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
, q1 ~$ J9 Z" L% z0 Rglobals+ q+ ]6 u4 l5 Y# J
[
( p0 R; G5 Z. E7 e, M2 o max-grain
2 s6 v) I& c" m4 _0 ^8 \+ {5 W4 G1 N
]
% ?" m8 `3 W- d, {0 C
+ ]# s& w! G5 \7 v0 Tpatches-own7 V5 U; ?3 [3 [& V0 [* j
[
. H+ Y0 X0 a( n grain-here & j' u4 x( @( p+ z5 J0 P* r
max-grain-here 3 h, A" }" T7 Y( R2 z2 H7 e+ G9 P
]
F; ]2 A2 F" k- A# `2 Y: L r2 y% R2 l( I/ w
turtles-own9 m" \5 [6 [7 G; v% ^0 y+ c
[
( v3 j) F% P7 B age * G$ ?; \! i+ ^1 u7 z
wealth
% b+ [, y! J* y) k6 g Y life-expectancy & w0 U- B7 `' ]3 `2 G- X
metabolism
5 g( {; w$ H/ |0 Y vision
( o7 }, w8 H4 @0 f+ \. Q+ d inherited 4 E( Q1 c- \1 o. d( U& B
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! k7 D) P; _ x$ r/ U% ~, V! g- A- h
to setup, L; G9 _2 q- A/ D) {8 I
ca
0 W; S! \1 I: r, e' R7 l; r7 e set max-grain 50
( x% Q3 ?( R4 F setup-patches
4 C# g- R! O' C* ^- k" X setup-turtles4 _- s, ]. c9 ]4 Q- `! A
setup-plots: L5 n7 s; C1 @$ j. k
update-plots
/ g! _' K; S8 Q4 gend
# n+ {. ^/ k* Kto setup-patches
- e/ g( b$ X- p6 p0 ? ask patches/ P' r7 a9 ^$ L* ~# g
[ set max-grain-here 0
, ^/ M* s% q) } if (random-float 100.0) <= percent-best-land. E% |- [$ a2 p Y; l; @* F
[ set max-grain-here max-grain% M3 Y b" `6 O. f8 s; h) o+ Q
set grain-here max-grain-here ] ]
: ?. p# ^! b8 u repeat 54 d* A6 h" E8 @* C- `* o1 N
[ ask patches with [max-grain-here != 0]6 p8 R, a! \( [- |0 b
[ set grain-here max-grain-here ]# t% \6 H2 e9 o0 Y" R' k
diffuse grain-here 0.5 ]/ h% I7 Q7 @: h: \5 G ~5 }2 B
repeat 10
- r9 G# |: e6 n$ Z) j' ]# { [ diffuse grain-here 0.5] ) D( l; R C5 `/ z+ S2 v
ask patches
" {4 t5 g9 |9 z! L# K# P! x [ set grain-here floor grain-here * F* e: M$ w. @
set max-grain-here grain-here
' m. E1 Q8 E# f6 |$ L. C recolor-patch ]8 w: Q$ a$ i$ t) \
end( }8 X( ? P, a j# M2 ?
to recolor-patch
$ L7 C, Y7 w' C* J/ e, g set pcolor scale-color sky grain-here 0 max-grain/ H' [9 V* E" E3 A% j
end
/ ~4 y3 g9 F2 a; Z5 Tto setup-turtles0 ~6 F& |$ A. Q+ I
set-default-shape turtles "person"
) X# G; ~ v7 q! F1 i' N% q crt num-people
$ Z9 ^9 F2 C$ w5 o [ move-to one-of patches & r/ U, r9 p: V/ \# p7 P/ v5 _& B
set size 1.5 - U& o8 d. D3 p1 d4 i$ b6 {
set-initial-turtle-vars-age4 V: e1 Z' C" M
set-initial-turtle-vars-wealth
J4 E: }4 E" u( N set age random life-expectancy ]9 O3 [& I, `: I
recolor-turtles
4 p3 |& ^$ h1 I- K7 {end' m' k7 V, I- u7 M6 d
6 r$ ?- Y" c. W9 \# r) Q; m; U% ?# tto set-initial-turtle-vars-age
: l2 q- @: t+ O. p let max-wealth max [wealth] of turtles' a/ m: J$ Z# K+ m8 a
; j3 ]2 N, j2 j ifelse (wealth <= max-wealth / 3)* ?. j, p9 V+ d; c9 p
[ set color red 9 j) [- V7 ]! x, x
set age 0. J3 G4 W+ Y& D7 ?% Q
face one-of neighbors4 & q' }/ ~. L- u q
set life-expectancy life-expectancy-min +0 k ~& r) ^! E
random life-expectancy-max 1 M4 j0 d* @0 {/ |+ K
set metabolism random 1 + metabolism-low
2 o$ w c, f, u9 p set wealth metabolism + random 30) H. R: z$ @# Z, o
set vision 1 + random max-vision% v+ V3 H$ |) i: I0 @
set wealth wealth + Wealth-inherited-low ]* ?) v# R- u6 ~5 w6 P
[ ifelse (wealth <= (max-wealth * 2 / 3))
- s& a8 k2 n9 i" t3 c [ set color yellow 8 C; k$ ^/ g+ _& }8 e/ F. _
set age 0
3 [6 o* u$ A4 H* V { face one-of neighbors4
# X/ E' q3 j9 O set life-expectancy life-expectancy-min +
# `9 b! T0 I& s, [' X% f random life-expectancy-max + 1% N- Q3 x* Q4 \! c# T ^
set metabolism 1 + random metabolism-mid
! F, D) M9 R7 u set wealth metabolism + random 304 M' w. Z* ]1 @6 X" h9 o3 d
set vision 3 + random max-vision8 H: B2 O" K( ^1 \) ?6 b1 l9 C
set wealth wealth + Wealth-inherited-mid]' c2 v1 q3 d& I+ v
[ set color green
! Z1 p' F- s. W" P5 A% I set age 0( e2 r+ c6 W& \4 u7 m; e% j
face one-of neighbors4
4 K% y. s6 C8 v$ @ set life-expectancy life-expectancy-min +
" D% F2 j0 _3 z$ o/ z random life-expectancy-max + 20 o' a( H% D4 q/ r' R: U
set metabolism 2 + random metabolism-up3 m1 |2 |$ |/ @3 T6 z6 I
set wealth metabolism + random 30
- Z; I7 R8 f; q/ X1 a2 J1 t set vision 3 + random max-vision5 }5 K H: O- P* ]4 O' Q/ j3 x
set wealth wealth + Wealth-inherited-up ] ] & g! y- B' [7 T4 M' b$ `4 Y: _
& k: [6 Q& v, Q6 [3 v9 O& V' kend8 Y& H/ C& g D M. Z+ f
to set-initial-turtle-vars-wealth% }- Q% p$ _: _& A; X' Y: ?
let max-wealth max [wealth] of turtles
- V1 @- c' C) @; Q7 [ set age 0! W& d7 `3 a: v! c" Y0 a
face one-of neighbors4
( k7 u. y o$ R8 q* u set life-expectancy life-expectancy-min +. t3 W, n4 @$ `, u9 @
random life-expectancy-max - n, C9 z. m$ h* p5 }1 H
set metabolism 1 + random metabolism-up- L+ m( v+ x1 T
set wealth metabolism + random 30; N; n% T4 }6 c# x$ W" r
set vision 1 + random max-vision , W/ H# n) _ }6 L
end
0 V2 x" N+ d+ D7 M1 v1 uto redistribution4 s# e5 F. V( O6 y
let max-wealth max [wealth] of turtles
& ^. \$ n9 y0 g0 h. Ilet min-wealth min [wealth] of turtles+ ~$ ]1 d {2 V: {: t
if (wealth <= max-wealth / 3)) }& `2 |. W- \/ i& `5 X
[set wealth wealth + Low-income-protection ]6 u& l* K0 b4 X8 M3 J
end
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0 E4 m$ W9 g- P( { `5 s, m6 n/ hto recolor-turtles( ^$ ]% d* K% y7 m, \0 }$ J
let max-wealth max [wealth] of turtles) U+ \! g1 g; p
ask turtles H6 z2 }9 a: g0 H+ q% `* H3 `6 u
[ ifelse (wealth <= max-wealth / 3)
4 h1 Q5 [3 h4 M+ R [ set color red ]! u' z$ \ l! f/ q w# D4 j$ B
[ ifelse (wealth <= (max-wealth * 2 / 3))
$ s+ L( @" {2 i& m+ S [ set color yellow ]
# w8 P+ p& H, ~0 Z4 K' u [ set color green ] ] ], @' V8 W& L7 k4 L1 B: w0 f- S6 a
ask turtles [ifelse show-wealth?
+ K# V8 ^ N7 T$ t' D* ~% K [ set label wealth ]
& Z0 G M+ n6 {7 s, n6 n! D1 w [ set label "" ]]" Q# N+ i5 [0 v0 S5 R
end, l9 t2 B' f* Z* ?3 _
# z& x8 `1 z1 m g! ~9 H9 mto go
3 k* h% P ]- Z* \0 I% o; ` ask turtles
& L7 @- X( }# z, p [ turn-towards-grain ] . f; W7 S0 U( g8 P1 F
harvest
3 u, t! B5 [9 E; F3 v e/ N ask turtles( Q( z' x4 y9 _' x* B; V1 ^& e
[ move-eat-age-die ]5 w1 I+ g1 B3 d( ?& H: N
recolor-turtles
8 z8 l4 j8 o- V3 [2 I. s& L if ticks mod grain-growth-interval = 0
- E$ m/ t* A" _- y [ ask patches [ grow-grain ] ]
* v& J# D' h# F/ S: ~7 h1 ^+ `0 X8 @; D0 S) ~ 1 ?+ k8 B2 V7 s( m: e
if ticks mod 11 = 0
% r% K! O7 Y! X3 s6 N( B& ] [ask turtles
5 W) b# J! I5 a& ?2 H [ redistribution ]]1 I3 t) w+ H" \9 b3 L \! [* o
if ticks mod 5 = 0
" A( Q' j1 i4 f" Y0 j; ` [ask turtles2 ]1 `4 v7 [; Y# P7 _/ \% p: j! y
[ visions ]]
( y2 a% J8 f; [ tick l1 Z' R" h! Z% K* s0 t
update-plots; E, i$ ]& m) q
end" l) e5 ^+ B4 Y: T+ J& }
to visions% v- b4 Z& m$ X
set vision vision + 1 / j B& h! i$ Q9 R( L0 |2 a
end3 v& C1 G6 X/ P/ v O
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+ D8 k5 v) J! S8 `, x2 a% r* q
5 J1 d3 L6 B- P. W z4 U, D+ t+ Q
to turn-towards-grain
9 e8 [2 _) D, P# ~ set heading 0
: d* M1 n# r/ @- w: J# I- R4 g$ H) H let best-direction 0
/ \ A0 M& }# p* ^0 F. O let best-amount grain-ahead: F9 v3 a3 i: J. I8 t2 c4 r
set heading 90$ X* V# K f4 F
if (grain-ahead > best-amount)6 t3 L7 ]; }# r5 g
[ set best-direction 90# g1 C" ~: h t( N7 t1 m0 |/ X _
set best-amount grain-ahead ] ] ]8 L' S2 l u9 m$ T8 o" x F
set heading 180
& E7 Z9 C( x1 ^+ ~$ M" c if (grain-ahead > best-amount)
. V$ O4 Z: T0 t6 X- b" t [ set best-direction 180
4 ]5 X6 P _" p# k4 l set best-amount grain-ahead ]
6 p( h* @4 G, E! ]4 f set heading 270
# \2 ~( ~* X4 l- V% V$ z if (grain-ahead > best-amount): C- |; X L9 b. m# v
[ set best-direction 2706 p2 P: y5 W, z- h0 E: J
set best-amount grain-ahead ]' Z1 ]4 d* ? T1 `% W* @: n2 h1 |* |
set heading best-direction6 d/ b: l' y( n8 I/ d( c9 w' H
end
+ w% {' k/ t4 h7 h1 D) x7 ?2 g, q. A! X
4 a7 _; ~1 a* I" J" J
to-report grain-ahead ' Q1 }* X( }- p6 Q1 m' u9 e: z- }
let total 01 \* ?% ~. Y9 i3 V/ s
let how-far 1$ c' i S& o/ `/ n2 B/ `- j# _6 A
repeat vision* _1 Z+ W {0 E- M+ `, s/ @+ R) y
[ set total total + [grain-here] of patch-ahead how-far
, f5 _. z b3 C4 }5 V set how-far how-far + 1 ]
/ [' \+ H% D- C/ B9 A! x. u/ V8 Y& r report total
' f: Y& [9 r* L1 Q' \+ A% \8 {9 wend
( v! t$ d5 P3 D6 |7 y* {0 \% r! r- b7 T( V; f; L* q8 {
to grow-grain 5 E4 ?% G9 o" F* Q
if (grain-here < max-grain-here)
: g* K- m7 a- `6 N [ set grain-here grain-here + num-grain-grown
# B( J2 |6 {2 o# H" \ if (grain-here > max-grain-here) + z. N0 B1 W; M+ f
[ set grain-here max-grain-here ]
3 V* e8 U! h/ g# y recolor-patch ]# M7 y1 g6 H0 d! c. ~
end
( W7 T& o. W0 Jto harvest
E. c+ n6 |7 b+ B3 B. U2 y ask turtles
2 z" N- f! s0 m+ j8 k! }, H [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]: ~7 a' ^* F4 G2 a. P
ask turtles3 u) E+ c: ^/ @7 x% }
[ set grain-here 0
7 c$ n* X. e7 s) f* L recolor-patch ]; x# C- D8 Q7 [
! {' V9 L+ R: C7 p; Q" w+ g2 j
end
0 w: X- c5 `0 v8 s& c* G3 N0 e8 X0 ]2 M: ^: i
to move-eat-age-die
) T* R) k4 U2 A1 J fd 1( N/ m# g' y" U8 w! X T/ {
set wealth (wealth - metabolism)6 T6 _ u% a, k! a& b* t. i
set age (age + 1)6 _* }4 [& p4 ]0 S% [- J8 l; G
if (age >= life-expectancy)
5 k) P8 J9 W! }: b m9 T [ set-initial-turtle-vars-age ]
9 s% t& I" I, _4 Z# @. S' X if (wealth < 0)6 a7 S; a: X! n' x) l) X
[ set-initial-turtle-vars-wealth ]
& @6 d5 U7 R+ {) ]8 P* e+ Z 2 b8 i3 o# Z9 A$ j
end
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: d& m/ W/ X* h6 L% yto setup-plots
8 l @, h8 y4 u$ x6 J ^ E set-current-plot "Class Plot"
0 u; ~: O( ^9 w, X* v V set-plot-y-range 0 num-people. w+ f$ h* r& D
set-current-plot "Class Histogram"- `) _: q5 ^) w. B1 h( V( l
set-plot-y-range 0 num-people( ?4 K* m1 m+ c4 ~; R8 T5 b) N& X3 i
end3 \6 ^. g5 _' B. ]
. C( K9 Y; ?1 I, }% T
to update-plots% [! x" Z# J: E7 R
update-class-plot
9 u/ |# X& v+ z0 g update-class-histogram
$ P6 l# A: D) t6 V" z update-lorenz-and-gini-plots' X8 p& }1 G4 M" y
end1 O( I& [+ D! j/ K1 m9 Z
D1 H2 l" o7 d* wto update-class-plot
" N; M0 ^6 V2 O) H) M set-current-plot "Class Plot"
' B& V0 v/ D9 Q6 V) t set-current-plot-pen "low"
( Q' _$ {% H9 k0 p* J3 X7 A3 @! M plot count turtles with [color = red]1 _3 k6 f" A2 z4 K& C( e* }" G
set-current-plot-pen "mid"
, g" T9 k9 B4 j4 F plot count turtles with [color = yellow]8 F# R$ H q5 ^ e( M
set-current-plot-pen "up") f3 ]7 X' f; ^0 a8 x" W( \
plot count turtles with [color = green]/ z. b; M9 I2 z5 c
end' Q' [' _# ]% w# Q0 ~
6 D1 v4 j$ |+ ?: T
to update-class-histogram2 a! j% u( ^' B" b$ K b1 W
set-current-plot "Class Histogram"
' U$ H& q- j( f. q! [8 V8 D plot-pen-reset1 C: F8 D8 Z% o8 s) s" |
set-plot-pen-color red
; Y# X/ T5 n, p0 w) r! p plot count turtles with [color = red]0 n. u% k" ~' c
set-plot-pen-color yellow
0 t/ l X$ f) E ]% q$ [ plot count turtles with [color = yellow]; d5 c* Y2 M" e+ [+ q- Y
set-plot-pen-color green
, V( x5 i" {) H# D7 |) _1 _/ b plot count turtles with [color = green]
8 [$ E, O( [" f; _. s5 Q/ Cend/ p( ]$ X4 o$ S8 L# j% D
to update-lorenz-and-gini-plots! ^- a. V% x- [; D7 s( w8 y3 Q
set-current-plot "Lorenz Curve"
+ A2 m: ~2 Z3 Q% O7 ~2 X1 f3 u5 X clear-plot: y; m: y6 P& w5 H2 a% B
0 `; I8 T: Z* [+ {. Q6 L- b set-current-plot-pen "equal"
/ [5 h3 \( \/ J4 B2 D plot 01 m$ t: a l+ _
plot 100
+ q' @3 {1 r# A b' f; J2 W' M. c% L
set-current-plot-pen "lorenz"/ q- ]! J# w% r9 t# a. V! c0 B
set-plot-pen-interval 100 / num-people
3 W' p6 U9 Z% U e8 J plot 0# r' \; J. ]1 Q2 R4 `
) k4 {7 v8 i: m7 h* H* L* P
let sorted-wealths sort [wealth] of turtles
4 } R: M$ X! F% X8 F: D% I let total-wealth sum sorted-wealths
" r1 S0 q3 p" _& o9 C let wealth-sum-so-far 0) o, A( l6 C% I: }- N% i( C
let index 0, V$ ^- ]- U& b
let gini-index-reserve 0
$ h# C- I# e% \5 E" e* l; G
. V6 P( J3 m [" V, r) P repeat num-people [
' C4 I6 v# i" K& i set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)) l% @; r4 {3 u5 v6 o
plot (wealth-sum-so-far / total-wealth) * 100# W% @: x+ z- Q
set index (index + 1)
; a* s$ \+ T7 [( F$ @7 s' c set gini-index-reserve
! L9 r2 [: A4 g" a# G gini-index-reserve +, {* j7 a/ K* O
(index / num-people) -
( Y4 A2 r. D7 u( T- g' p: T (wealth-sum-so-far / total-wealth)7 Q3 `% ?- t/ H6 E U- G" U
]
5 T/ w# c# @; o. Q' E/ `( y4 }( L5 _% T
set-current-plot "Gini-Index v. Time"4 ^- \( t6 t/ Y/ M9 u
plot (gini-index-reserve / num-people) / area-of-equality-triangle
* H$ _1 U ]- V8 s/ ?2 O) m. L' oend
) \0 w9 X" T. z9 \: Eto-report area-of-equality-triangle2 P6 n1 e' X* T1 A% \ R1 o
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)9 q5 Z2 o% v. S: K! ^7 x
end |