }
k$ j, P" F, k) y: E0 }0 S9 mto grow-grain
( ~4 R2 a. g D9 {2 q: X! d if (grain-here < max-grain-here)
4 t' B) @( L" U8 G8 J [ set grain-here grain-here + num-grain-grown
; Q1 m, J( `1 H& m4 D if (grain-here > max-grain-here) # s L2 ?/ l! B6 }8 p0 z
[ set grain-here max-grain-here ]
9 x; \! Y8 y6 W$ b2 f8 ^0 D recolor-patch ]
! `6 N" X& d, ^! Fend# c& B/ }5 G3 W% B2 Z2 R9 t
to harvest
' z6 ]& `2 Q$ V! p, q ask turtles
. Y/ m0 ]) Y2 u0 Z o. G [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
/ y& c4 }% j% X ask turtles
, I' H0 P: M, J. {" z5 n; h [ set grain-here 0
# ] w' S2 }/ n% d0 W recolor-patch ]
9 Z' y2 m. O: ~7 L6 w; ]0 V) { 8 ~% j* b# S; H) l( c' k
end
7 r/ {& j3 g/ f+ E& h' @' ~0 Q- B$ b, x
to move-eat-age-die
& R( j+ P; j3 |( T fd 1& K$ Z9 X, o$ a+ K3 z+ G
set wealth (wealth - metabolism)8 O2 d" ]9 }1 T3 g6 _) x1 q
set age (age + 1)8 W3 M( P4 \8 v/ ]3 g* m e$ t( C
if (age >= life-expectancy)
2 p& x' L; {% h. W) O$ N [ set-initial-turtle-vars-age ]9 D$ F" c+ S3 X+ `2 l
if (wealth < 0)5 Y# _ v E$ d8 y1 @
[ set-initial-turtle-vars-wealth ]
3 k: U3 k! C4 l, y, ^( I+ W( Y l0 F1 l: @0 M
end" x* a# Y7 o- y) r9 x& ] L6 J
. q: j3 n4 X, l! l9 J% E, r8 {4 l. u \7 n4 X0 E
to setup-plots1 k) x; h! K' W, F% x
set-current-plot "Class Plot"
$ B" J% q# X# |* D+ f% j/ g% ~ set-plot-y-range 0 num-people0 L+ g' h* B) P% s7 R9 c ^6 {2 o0 y3 B
set-current-plot "Class Histogram"/ Z e! j6 D; b
set-plot-y-range 0 num-people( }) z% ]6 i6 v1 R4 `- G% Q
end
' c) i4 M. G9 G @ d. o
P6 d- ~9 R P9 u: T m0 pto update-plots) D/ i5 a3 U: U8 K7 l
update-class-plot% J$ C/ `9 x; f! K, @
update-class-histogram8 t8 X5 d: E3 h: y" \
update-lorenz-and-gini-plots: W+ o; |, b- Q6 m9 y! M
end
4 w+ z& k9 \$ O4 U6 K) J9 P
. d4 |9 `( \) n# \( Y8 Zto update-class-plot
3 l# V" y9 O9 V" h% C set-current-plot "Class Plot"* V) X2 C- t! w( n) u7 \
set-current-plot-pen "low". p5 j; _ x; ^6 [9 ?
plot count turtles with [color = red]
- L$ v$ Z; ?' t p* K set-current-plot-pen "mid"5 W9 d y2 [; {) K. r1 u! \ N
plot count turtles with [color = yellow]
3 j5 v& H( O- K1 h) I set-current-plot-pen "up"( i+ G& G' h. Q: g
plot count turtles with [color = green]# s/ G' j& @ }$ o
end' ^4 o6 @1 p& |) }) ]3 b# V
# b/ v5 ]& Y {+ h) d& F; W% Ato update-class-histogram
9 m* Z; a6 }: j5 i9 d* `. D6 R set-current-plot "Class Histogram"% @" P1 b, l I0 a) N9 o$ O
plot-pen-reset# x' t( {4 o( K* X: Y) x/ M
set-plot-pen-color red4 F9 p u1 |$ v
plot count turtles with [color = red]
0 O5 O$ X: B4 U5 _; [3 `' [ set-plot-pen-color yellow, a* i/ A( ^7 f" c% y }
plot count turtles with [color = yellow]# F3 _0 `9 \6 f
set-plot-pen-color green
4 ^+ r8 I- ] x plot count turtles with [color = green]
# _7 F% h0 W' E1 G5 lend0 s2 U R* {* g1 l
to update-lorenz-and-gini-plots
1 W& ^2 I' J" z. T' A7 T$ ] set-current-plot "Lorenz Curve"
( z" T6 k8 J* x J) S4 J7 t+ T) F clear-plot
* B! q) j; C9 S; K4 x/ Q1 y, n
- t( X! U( ^2 {) s0 S7 D; q set-current-plot-pen "equal": C% ^' q" q1 _. L: f
plot 0$ }3 r' h% \5 G# \9 ~& F5 G
plot 100
6 Y9 ?9 B/ Q; y* E! A/ q; n, o: l& T
+ [& B7 q+ k0 q( X0 n/ p) b set-current-plot-pen "lorenz") R$ ]. c5 {! i
set-plot-pen-interval 100 / num-people
& q) J5 x* Z* D5 C plot 0
/ O7 `! C- }* ~9 m: z1 O" a7 c# h3 m% W" i/ _/ N- X
let sorted-wealths sort [wealth] of turtles
5 [8 T, j3 e" ?1 h let total-wealth sum sorted-wealths& F$ o& V6 }- r3 j
let wealth-sum-so-far 0' N' ?" o6 p& C, Z- |# i" m
let index 0
5 i. i5 O: m, d let gini-index-reserve 0
1 j* v( V+ X) z7 m& N" Q- g
) t2 r, e# S1 N5 e- r repeat num-people [' @; z; k8 ?. x& J
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)7 i) f* n4 \& r, ^
plot (wealth-sum-so-far / total-wealth) * 100
# N5 Y9 a5 Z d+ a set index (index + 1)# Q6 F8 O& H; J% m5 H
set gini-index-reserve
- x& W9 q# J0 |# P# C* q) e gini-index-reserve +
- D+ [5 D/ ]+ j5 O (index / num-people) -
' l' r4 b& {1 T1 u (wealth-sum-so-far / total-wealth)
. |2 c7 p s6 D" c9 O! @ ]
2 I: u$ c: X. m/ U. l
* m) c& X Q& N" _5 H set-current-plot "Gini-Index v. Time"" @ x) n! _$ h& D- r( d+ M3 b- a
plot (gini-index-reserve / num-people) / area-of-equality-triangle' v% h9 M) v1 T: e3 Z: Q4 \
end! j/ A, L- y7 K/ L9 ]
to-report area-of-equality-triangle
' R4 ^" [. J; ^9 p report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
9 D/ s+ N k7 d' H3 O h" Zend |