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; w- L* q& N4 D/ O2 c3 M
globals
, y/ R1 h1 \/ _3 E[3 B% F' @9 t1 N" }6 ^# X2 m
max-grain - v4 b/ }% ~! F" p
# }6 ^; }( _8 G5 g2 Z, I/ Y
]
2 |' ~2 j0 H2 K* V ], u
* s Z9 h0 n7 D/ Gpatches-own) ^. N# R! m$ M; D2 \6 d9 @
[/ z4 v( X% @0 p; u5 F
grain-here
6 g$ k! R! x. g9 e7 q max-grain-here 4 L. x# C( s2 ~# z8 G
]
* t2 s+ e# |/ ^7 d. Z; K3 C7 A, e6 S4 B$ `4 u$ ^0 I; }
turtles-own
& n& b+ J" A1 d, \! H8 K9 p[5 H) H7 [" M/ A1 \; K( \2 j! N6 Y- X
age 4 R3 z9 N6 e* i+ E! B6 L2 ?
wealth
. D1 C/ |- F$ T) ^1 c4 @3 Y/ |& k! s life-expectancy , A6 U4 J8 A9 F0 j6 C
metabolism
4 s; L1 k3 X- {# h' g3 D- q+ L. O3 g& d vision
3 o/ Y) H b8 p* K inherited , I: B+ S% ^; O. K4 K* ?' \
]
% U$ k# m/ V7 U* D5 j/ [0 I* @% l
8 x3 D7 _4 A4 M! z: {5 h4 ~* |& i5 R% s: f
to setup
0 I% o% G. G, K" g' Q, z% T9 ^ ca
# t& x/ D9 ~2 ^0 D; u. w set max-grain 50
/ a! b" ~1 U8 o) J# ]! k" r setup-patches
" A+ ~" j! ~/ Z: e- L setup-turtles8 R% m4 B$ ~1 @% L! N# @; e
setup-plots) n! u4 w' m: B( ~8 B. h
update-plots
. j2 B5 R T3 n/ I& kend* b! @/ u* ~: p5 S. p
to setup-patches3 O5 C* \# ^6 o( F- Q
ask patches) t7 P3 D* I5 f, p
[ set max-grain-here 0
4 K& q# r. Q) n5 j if (random-float 100.0) <= percent-best-land
& R6 n) t0 x+ V; ?- @3 Q5 ~ [ set max-grain-here max-grain2 }7 `, T9 s& @- r. n3 P6 l/ ?
set grain-here max-grain-here ] ]; k$ {$ P) K8 n( i% [' C9 R0 `
repeat 5
7 S7 R: t- Z5 _+ B8 p [ ask patches with [max-grain-here != 0]
, d; [; A1 \$ e# B: o0 r4 z# @5 E [ set grain-here max-grain-here ]
; F% W+ }+ E/ f diffuse grain-here 0.5 ] ~$ w5 z: W B2 B8 [5 _
repeat 100 d8 E6 S4 ]# x: w
[ diffuse grain-here 0.5]
8 r& R, P6 k& Q2 x+ ~+ ~% q ask patches/ c. A& M6 a: |
[ set grain-here floor grain-here
% r2 U: M0 E( _1 L# g set max-grain-here grain-here
L: ^4 j" K. a6 o2 M7 r' F recolor-patch ] o( O( p1 u: L
end. L% ~; S/ ~9 X! B3 |: Y# c) k8 c" S
to recolor-patch
# ^& j: c& U. `! ^) K+ g9 O7 S set pcolor scale-color sky grain-here 0 max-grain+ V$ T% b. C. S% [4 r5 I2 E6 ]
end& I0 T; s# x2 _( k! J
to setup-turtles
4 G9 _# z6 x9 y3 C: a set-default-shape turtles "person"
1 j4 v" q; S( h- q2 y( o! t crt num-people c# N2 O8 j! c
[ move-to one-of patches
, e0 X6 i2 n" J# G9 w9 d set size 1.5 - e5 D- S. e. @0 o" m, i
set-initial-turtle-vars-age+ R# O$ ]8 K' d f* g
set-initial-turtle-vars-wealth/ }8 O( J9 g: W/ r+ @1 N/ \
set age random life-expectancy ]
1 k j7 p' o, d, s( v recolor-turtles
( N/ Z& G. T; Hend1 m* r5 \$ H; [! }+ l* z# V
9 }* N. |9 r, V. \/ E! a% h( Bto set-initial-turtle-vars-age
9 y$ p& S2 e: Z1 P' H+ Q$ k let max-wealth max [wealth] of turtles
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M% i0 T' A- r, v8 O' j ifelse (wealth <= max-wealth / 3)$ x' k3 ]5 I, @ c
[ set color red
) r! I2 V7 |9 c' D8 R7 R' h9 Y2 Q set age 0
$ g# n7 V+ i* V) r, f& d7 I: r/ c face one-of neighbors4
4 l" D0 I# z( R, { set life-expectancy life-expectancy-min +/ H+ z4 x8 N" |
random life-expectancy-max - _ D& i/ N7 o$ _0 W
set metabolism random 1 + metabolism-low4 a0 a: p3 Y+ f/ y3 M& N
set wealth metabolism + random 30* P. t v( a( B, }2 c$ K7 F) H. i
set vision 1 + random max-vision
- i; O( p% ^4 `3 o( L6 Q( } set wealth wealth + Wealth-inherited-low ]- k' V5 `" \7 H2 I) S
[ ifelse (wealth <= (max-wealth * 2 / 3))
' }. u& `: X, b9 D) M [ set color yellow # ?; [1 a6 L8 m) F) r' E$ _, f
set age 0& }8 ~1 Q0 X0 R) M+ s# ], V
face one-of neighbors4
2 Z4 T# ], k# O$ Q' e set life-expectancy life-expectancy-min +. J! m: s' b x ?- |* E) J0 A
random life-expectancy-max + 1$ }9 q% P4 s' n2 c
set metabolism 1 + random metabolism-mid [4 q% M. X9 z9 }- E
set wealth metabolism + random 30) j7 x$ }1 q% v2 E
set vision 3 + random max-vision
0 E" v2 O) G( ?$ x set wealth wealth + Wealth-inherited-mid]; u9 N& _3 D# N3 N1 n2 _
[ set color green
3 o0 Q1 \5 O. L d5 ^ set age 0
) L8 I- G0 I& n0 f; c% o Z1 K; V% d face one-of neighbors4
2 X" T) ^' a( C- I set life-expectancy life-expectancy-min +
5 h) |/ _& c% ^, J; _. U! u Z j J random life-expectancy-max + 2
5 `* o# M$ z7 D set metabolism 2 + random metabolism-up
; t- m/ y9 f8 w$ x0 k6 D0 w7 H set wealth metabolism + random 30
* u4 _) m0 e/ W1 x% I) A& j! o set vision 3 + random max-vision% |$ n( S4 d( Y5 _5 m; e
set wealth wealth + Wealth-inherited-up ] ] ) m! @9 S' z4 S
$ a! [& J$ d# H4 L4 c3 j2 o* t( V
end* [3 r8 z2 e4 I* I9 c
to set-initial-turtle-vars-wealth
# k3 l' q+ m* K8 o5 R4 b let max-wealth max [wealth] of turtles
1 x& `" w' i- A8 _ set age 0
8 G2 k6 Z P- M9 C' J face one-of neighbors4
$ w# d7 }* g, y3 n9 T- E; Q set life-expectancy life-expectancy-min +
6 l0 J* B8 ]: q random life-expectancy-max
! @5 I [+ d( G4 P5 f set metabolism 1 + random metabolism-up
Y, E) n/ i$ y set wealth metabolism + random 30
( b" `8 ?$ `9 C7 Y3 h p" L! G1 g set vision 1 + random max-vision
1 r/ H7 D" i0 H, X' c Aend7 W. y! A% N( b% v+ G5 D& q: q6 a
to redistribution
1 ?9 ^' B, Z' I1 d plet max-wealth max [wealth] of turtles
. R- k1 l9 p# c2 v! y" Plet min-wealth min [wealth] of turtles
0 E+ Q/ b$ T/ o: i2 Pif (wealth <= max-wealth / 3)
! s( ?& C: x5 P }( u [set wealth wealth + Low-income-protection ]
; A" G& R4 p! k; u5 P7 D& Aend, w( T' ^, i3 T" k4 @" v
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to recolor-turtles$ O" z5 R) P; x- n
let max-wealth max [wealth] of turtles
6 |# h) s L0 P3 t" | ask turtles
) ?' }1 G5 V. D) O6 J [ ifelse (wealth <= max-wealth / 3)
$ ]! S9 k1 n% j7 D7 `" W% Z. d [ set color red ]
) ~# T1 P: u8 Z8 H) J$ ~& D [ ifelse (wealth <= (max-wealth * 2 / 3))
5 \9 @ b( n; O( b0 `4 `- o7 o$ | [ set color yellow ]4 P" }9 y' M- V& a6 M) ~
[ set color green ] ] ] ~" M4 m, X% g% z1 E
ask turtles [ifelse show-wealth?; Y. j1 P' D+ N& X
[ set label wealth ]
! }) A' g! r' i. b R [ set label "" ]]
* \0 a; @" {% q7 Rend# [& s8 H4 A( l! {4 c) r0 c+ h. J& K
& c& {" T; O. n; k f: b0 O
to go2 f5 X+ F9 h$ K1 Z' q T' F1 Y& f' Q
ask turtles# \: p6 j- y7 B! [+ i$ B
[ turn-towards-grain ] 2 f* {. c1 |+ X D) n+ X
harvest- O( B9 h' O9 ]7 L4 j3 o+ X
ask turtles
' A1 X6 h1 m6 \: q$ f [ move-eat-age-die ]7 B9 |9 [ u5 f8 z
recolor-turtles( t Y6 @1 V0 R2 d
if ticks mod grain-growth-interval = 0
7 F: l6 e6 c& e6 a [ ask patches [ grow-grain ] ]
% i% q( F3 X) [( Y! V, q : S& `8 }- R- l& R, V( i
if ticks mod 11 = 0
% [5 p# [6 `, O9 X [ask turtles8 y9 y8 M) A8 Z {& R+ ~ y% D
[ redistribution ]]! o4 S! M" @7 }' R% ^8 h( D) q* `
if ticks mod 5 = 0; C- z0 [3 }- ^' V' Z, s* D$ Q* _
[ask turtles
/ u1 o1 m& l* I' y* n/ Q9 {$ } [ visions ]]: i( V, Z7 V0 I( D8 x8 w m
tick
$ w* g& ]/ k Y! m: y update-plots
" @( e6 A& R5 B/ w' G% Send2 f u0 d# k8 g4 E! }, Q
to visions8 c3 X% I2 e2 x) T+ e) c, ^# C4 m- e/ y
set vision vision + 1 - N) z" S; q, u) C) ^+ J+ z. ]
end
E/ F' V) s/ ^0 G% S1 n
) E9 f) m- m! T3 C) O7 R
9 _; I$ ~( b X$ C$ T% J1 O
6 C8 Y4 d- ^% a; |to turn-towards-grain
; ?4 }3 G' S% t$ \& Z2 ` set heading 08 i5 Y3 Y" y* V5 r& O
let best-direction 0
' _* V8 N4 k% c9 M5 l: B let best-amount grain-ahead. g0 V) ], x4 X* O
set heading 90
3 P" ^3 v# q& ]; a if (grain-ahead > best-amount)3 x; h `, s, }; H, D
[ set best-direction 90
) {) k z* b% ^ X set best-amount grain-ahead ]& `, i% n# T/ h' O" P. {
set heading 180
( \6 M4 T( g' H: C: U7 q if (grain-ahead > best-amount)0 W/ y+ F6 X& e9 ~
[ set best-direction 180
* ~& r+ S1 @# ~+ J set best-amount grain-ahead ]) ?, u( c$ N% j( Y. f' i: ~
set heading 270
& k# n1 j" k$ d7 L" G if (grain-ahead > best-amount)
3 l1 U" s! X$ V [ set best-direction 2707 T+ n4 U+ r/ o# f c& X, O3 j- G
set best-amount grain-ahead ]% A' O: ]4 t$ S
set heading best-direction4 U5 c9 G% t* |4 _! F" E# ?
end
: v0 {! M" e, n3 N) Z! H8 v$ T H( J! R. h% G6 I
8 ^2 S6 i6 g A0 E# K
to-report grain-ahead 5 x8 F3 \( u4 c
let total 0
; F- u3 I- q- o8 u; _* ~ let how-far 1
# E2 N7 F2 m4 e# ~7 P% H repeat vision
n0 o4 l' O: q9 J. o4 i% i [ set total total + [grain-here] of patch-ahead how-far
" ^* N) l* A2 [6 v: U' v set how-far how-far + 1 ]$ C6 f! Q" p( ^( E/ A' Y
report total
& ?4 d, O+ c I9 e/ hend
1 q0 A0 F0 _( S* X9 B' {
/ h. g+ q) J; eto grow-grain # ~2 R+ w& o2 g' y" U# s- W
if (grain-here < max-grain-here)5 n: E* j. a; C4 |* K
[ set grain-here grain-here + num-grain-grown! z O# v3 G1 c. s
if (grain-here > max-grain-here) % p- ^* }3 F6 k1 o: r
[ set grain-here max-grain-here ]; R [3 d& S$ r E
recolor-patch ]1 t$ Z+ Q3 p( B3 Y: d: x
end# |! `- v% |7 k( I, R- s' a. M
to harvest0 C) Z& J+ `( G: \. l" E. T6 ]
ask turtles! c7 }% y: ~; Q. B [8 z/ t7 e
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]# Q$ d- W( d1 T2 a) Y, Q3 Q, S
ask turtles
# Y! ~4 f8 [& T% Q [ set grain-here 0 S! x) \4 s. t! G
recolor-patch ]0 C+ w# C X0 f5 e) Q0 K# C
, c! u% i6 P" B8 @! lend
! O- r4 e8 \" S7 A
) s9 g. M- N+ l2 Eto move-eat-age-die
& o, s' A3 S, p1 Q fd 1
8 p5 }: M: K) h& L- w2 z& \ set wealth (wealth - metabolism)
' K: @+ E( k- q( W' T, D set age (age + 1)8 g- S* x1 X! d/ o3 h6 E
if (age >= life-expectancy)
, X' j- Y4 G) A+ q6 {4 | [ set-initial-turtle-vars-age ]
; p6 o* `+ f- s4 ~ if (wealth < 0)
6 o" T% h" v# a; N5 H [ set-initial-turtle-vars-wealth ]
* p# J2 k0 v) Y$ }5 S4 g" j2 F 0 w& y+ x3 ~* c/ \8 F4 l
end5 r. R4 x% o. [; b- t
) \* l0 K5 X* u' l# G8 o6 C1 u9 n4 I- Q1 F% @4 d& W5 ]' a
to setup-plots/ a6 @# g( L$ U6 Z$ |
set-current-plot "Class Plot"# S& J' x1 k. o9 A, v; r9 z" T; A* x
set-plot-y-range 0 num-people0 I8 b: D/ L! D
set-current-plot "Class Histogram"
: O3 R5 p/ F, o. }& C/ r, B set-plot-y-range 0 num-people
3 k! k8 p1 B, n+ hend& N) T- y W* i) u, _
' b9 J* r2 g0 w0 B2 _
to update-plots
" j6 U% m7 d7 |7 B% o3 { update-class-plot
4 U' {# W3 |! Z3 X9 X update-class-histogram/ F4 L$ J) [0 x9 w3 z- U
update-lorenz-and-gini-plots
* F% I2 W. L; N" k5 rend
5 R5 Y7 c6 z6 L% Y
( `8 _8 u9 S+ O0 `7 Jto update-class-plot
* ]' {( x) z' M$ V& l set-current-plot "Class Plot"
3 K5 l: m1 w; f- | set-current-plot-pen "low"& |: k6 x; ]: ~6 O' T4 |
plot count turtles with [color = red]
+ W+ w2 K7 G7 H) W set-current-plot-pen "mid"
( p7 {; T2 b3 a, X" a( m plot count turtles with [color = yellow], g. p6 \3 W' ^/ F( h
set-current-plot-pen "up"
8 A/ }3 C' j, Q& g plot count turtles with [color = green]0 C1 O7 j r6 E- p7 U9 n) F/ o
end
+ R7 F$ m3 i$ Z8 `' Z- g l- t$ e2 ]% R t& [' o4 s$ D
to update-class-histogram
5 L4 `) ^* ~) m3 @0 _* n8 _ set-current-plot "Class Histogram"2 E3 Q0 {2 V4 x, P
plot-pen-reset% C+ a! ]& ?# A- R
set-plot-pen-color red' |, K+ _. }; s$ D( a. e2 |
plot count turtles with [color = red]
2 a; ^* B. {8 q( ^0 b! ` set-plot-pen-color yellow
; X" \. u3 b1 n2 ~ plot count turtles with [color = yellow]* s" D. d- ?. V4 g. G. q
set-plot-pen-color green
9 I, D: E8 H: A+ T plot count turtles with [color = green]" ?0 Z D% V. U H O3 C
end5 \# R: R" S) m
to update-lorenz-and-gini-plots! q( G% w% l8 p1 ~! U j: L
set-current-plot "Lorenz Curve"3 p5 \3 P2 a& [/ |- j& h
clear-plot* ~' J; ^! T5 ?7 Y* ?7 i4 u/ B7 Q
' H* w8 P7 H% D! O
set-current-plot-pen "equal"" r1 J+ j! B! j; g' h+ |5 q3 k
plot 0
" B- Y& U: O, L5 ^* D1 F plot 100# F6 t9 e6 Y# t: ]: |
! x1 `3 |) e" A( O& S3 E set-current-plot-pen "lorenz"5 k s4 \' D! z
set-plot-pen-interval 100 / num-people
' e' b8 Y' M- ]8 [- ?+ @ plot 0
' T% o& i' ]6 b
2 [+ Y# V4 ~/ M. x9 G) j' b let sorted-wealths sort [wealth] of turtles; ^ b7 a' u& s
let total-wealth sum sorted-wealths2 L7 m) Z# s2 j0 d
let wealth-sum-so-far 0
1 I, c4 P9 A( l let index 0
/ A6 C9 @8 o* g9 D6 x8 z let gini-index-reserve 0
- m7 {3 s/ x' ]2 q. K
& S v: X, w3 q repeat num-people [
: _# M3 q1 y' D' x. j7 W+ S5 C set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)5 U3 \/ s. F& y
plot (wealth-sum-so-far / total-wealth) * 100 O! v# r% N- C3 r% a( h
set index (index + 1)
% [+ M; p$ M+ _) b" V: u set gini-index-reserve! [# ?- M h1 A% P, t) }! Z+ _
gini-index-reserve +
1 L9 F3 H8 ^ L2 o (index / num-people) -
+ \5 p) t3 g. K l% u( b3 l* A (wealth-sum-so-far / total-wealth)
& Y+ C- [+ z( c+ t( L! w0 `8 l9 ` ]' u& Y6 l4 W* X5 t8 g) t
2 d1 `0 x. d" u/ W
set-current-plot "Gini-Index v. Time"
/ _$ s, w2 `! `8 \3 j plot (gini-index-reserve / num-people) / area-of-equality-triangle
9 E) Y- q; L9 D9 c W1 G2 W, ~$ r2 Eend8 K6 U4 d4 a" J0 Z4 c
to-report area-of-equality-triangle" r. t. ^$ V! t) G g
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
5 J# C6 Y; ^" q9 | d z) fend |