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. F# b7 T/ a* f2 R
globals- D( b9 F# `) s4 ^. b8 }" r
[
- z1 P, |' F$ e( @/ |/ C max-grain
) ^* M7 ~" p+ O8 @+ y. D+ S- v# F L+ t2 S
]
* r1 P- L: s- c- j% i- W
8 r+ r8 L' C# _8 T4 Gpatches-own/ |- ]7 G$ T) r5 r4 l1 S* ?
[+ X0 L* O" [5 D. g, j
grain-here
& o. h/ R v* T9 G; _$ Z max-grain-here , e+ H- e' \. {+ G$ q$ e
]% n* X( z: Y5 M4 U y: d/ @
; \4 U8 ?2 r' l5 p+ \/ \) L; y0 D4 H
turtles-own) F, Z$ f, ~2 d" a6 j
[
; [/ T \: L; r, J: O; d age # ^3 A+ g( @3 H3 p3 o) x+ K
wealth
$ d0 H9 m0 z0 [! N# @8 x life-expectancy
3 u9 D5 |3 F3 R' A* X; f* j4 [, i5 n metabolism
# g* p: f. V2 |( C) C8 T vision9 t1 F$ K0 N0 |2 S
inherited $ V$ p- r, m0 a) Q+ V3 ~- T
]# \ N& V* }# E/ }
8 U- |3 L* H! i K1 G; F8 q+ `; a; I# F8 c( U! j1 X8 |8 _6 g
to setup8 w& a9 ~' l5 f5 g9 Q* X, U
ca
7 I2 K: s- J- _0 P set max-grain 508 ~" i2 A3 G6 k; H9 A- F- p$ c/ X
setup-patches
- T; v' D. f/ `4 Q6 i8 n3 ] setup-turtles7 y* C2 F9 W* _
setup-plots! p/ p4 k; _% O: B& u9 u: ^2 \/ n) s
update-plots0 b1 z$ E/ V8 w2 k3 y( T
end
W# B. H8 G( i9 G; jto setup-patches1 V. b, j/ z2 q# z
ask patches( M0 |" J! m D% i. _5 D
[ set max-grain-here 0( H) A. Z0 v% y- A3 @ t$ Z
if (random-float 100.0) <= percent-best-land" ~* U3 a8 i# a7 Y4 i$ Z
[ set max-grain-here max-grain3 x! Y7 g4 Q5 ]
set grain-here max-grain-here ] ]
6 [7 ]& n* Z: W" k repeat 5
8 ~4 d5 r$ c( U [ ask patches with [max-grain-here != 0]* }- |& B& S2 b& h
[ set grain-here max-grain-here ]
. s3 I# m1 v. v* M diffuse grain-here 0.5 ]2 e, N5 }7 D* A% W0 u1 ^
repeat 105 y6 I- x9 b1 `* R6 ?4 x# P' Y9 c9 ^
[ diffuse grain-here 0.5] ! ^% v. g- V) f! T0 b4 F- b
ask patches
! x3 ~" z D& \4 |2 v' L [ set grain-here floor grain-here 8 _- ^$ Y# O, T& O" h
set max-grain-here grain-here + c% p+ ?2 S, N1 R+ Q5 d+ V& y5 M# Z/ }
recolor-patch ]
) z# I/ l% Z% ^& F- W; R( i8 A: K2 xend; G# X. ~: N' I1 G; T% L
to recolor-patch T# Y( J+ l1 _$ J7 I4 p0 e
set pcolor scale-color sky grain-here 0 max-grain1 H$ y9 l( P4 v( K, B+ V* S8 a4 a
end+ O0 R# Z' ?: C
to setup-turtles
, y3 [; T+ p- Q- o. _' B set-default-shape turtles "person") E# B+ K/ c- [. I# o2 S
crt num-people
) _" ?$ Y* `3 O( r- ~ [ move-to one-of patches
. ?9 F4 W* y- @8 r; f set size 1.5
% `9 j& ?8 q$ V2 {% d" p8 Q& e set-initial-turtle-vars-age: }, d& w" Q8 N" P6 b
set-initial-turtle-vars-wealth
& N5 q0 c8 X! o* K3 A/ n set age random life-expectancy ]
, b" t* P, [4 a recolor-turtles
% T p+ e4 p* P% @* V. M( _# p8 M9 Xend
: w6 s+ ?1 I/ r* f
% B) S) O6 e/ }/ D( lto set-initial-turtle-vars-age7 T- l1 B) } k# L
let max-wealth max [wealth] of turtles
6 v$ D$ K+ A/ f; i
& W9 I1 T: m4 u) A! M7 U1 s$ u% k3 v ifelse (wealth <= max-wealth / 3): r( s' D9 F F% l
[ set color red # k" w0 q5 {9 b8 D; J+ h) \3 L
set age 0
6 E& O4 V& {/ K& W* ` face one-of neighbors4 - k* t( E+ a4 B' D
set life-expectancy life-expectancy-min +
; w# d) g, G- j& z random life-expectancy-max ! X f) z4 u; C9 w; t
set metabolism random 1 + metabolism-low
$ d; p2 ]2 a4 o, B9 F1 Z set wealth metabolism + random 30
) k/ m+ J; k+ K; N/ p* p% N8 K0 ^ set vision 1 + random max-vision
4 X% S. A7 Z. r( H set wealth wealth + Wealth-inherited-low ]
# z+ Y5 V* l" ]) o9 X' }# F [ ifelse (wealth <= (max-wealth * 2 / 3))- j! ~3 j2 Y4 U( ?6 E/ b
[ set color yellow
3 T5 W$ e" T' O0 }0 G set age 0
2 v( A5 _. d) J; d& K1 @ face one-of neighbors4
- i7 v1 d7 N- c+ l! l5 c$ I! J set life-expectancy life-expectancy-min +) D+ i# P1 I/ r2 _4 T, u3 N7 v
random life-expectancy-max + 18 p% q2 {7 }% i1 K& T- {( E/ e
set metabolism 1 + random metabolism-mid
) k" u/ O" V+ s# |$ K) J, E set wealth metabolism + random 302 S6 ^. u6 c" |7 b
set vision 3 + random max-vision
! @* F' \; b% x! K set wealth wealth + Wealth-inherited-mid]: E: Z. ?5 u6 E5 z) \4 H+ l
[ set color green 4 Y2 h! t; b/ O: O8 a8 H+ \: P4 I
set age 0* p: [9 n. K. C; @$ N
face one-of neighbors4
2 g: c& u0 Z7 j h/ l4 w* ? set life-expectancy life-expectancy-min +$ i5 _3 I, ^0 |
random life-expectancy-max + 2; @4 q2 d7 n/ E( u
set metabolism 2 + random metabolism-up# q$ b: G( ^9 ^ \
set wealth metabolism + random 30
0 M9 Y2 d( D5 ?$ n5 L: s o6 s set vision 3 + random max-vision
: c6 K1 ^5 X: o$ g! o set wealth wealth + Wealth-inherited-up ] ] 1 B3 j9 ]( |" A" L) ^2 M
7 q0 e! `$ { G* }, M! dend
& v$ H. i" T# K* Jto set-initial-turtle-vars-wealth% f& G0 \+ e* W% |/ P% m& t
let max-wealth max [wealth] of turtles
^& G- l5 _1 M& w! o set age 07 \3 p. [" l# c! j& r" e& s
face one-of neighbors4
3 G& `5 x8 X0 T$ m set life-expectancy life-expectancy-min +' j4 W: J3 ~6 M- l) z
random life-expectancy-max
Z- s. y1 @2 I7 J set metabolism 1 + random metabolism-up; x4 T6 U: J9 T! e# k
set wealth metabolism + random 30
% o q# ^0 ]7 A% X( U8 e set vision 1 + random max-vision 8 G' Y# i8 H7 I0 ^! [! b5 |
end9 U, q+ M6 Z/ |6 X% _- p3 r
to redistribution8 I- D7 ]7 O+ s! z
let max-wealth max [wealth] of turtles2 S& u& \$ F- o- @$ |% f0 _. [
let min-wealth min [wealth] of turtles( ?8 I, i0 b% F8 z
if (wealth <= max-wealth / 3)7 U, [9 r% P1 C+ T8 |! {- Z& l
[set wealth wealth + Low-income-protection ]
2 K1 `& R* x5 y6 K- y$ r/ Dend
+ L- ~/ `, o" j3 ]- ?, n/ s( ~8 R2 q7 k - M# I1 q& |, }3 C. b7 H3 L1 ~
to recolor-turtles, N B2 r! z* n9 { F& `* c' e! ~
let max-wealth max [wealth] of turtles( S5 w: [( [0 M" a
ask turtles; Z" ~0 c2 z. h @ m8 X0 P/ s( k" C
[ ifelse (wealth <= max-wealth / 3)3 @) U$ x& j: R) M9 T. ]$ M
[ set color red ]
+ }( O) n. f: i/ D1 l1 }9 D# ? [ ifelse (wealth <= (max-wealth * 2 / 3))$ S9 J4 M- V" e4 ]) k
[ set color yellow ]6 Z* T0 Y4 l: s' E
[ set color green ] ] ]2 A* C' X1 }- h0 O) D& J/ K2 X
ask turtles [ifelse show-wealth?- |6 V% l4 \8 m4 |# H8 o
[ set label wealth ]
1 V( e- ?, n; K5 h [ set label "" ]]
* ?" r$ L: A! a P7 u- M% a# `end
/ {, {: Y( ^6 T" T( q5 Z$ W" S: S- I( b1 O/ ?
to go
' b+ ~- }. s* g* q9 a ask turtles
. Q0 z9 |: X5 a [ turn-towards-grain ] , T4 N- k% _! P' l. q
harvest; U4 x9 y$ J/ g2 h9 a b3 h2 A
ask turtles4 z( H1 k4 Y6 {0 U8 w* q$ s
[ move-eat-age-die ]: P9 k4 l/ y- M7 Y" v, n8 i
recolor-turtles
5 p8 T/ i# y1 P2 s& i* Q if ticks mod grain-growth-interval = 0
5 u! ^4 W/ Y3 M4 k0 @1 ~6 X4 ~, Y [ ask patches [ grow-grain ] ]. G5 h$ ?+ \" _' z
8 o2 L$ i8 I/ z6 x if ticks mod 11 = 0
/ W6 b# o, ]6 b [ask turtles
# z2 ?! t7 _' c8 Y. o$ ~ [ redistribution ]]
% j) K0 |. n/ @. L- u( ? if ticks mod 5 = 0+ v& }, k) g1 ~# J
[ask turtles
5 C$ O" H' f% G [ visions ]]$ c) x9 q% G1 e
tick# M+ z$ Q; X8 I4 k% K3 |) `
update-plots5 x2 E. B3 \2 M0 [; R7 ]/ V
end
2 F* o: C/ v0 M* }% uto visions: b$ H4 x W3 f* `/ w- j
set vision vision + 1 + `7 N t8 h1 A1 \! Q$ z+ ^
end" c9 R' P! M" J& @' ], S3 I: M
8 M+ H/ j( O) @7 B% a: j; J$ c; W2 U/ @) Y9 Z ^; I
1 f; U& y& T4 |1 e& Y" C
to turn-towards-grain
- S8 }9 u. T# ^5 R2 v: s- F set heading 09 b2 [2 r9 ~9 E4 z, ^( m2 T
let best-direction 0
+ o: ^* Z' ]8 _) J/ L* h let best-amount grain-ahead2 m3 P5 Q# P. a% b, c
set heading 90
4 f! I; B- v7 b$ e( b$ r if (grain-ahead > best-amount)
- L- L+ M, g( E. `9 R; b [ set best-direction 90
. R- {9 b8 v0 k set best-amount grain-ahead ]
; u; Y3 P% f% B( ~* c set heading 180
0 s' \+ [$ Q% x' N6 t if (grain-ahead > best-amount)3 X8 q7 J; n2 a3 z
[ set best-direction 180. f W$ A% c2 m6 m
set best-amount grain-ahead ]
1 ~7 ]7 p. \- I) d, S% c set heading 2703 q h9 }) ~8 |3 U) A6 _
if (grain-ahead > best-amount)% b2 }" E& P. e, I: a& x: U: u; t
[ set best-direction 270
r: N7 N0 }; c/ u. j5 B+ V9 N set best-amount grain-ahead ]
% S( b) C. ]: J4 S( X9 ^ set heading best-direction
: d* n9 u4 Y1 g4 k( _; P7 V' |end
6 ]9 i( ^3 \1 r+ N8 V* ?( A! k0 r* ^; Q
7 i* R) ` s7 \$ c9 |
to-report grain-ahead
$ t1 m+ k2 D) v) r' n. `, r: N! P. g let total 0
% S* J2 l( j/ U- {( F U; A2 B) E let how-far 1$ a! N) A* p x
repeat vision
# m0 g, `3 R6 q+ t: p) c; w% j [ set total total + [grain-here] of patch-ahead how-far
* Z I8 L$ y* _) w3 K4 |. l; ~ set how-far how-far + 1 ]* Y" X1 i. r0 [ V& i
report total
8 \; t. T- G: M qend& n* s; d2 F9 d$ ^: H4 a
. {6 \) }3 `( G* q- s. ~2 hto grow-grain
, `: Z" d1 i/ |0 V5 S if (grain-here < max-grain-here)
" b7 q% b, B' l3 E R [ set grain-here grain-here + num-grain-grown
/ C! G- L2 p1 n: c ]$ m if (grain-here > max-grain-here)
& E1 ^/ S: g' {! Z, Y6 ?7 f; z [ set grain-here max-grain-here ]
7 m+ _0 D* X% l2 P( y recolor-patch ]+ I1 o+ B7 M; h9 N& [
end/ N) S9 d* |* s* `( {: h# h
to harvest% W, R9 b$ `- K9 U2 ^2 a' r
ask turtles% b1 ]. K% d1 p$ f, R& u3 Z
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]) f: B2 E& @. I$ ]5 {/ F6 S( U
ask turtles$ Z) I# q6 K Q2 |
[ set grain-here 08 w# s) [3 A2 T: s# d
recolor-patch ]& z$ D: v9 c3 O; M5 T+ C
% I5 ~. ` c" ~8 \ n' m* ~
end
% s4 K8 }& e0 n& u/ P( o* }- ~7 q6 m
to move-eat-age-die 8 P$ N& o m9 i+ u: A3 Q' h& t
fd 1
4 w4 Z* X1 A4 A& E1 N& R3 O set wealth (wealth - metabolism)+ G# C, C$ a! D6 G3 P" X
set age (age + 1)
4 x" U- B* g6 x: ^4 _ if (age >= life-expectancy)
# |: [4 S1 u, r: z6 s( n( O" G- _ [ set-initial-turtle-vars-age ]2 x% |: m& y4 j5 e: R) ~5 Y" J2 x
if (wealth < 0)
- C+ U: t# X& l* d [ set-initial-turtle-vars-wealth ]( o' W' L' u5 p* e
" U2 M5 j9 _! {end
_' g& Z- Z9 p% k' `# ^' \7 H+ @3 Z
0 A0 w4 g/ ^1 l$ E/ K3 @: sto setup-plots+ N3 ?* U3 N3 w
set-current-plot "Class Plot"
6 R& ^+ T f4 }( r& ?3 D: J set-plot-y-range 0 num-people
% B8 N" U" F' P$ s: Q4 p set-current-plot "Class Histogram"
% M4 |7 {$ \# U6 [- B+ I set-plot-y-range 0 num-people
& O! b9 F" }. I1 l/ v1 Lend
I; M x- O; c0 S+ L" S3 L/ j$ Q! V, B4 b) W# i# W2 i# U
to update-plots
7 n7 ~) Q% _" C/ I update-class-plot; r% ?$ w8 ]! Y" A1 v; z, b V: S
update-class-histogram
, Y. h, P- r3 A/ ~$ g update-lorenz-and-gini-plots
( ~' q W/ P( t' w" q0 M$ P3 z. Wend5 v) p, ^, O7 q0 T
- X; R9 Q# J: X8 @
to update-class-plot
! C/ n" c/ W" K2 q( y( _, \( t set-current-plot "Class Plot"
; J" ^' j s, D set-current-plot-pen "low"0 J1 T; q+ K ]5 U
plot count turtles with [color = red]0 [8 H: E6 Z& `7 k5 ?
set-current-plot-pen "mid"; l. f3 Y; S2 i! m% h8 I0 l
plot count turtles with [color = yellow]# ^" a' ]: K8 H% `2 U9 m* d/ F" X
set-current-plot-pen "up"4 |; |5 m' ?6 L, F! M
plot count turtles with [color = green]! ? H9 K) u/ Z
end
8 S1 z% F9 `1 x. B! t6 t5 v: Z) n9 u, L8 T$ e* _
to update-class-histogram
+ {& m ~" R$ ]$ L set-current-plot "Class Histogram"8 j) Z/ N. L' {$ e4 E
plot-pen-reset; b, [( ~6 J5 ^/ M* Z' y, K
set-plot-pen-color red' L% L8 I) ?( R
plot count turtles with [color = red]& l6 R* ]2 _. y2 y
set-plot-pen-color yellow
. U. k9 r* i6 j& M plot count turtles with [color = yellow]* W5 |- t/ D5 G7 \9 i+ ~
set-plot-pen-color green
% U# H3 S$ O. O5 `3 ^, j6 y plot count turtles with [color = green]
$ }& [; c: [6 _2 iend
( a2 ?& }3 ?/ t/ D }) Hto update-lorenz-and-gini-plots
$ R+ W$ s3 F! I/ f set-current-plot "Lorenz Curve"2 {( y& t7 [9 Z/ K! ~6 k
clear-plot
% R7 L# |* \" v( q* L9 f* R/ q9 {2 G5 D9 I7 \! D& g
set-current-plot-pen "equal"
; K" e# r2 ~, h& i" S0 A2 W plot 0
: T1 N) |$ l& M& E plot 100
( O8 v) `4 Q: P2 s! c5 b& c) ]
# Y) V+ I% i. x. A N5 T5 B( C( P set-current-plot-pen "lorenz"& X3 O9 ?- ^5 I H9 g+ \
set-plot-pen-interval 100 / num-people% I& u0 m1 o) [$ l6 E
plot 0% u% c l0 a+ D t$ h0 r
8 I( J0 z2 i, X: }' x+ _ e let sorted-wealths sort [wealth] of turtles5 Y1 e- V& O1 g9 j0 K
let total-wealth sum sorted-wealths. d! a# c: B, `( m# Q/ Z
let wealth-sum-so-far 0* J. J' B- @5 x3 k
let index 0
2 {: u F* [$ b; m; X let gini-index-reserve 0
- F$ H3 K8 ]# v
# {+ u; F( k& v/ O: c repeat num-people [% X& V6 f, w9 i/ q, m# D' i
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
( ?& @# K% U1 P plot (wealth-sum-so-far / total-wealth) * 100
2 S5 K: D l( }' Z9 p set index (index + 1)
+ r2 c/ B7 W1 f: U set gini-index-reserve
3 u" b5 e+ y" l) [0 E; H gini-index-reserve +
! K! M9 G. J' M5 \7 w (index / num-people) -
" [% d- T; e7 e/ y) ]) z (wealth-sum-so-far / total-wealth)$ P/ U+ M$ Q% f$ B' e
]
* s* q( m* u! x+ a( m" f1 a2 U+ C5 t: s$ k4 Z, V" h
set-current-plot "Gini-Index v. Time"
+ U" y6 ]0 J5 _+ g# g' o3 ]! Q plot (gini-index-reserve / num-people) / area-of-equality-triangle
& D- S3 C J1 S9 Kend
9 U+ W. A/ r! t V1 C9 t9 a: Mto-report area-of-equality-triangle2 M9 W9 I1 `! T' d3 s
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
* w- s3 {/ R' p. K( W x& I) zend |