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0 }, J6 ?4 Y. W5 V0 Y) t ?
globals
/ G+ y+ x2 M4 v* ]5 ~[5 A0 \0 p7 Z# T9 f2 K. K" O
max-grain ( ~8 q+ p; H- l
5 t+ U+ |, ?" B! a8 z- w]$ ]1 ]+ N# p3 ^1 L- X7 \7 i
0 T! s; K6 I, Qpatches-own5 z7 L" u& r+ H' ^
[
; s$ A! @) ^" }5 W3 H' C$ A grain-here
( n+ N) h2 v3 P0 |- S9 T max-grain-here
5 Z3 z; i! J8 K] y& R z8 b& M4 |; U& n
+ ^+ a4 S4 m9 |4 @turtles-own
+ G0 U: _1 y) r6 c' x- p# S[6 r2 [1 v* n8 I& }
age
! |# t, |; c% g% a* p wealth
$ k0 F+ ~% Z! c4 E1 N life-expectancy
& V8 T, v$ G* L: W metabolism 9 v- T+ u: v7 f: W% s
vision, W2 j: y( L9 ~; |+ e5 ]# E# D# z
inherited * E5 O, d0 j, H0 f
]
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% g3 Z( L& d" s( V( U- G. d+ k, `$ F2 i' r7 ~
to setup3 Z, m9 ~& U8 U# D! V
ca$ t" M: B7 ]2 |+ N- s* K& C
set max-grain 50. l8 |6 Y% f; U$ f" \
setup-patches
- Y+ Z# j3 E9 b3 }7 d6 f setup-turtles
, @5 u; f( Z; i8 M$ E- d% {1 k: a setup-plots4 c! s D4 k+ e! ^6 _
update-plots
1 a0 R, w* Q$ N3 p" |end
& p3 b! L5 X" {1 ]to setup-patches
4 }- M }: s# l9 j, t5 x ask patches0 C3 E1 Z( `+ [+ F* V
[ set max-grain-here 0) l* F0 d0 ~1 [, p
if (random-float 100.0) <= percent-best-land
6 f; k" O3 _8 a [ set max-grain-here max-grain
0 U1 W% H: L8 d; c& @ set grain-here max-grain-here ] ]
3 {1 T3 o& V- {. A0 Z7 c repeat 58 u# q* w; x! e; i# x- X+ E! a
[ ask patches with [max-grain-here != 0]7 i# i I8 [# ^4 ]
[ set grain-here max-grain-here ]$ ?( Y/ ^* ~5 p/ {
diffuse grain-here 0.5 ]
, O1 v4 J3 b( p0 R1 x repeat 10
* l& P$ F3 M. @$ v3 ^5 s [ diffuse grain-here 0.5] ' U5 Q K% c8 ^ N+ W- F. l3 b
ask patches* k u. d5 j; ?
[ set grain-here floor grain-here
; e& J2 _; A5 J set max-grain-here grain-here ! I( H" S2 x3 l) E
recolor-patch ]
* p( V: ?1 z/ B4 K4 i, Z% [" `end5 a1 ]4 W& k! _& F/ B8 R6 O
to recolor-patch ( `2 v( Z- E" X8 Q1 Y
set pcolor scale-color sky grain-here 0 max-grain
! B9 ^) \4 v: E, t' n, O2 Lend8 k. R; ^7 h2 b; n
to setup-turtles/ ^* u- D, |1 t' z& G4 T; i% P
set-default-shape turtles "person"
. H0 y* h6 k3 Q& C5 ?& ~2 h crt num-people
* L* R3 |) r4 D- u! ^2 O [ move-to one-of patches . h+ W- Q1 w. o
set size 1.5 2 _+ n- R, ^% b4 w$ E
set-initial-turtle-vars-age N- |( Q& N' l: B/ s6 X% p
set-initial-turtle-vars-wealth5 h8 D) _0 D% ?4 M# i
set age random life-expectancy ]+ R; E9 T- @, Z! }: L5 |2 J2 T2 V
recolor-turtles
( ^: s$ @$ @( g7 d# Bend
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3 J+ F5 ?% L9 b' [( U- e& jto set-initial-turtle-vars-age: J, a) I1 F8 U2 H8 Q
let max-wealth max [wealth] of turtles% C2 K/ y# O# g0 v1 D
# f }( U' f! H1 v+ F" d2 n! @ ifelse (wealth <= max-wealth / 3)
3 J& @2 X7 `) E* C$ { r; A% s4 r [ set color red
( N3 ~! A; U# H& v" Z. U( C set age 0
1 {; c, b+ L' s$ \ I6 | face one-of neighbors4 9 J2 p/ {4 D$ P1 q# x4 q( `% u
set life-expectancy life-expectancy-min +
% l' l+ ~; ^5 T- _0 p( I0 f random life-expectancy-max
4 F. O1 q ]" T4 ~ set metabolism random 1 + metabolism-low* S/ }, H% a$ v& s, K
set wealth metabolism + random 30
4 a7 N4 M4 L7 z2 {; |. t1 b set vision 1 + random max-vision
# G$ {: L" v' U& N) B set wealth wealth + Wealth-inherited-low ]
3 x; g2 l1 h' J" G3 P9 t [ ifelse (wealth <= (max-wealth * 2 / 3))# S; r; f% f( V A) c. U) K
[ set color yellow + u. Y( S3 l- k2 O }
set age 07 R) W% |! K% `
face one-of neighbors4 ( W( g0 k% y) k" e! M
set life-expectancy life-expectancy-min +
) W U# }% H6 s1 t9 P$ \' Q( Q: {# D+ C random life-expectancy-max + 1
. f- p2 K+ T$ ~! Z set metabolism 1 + random metabolism-mid
7 u4 h3 O. H5 u* o- v set wealth metabolism + random 304 q) ?4 e( A; X/ q; S. ~# S
set vision 3 + random max-vision
}: {6 N* ` J( o$ y m3 j set wealth wealth + Wealth-inherited-mid]
& z9 [8 a# C; f: H7 \. N3 ]6 u [ set color green 4 a* w9 i4 [) \ Q0 i
set age 0
0 C* v) ?8 V3 J% i face one-of neighbors4 % q) y6 e, P0 h4 F! V: L# r+ d+ Z$ v
set life-expectancy life-expectancy-min +
+ b+ s0 C+ K) b8 {- u$ M' a* ]7 J random life-expectancy-max + 2
/ m9 W. T5 } H& C* p set metabolism 2 + random metabolism-up
# B5 z2 l( M& T9 d \, B set wealth metabolism + random 30
/ H/ l# k4 W8 X3 \ set vision 3 + random max-vision$ ~2 {) A# }( G, c* T
set wealth wealth + Wealth-inherited-up ] ]
9 z( d/ N) h. |) i* T/ f# N
+ u, O3 _4 |$ g1 t* Wend
; x. }3 e5 `9 hto set-initial-turtle-vars-wealth/ F. d' W1 V# i3 g0 C; I; H1 ]
let max-wealth max [wealth] of turtles$ n1 }1 {) W" p' Q0 A+ y
set age 0
1 }& z5 _5 e2 z' C face one-of neighbors4 0 }- q. r, a( E
set life-expectancy life-expectancy-min +
+ S# H( O9 P4 a2 ] random life-expectancy-max
# ?, N2 _1 d: t; @$ e3 ?+ g set metabolism 1 + random metabolism-up- R. W- `9 k% _% v* H
set wealth metabolism + random 302 b, F% X/ @: @* i# l
set vision 1 + random max-vision
2 ], I( h" n: Y' R# Oend
! f7 B3 R0 ]) mto redistribution* ~( j/ B' Y( t
let max-wealth max [wealth] of turtles; ~4 J2 ^ x! E
let min-wealth min [wealth] of turtles( B5 a- R1 c* x( |$ r- X
if (wealth <= max-wealth / 3)
0 f% a6 X* W1 _4 A* l- y [set wealth wealth + Low-income-protection ]/ s$ Q% c7 E& @8 r
end. C3 `- X* @' m
1 ~) @ n9 G) A8 p! }to recolor-turtles) r: T! e, q3 `% F% z
let max-wealth max [wealth] of turtles; s0 P) P7 v, M1 I, P: l
ask turtles
; n' u9 f9 F* C# R1 n/ ]; V/ Q1 a [ ifelse (wealth <= max-wealth / 3)
k! R; S: l) `% I: o- v7 C [ set color red ]
" b& K4 \, p1 _0 N5 c [ ifelse (wealth <= (max-wealth * 2 / 3))4 L8 Z4 O% w6 Q) c3 o. a& Z6 {
[ set color yellow ]
: D( @4 ]/ q8 v1 W+ u; s [ set color green ] ] ]
`, ?0 e0 E1 f' x1 z/ a1 j ask turtles [ifelse show-wealth?
! E# A0 ?* V G [ set label wealth ]' s; Y# a; B( f& s o7 E
[ set label "" ]]
% j. P2 v8 m% n& j- h: \" `end
' w; |$ U @3 ^' U6 @! Y. f4 ^
. @2 {$ T" v& g* O* q* h& kto go
' E8 G9 g7 b& J c& t ask turtles' G3 N1 R2 v6 W/ C1 b
[ turn-towards-grain ]
# i/ M; u @7 T/ @2 [ harvest
4 K- q0 Q) i, f6 {; A6 U ask turtles6 S, `1 J$ X) ]
[ move-eat-age-die ]+ d; U6 J; Z3 l4 f3 b
recolor-turtles# a2 {5 h$ B1 [. X
if ticks mod grain-growth-interval = 0
* B i+ I; Q4 @$ v0 V# r, T. S [ ask patches [ grow-grain ] ]
' k$ I4 L( t+ g7 n( L
9 g9 |2 H! ~( g if ticks mod 11 = 0
- j# [) R$ O, n, M/ h [ask turtles
' M3 s% `$ b" }2 b. y( f! w* n; f [ redistribution ]]
; |; L7 x5 ?; I" J% C2 r if ticks mod 5 = 0
& n- l- X0 w; Y [ask turtles3 ~3 w( u2 e! d" ~% B4 }- u- k
[ visions ]]6 o* W1 L2 ?8 G4 N
tick
) P# \8 \% P4 ]$ K, n& q j update-plots
- X7 ~' o0 p( y. Q" [end
) i( ^! I9 c3 L) t. B. @to visions. R j" f6 h' U* J
set vision vision + 1
2 O$ z; D3 _/ Z. p: S' [end$ I- K, K3 a' ~" n2 s, F& k0 s9 |
6 Q7 {: H- v B) t& n% P
. o) _- q1 I: X% l1 B1 D; R! E8 z, M8 x
to turn-towards-grain . k3 s9 W! F6 |2 T$ |
set heading 0
) W- k3 n3 f( s1 g( y+ E let best-direction 0: {8 x1 I+ |% n- c; }
let best-amount grain-ahead
/ Z; V. E, ^; e: ]% ^- N9 i set heading 909 L+ C6 G8 t1 N1 q* N/ e3 {# W
if (grain-ahead > best-amount)+ e8 O0 u- g5 i( T& G: t* Q' a
[ set best-direction 90
( k! c0 I" [6 I6 O8 G1 [# ]% h set best-amount grain-ahead ]- E: O- i( q* t3 \. a
set heading 1803 D2 U- m& Z% h9 y$ `: S
if (grain-ahead > best-amount)8 Q5 T* q: i0 [$ a! A
[ set best-direction 1800 g+ e, O7 u' `+ r+ q. F
set best-amount grain-ahead ]9 p' N7 O9 b `6 O9 ~2 i
set heading 270
" h& Q" V$ \/ K2 W if (grain-ahead > best-amount)
* ~( t! ?0 s; d6 ]! p [ set best-direction 270
4 I! |. z: P: H; x1 J4 R set best-amount grain-ahead ]
% a: R( o; T: ?* ^ set heading best-direction
5 z4 a* T4 W! }# N- f7 Vend2 @7 I6 k+ o, K! [; H5 P: c
" N2 T* S, H3 Q" U
% t: k# ]* u$ l
to-report grain-ahead
7 Z, O5 H5 W v) E let total 0
+ J* ~) g; @& i6 O% m let how-far 1
0 u6 D- F% x# b; q( H repeat vision( B% H! b/ p) P4 a$ a: I: }$ d3 f6 p
[ set total total + [grain-here] of patch-ahead how-far. _$ a) M1 @) ]
set how-far how-far + 1 ]0 }3 m; g. O2 R- k
report total. f- N0 ]/ A& H4 T" w
end
6 | n- [0 b- B
" E, Z& k5 V6 ^1 R4 Lto grow-grain
0 j& l& W+ @' Q3 W if (grain-here < max-grain-here)7 \1 V8 h; ^& g1 v# k
[ set grain-here grain-here + num-grain-grown8 ?" o1 h) ]. }" X1 q+ y! }
if (grain-here > max-grain-here) " Y& ~2 w- ]$ `3 L
[ set grain-here max-grain-here ]/ K) O# i0 D% R, i! g
recolor-patch ]8 A9 ?* b8 A4 l+ b" s
end2 ?5 t9 k6 y% R1 ]' y/ N9 e- `
to harvest3 E; b- q1 z, e1 r- [- M7 ^
ask turtles/ Y* V% ?0 m8 A: y) H& Z: C C
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]9 R0 `0 B& I6 J; G
ask turtles
( @. L8 Y: R4 d* s [ set grain-here 0# g8 y$ S0 Z7 Q3 n+ O
recolor-patch ]9 n4 o( C8 { }
# s. `4 K/ x5 D* l1 |; t
end
; [6 c6 p4 G" o& R
' t0 C/ k) V" K1 Cto move-eat-age-die
# y1 K1 ?2 q; t( @: Q fd 1
8 P4 g% N; x. Y* [ set wealth (wealth - metabolism)2 y3 K( {. G4 W8 d; }3 [% l
set age (age + 1)% }' Q( _6 o4 ?+ b' e
if (age >= life-expectancy), k% t2 R6 R7 |1 c% K/ S, ~7 V/ }
[ set-initial-turtle-vars-age ]
0 m1 h9 J, o/ s+ L if (wealth < 0)
, u& l/ G! O! `9 j* _5 _& n- B) d. T [ set-initial-turtle-vars-wealth ]
; T6 j; {, Z4 K! @3 q- K
# U9 u. R$ D& }; b& xend- l, x! k/ O1 W8 z8 N7 u
0 c: r0 ?' X2 g( W* e6 v8 e5 {9 `6 v; [5 s" K( ?' s, e4 K: h$ Q
to setup-plots
, Q5 ~/ V( m3 W# ` set-current-plot "Class Plot"9 y) h& } p( H2 V( P; e+ d' [
set-plot-y-range 0 num-people
?7 Y( E P# u4 w set-current-plot "Class Histogram"
9 L( ~( R/ F$ B/ ?$ i set-plot-y-range 0 num-people" l+ B! [# T/ g; Y) D+ q. U* F+ n
end
3 q$ \& w9 l1 t, c2 Q$ i+ |" L3 l& P% v# s/ Z. C
to update-plots
, o4 @9 m) ?5 w- a _ update-class-plot/ j0 _9 b, `' R9 b5 ^" a
update-class-histogram
/ z4 T$ `5 ?7 [: K4 D update-lorenz-and-gini-plots
+ z/ [ {' d8 Q/ B3 Cend
" ~2 l. j) J# y5 R% F) Y
6 g9 ^5 P. |! _& [8 ]% c9 rto update-class-plot
9 i4 Q0 ~" }9 Q4 A8 g set-current-plot "Class Plot"2 Z; g' h9 Y$ d
set-current-plot-pen "low"# u/ c2 ?7 C$ C9 ?7 r$ B* T
plot count turtles with [color = red]
& _4 ^; q/ B* L0 }: Z set-current-plot-pen "mid"* s! L( y& y9 j- e
plot count turtles with [color = yellow]! U( r: |4 s7 V
set-current-plot-pen "up"1 \: Z9 W4 p; M' o `4 W3 p
plot count turtles with [color = green]. a6 j4 I' b' d4 n- O7 c# r3 }) \
end
, t% \3 R3 [6 j+ Q( B' g8 i
: b$ [ y( `( `. @to update-class-histogram* J3 J& w/ T1 `
set-current-plot "Class Histogram"2 b8 I8 ~' ? F9 B( |! F
plot-pen-reset `( m: P; a1 P% T# O
set-plot-pen-color red& B0 P" @. P [) G
plot count turtles with [color = red]1 X- _$ N2 Z0 W) R1 ^
set-plot-pen-color yellow& W# k( P2 R9 O, r+ r
plot count turtles with [color = yellow]2 o5 d/ a7 z, |- H' l N4 x
set-plot-pen-color green
' f/ v* \) t3 b2 G/ b2 j3 S! I plot count turtles with [color = green]
; `, @8 n1 n {$ t3 q4 rend
& M4 w/ n' {( ?% Uto update-lorenz-and-gini-plots
* n) f1 }! I5 K set-current-plot "Lorenz Curve"
7 C0 b+ I# \5 \) I# `0 R clear-plot' ^) K! O! r, I8 E, Q- ^' d3 u
) P& o8 o- n: Z* O; f
set-current-plot-pen "equal") q, ~! s, ?( I3 C: [; {
plot 0
, `7 o: q- Y; H$ @ u plot 100
- U! i, w! K* `& N
/ X% v. D; f+ u# C2 f2 H5 J3 i set-current-plot-pen "lorenz"- ] [7 b) k* y7 x' y7 M" c
set-plot-pen-interval 100 / num-people: T% }9 \& ?6 _$ }$ u4 P. q
plot 0$ @" ?. d, m' ^
( H7 |; L/ D+ U* V/ { ~! Z
let sorted-wealths sort [wealth] of turtles
& p" Y* c& `$ W" H$ @ let total-wealth sum sorted-wealths
% `! R( X3 N, H let wealth-sum-so-far 0
3 Y+ m; n' Z# x# i" R" q$ P$ U let index 0, x# O4 k8 o% U3 b' T4 p
let gini-index-reserve 0
9 }9 u- f! a4 p1 }6 l& S0 H/ L, m/ G/ n4 k/ n0 i, X) g: L! D
repeat num-people [6 c5 u$ G: z# |+ _/ d% L
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
4 W$ i! I8 e# ?; J8 h plot (wealth-sum-so-far / total-wealth) * 100
: z/ j6 q l8 h# q set index (index + 1)
# u5 n5 i. f8 C* l/ @4 h# U+ X2 y$ S set gini-index-reserve5 ^! m2 t6 v0 }) _( \# p
gini-index-reserve +
$ I) t. J( `: K' f! T4 l( K2 r (index / num-people) -
3 \' f$ R' b b) @7 X/ u (wealth-sum-so-far / total-wealth)
, S+ {" @" F$ u ]
2 c1 `5 v% I; x+ z' Z7 s. R6 z* }9 q% H3 ?
set-current-plot "Gini-Index v. Time" z' d1 a' {; Z/ [ X/ p. K# w
plot (gini-index-reserve / num-people) / area-of-equality-triangle" ^( n$ ]0 |! X
end
0 X% d0 z$ L! k1 r( {' t/ j4 Cto-report area-of-equality-triangle" @! K/ ?0 X' L6 r9 _: p$ s# o1 {
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)2 g/ Z9 {8 R! z5 a: x! K% Y) A
end |