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- r3 h; s. Z: [. X5 C5 r! e( z: j
globals* P9 W8 z* Z& r) @4 H# s+ q
[9 R1 V& F8 O2 Q( T, ^
max-grain 3 K( y1 O$ i3 T5 a
7 E5 C, q0 }( F; t7 z
], r6 V0 z9 P x: a: z# A- d
1 E! c5 z4 f# S6 O, i
patches-own
& l( z$ z' i/ Y7 _7 i/ O[& U0 T: R3 O& P, t) s
grain-here + \7 [) M, j G
max-grain-here 6 [% A2 o0 L4 i/ {8 d1 U
]. p# O3 A& t4 O
* W* P/ o0 |0 Z" o, R( Z5 b }5 fturtles-own
* s% O. o5 j7 B3 ^) o' ?7 y: x4 C* `[' X5 M+ V% b7 e% Z7 c) \2 f! M0 K
age # v4 Q3 G% N- a7 a1 Q6 d O
wealth
- ~" ^5 ], s5 g5 v" V life-expectancy 9 o; X2 j8 g p0 F, n# y& Q
metabolism
$ Y9 h4 s1 [0 [, I5 z/ a* r$ B vision4 u* g8 R* X& {2 R, \9 K
inherited 8 _( S0 y! |6 ]- B4 `
]
2 n" o" Q, Z7 a
4 v& e# a0 q) f' z w4 J( z0 L0 w
to setup
7 p9 K6 {! f" O ca
& B# x; V) R$ a& C set max-grain 50& [4 ]6 H5 N6 ~8 T8 s: S1 l
setup-patches
9 t/ z6 I7 z! K% ^0 m ^ setup-turtles p* u, X' R1 s( b; b* E
setup-plots3 E2 _2 r" X) e9 B( [0 v% b' k i
update-plots/ D; ]2 w( J6 h4 @/ i4 A1 D2 r( b' M9 A
end9 B+ Q* Q# l7 L
to setup-patches9 h2 d8 g4 X- W# q1 X
ask patches( }, M$ O: q9 W, e
[ set max-grain-here 0% | m- j% v! _& c! {
if (random-float 100.0) <= percent-best-land& z1 @9 |: d. g' n' E
[ set max-grain-here max-grain8 P% g, e6 U% x# E- k7 q8 f+ l
set grain-here max-grain-here ] ]1 ~1 v% o& r K1 S4 U( Z4 m: P
repeat 5/ J+ b% i, Y9 V! n! w
[ ask patches with [max-grain-here != 0]
( {1 }7 G% r% ^+ j9 T [ set grain-here max-grain-here ]
! B) ^/ f" k" f7 z diffuse grain-here 0.5 ]
, B3 N2 }7 e8 d repeat 10
5 y" P( e3 I. K8 } [ diffuse grain-here 0.5] 4 P9 ?5 s4 A. r. X/ S. M
ask patches+ Q6 ~- b4 a! p8 L. y1 D8 Q
[ set grain-here floor grain-here + g! _; ?; }7 R9 K5 Y
set max-grain-here grain-here 0 @% g3 ]. f4 ]; @
recolor-patch ]
9 O& U6 k; ^# S$ P- y' E; t! M: r. \end
5 D5 P' B; C" d# m2 b, {6 `7 zto recolor-patch 1 H @ }$ Q4 P" V# j
set pcolor scale-color sky grain-here 0 max-grain+ o5 X; v. d$ J' k0 Y2 @
end! m* c' R% K3 ^% F
to setup-turtles
* x# z' n! r) v) D7 ]9 `. L/ q set-default-shape turtles "person"5 P; M- J. K3 ?3 ]
crt num-people9 o% |" ]( \' R8 h' k! E$ e$ E( N: |* g) Y
[ move-to one-of patches
! ^7 ?% C' w) p* w4 x1 y0 o set size 1.5 Z# [* Z' n. l1 a: @8 M
set-initial-turtle-vars-age
! X4 g1 I* D3 V: Z! ~, [2 z set-initial-turtle-vars-wealth
. y* c. i3 q1 G5 C* [ set age random life-expectancy ]
6 j3 K0 I" V4 E% U+ \ recolor-turtles; n: X/ P9 i' V2 i- |
end3 @! p1 F* ]8 Y I _: ]2 J3 l
! i- g. N5 a, ?# }3 }3 N4 pto set-initial-turtle-vars-age0 j, C# ]& k3 G% z% Z+ ^5 |
let max-wealth max [wealth] of turtles+ |$ h9 r0 q% k6 r8 d: u
# K& N( ?6 C% r3 E! ^. f) j0 x ifelse (wealth <= max-wealth / 3)- n/ [( Z4 q$ w6 y6 L; J4 R L
[ set color red
4 {# X. |+ r" \4 r. @, } set age 0
5 l( N* g2 X% M* v7 R/ ^8 F face one-of neighbors4 $ c; u3 T2 ?' l6 ]' Q3 n2 V7 u+ r
set life-expectancy life-expectancy-min +
3 x+ G4 r5 d4 ~ random life-expectancy-max * e, N s4 X) M/ ?; }
set metabolism random 1 + metabolism-low
% ]+ U7 C' T1 \4 j! o: L% J set wealth metabolism + random 30
8 i) i6 g8 r, T. ~& E. X set vision 1 + random max-vision x5 W% b' V% W
set wealth wealth + Wealth-inherited-low ]. j9 O3 W' K9 n1 F0 Q/ H
[ ifelse (wealth <= (max-wealth * 2 / 3))
& Z3 m- Y7 j2 o0 I9 D% ^8 j* w# ~ [ set color yellow
; f/ P7 j2 \; G/ o) R0 l) @& {# Z set age 0
5 o4 m9 `$ N0 X' }0 I/ f$ W face one-of neighbors4
) T9 u% y& X, ~. q, V6 I) f# A G2 | set life-expectancy life-expectancy-min +* i/ l7 k3 Y' I3 m* N; V
random life-expectancy-max + 1; ^' d/ [& h8 z$ a f
set metabolism 1 + random metabolism-mid# L0 J; f- t+ S2 E3 R
set wealth metabolism + random 30
$ d, z3 I# j' C, S: z set vision 3 + random max-vision
: `5 D$ Q% j8 D& P set wealth wealth + Wealth-inherited-mid]8 i) h/ k* d W" F2 t
[ set color green 2 [9 O4 P- m5 w$ P' `& u
set age 0/ s4 t/ Y9 w1 r. F4 f
face one-of neighbors4 7 \* P/ C5 x3 r+ l: M5 L
set life-expectancy life-expectancy-min +
; m* g+ q# x& X; w random life-expectancy-max + 2
& H2 z4 V! R2 O. _ set metabolism 2 + random metabolism-up; E3 E' O! L3 {( n) e: `. j. R
set wealth metabolism + random 30$ x& |% G, D4 S
set vision 3 + random max-vision
( z4 P: U- E0 X# T set wealth wealth + Wealth-inherited-up ] ] 2 _; q2 j- M3 O8 ^) f
0 V1 _& y! m3 K+ Tend9 l+ O0 R! b" D2 B4 T" y9 F
to set-initial-turtle-vars-wealth9 ?6 c3 s- ]" d/ n6 d
let max-wealth max [wealth] of turtles0 J( e; d4 I7 k$ W4 }" `# F3 O
set age 0, X; t7 b2 Z9 g1 v
face one-of neighbors4
# B5 [! \9 F6 j, ^; s, ] set life-expectancy life-expectancy-min +
1 b# y* C' N/ v* J4 m random life-expectancy-max ' d$ J6 X) x5 h+ Z' g; I
set metabolism 1 + random metabolism-up8 F' ^* j5 D8 K% z
set wealth metabolism + random 30! V! J# ]) v# t! @* d
set vision 1 + random max-vision & f0 ?0 T' H! H2 |) X7 _/ W8 p
end
0 ^: `# a4 z* [/ z- t! rto redistribution7 T7 j7 ^# V E9 W6 ^4 j
let max-wealth max [wealth] of turtles
% ^' r; @' t9 e. llet min-wealth min [wealth] of turtles
j6 @, B" p, Y$ fif (wealth <= max-wealth / 3)3 [' |8 @' R9 W7 A
[set wealth wealth + Low-income-protection ]
& D4 K1 E# B5 A! p2 |, o: i6 ~$ G hend7 g2 u% i6 i4 d0 K5 h
; }4 h$ V4 t. B9 }' _- y
to recolor-turtles) G! x" @. K0 m, x- a, v
let max-wealth max [wealth] of turtles6 H; |* j0 F7 h4 \% w8 f, i6 C( [
ask turtles" b* j0 P) b) T Z$ Q2 }* v0 M
[ ifelse (wealth <= max-wealth / 3)) I3 a9 P' E. [% B
[ set color red ]
: i* \5 ^5 I+ a. ?) K [ ifelse (wealth <= (max-wealth * 2 / 3))
0 S, c$ m' }2 h' |# y/ Y [ set color yellow ]9 q- C8 u/ {1 ?* U
[ set color green ] ] ]
. x/ X; [* C! b3 B9 ? ask turtles [ifelse show-wealth?
. |3 ^# s' s" l9 s% X" } [ set label wealth ]/ z l" i* \7 W% C. s/ A9 l7 D
[ set label "" ]]+ m0 ?0 j# r+ P5 v% w
end) G+ Q6 T" u8 _2 i% v
6 I: u7 p: I# y! s! c3 M1 A
to go1 d. e" w! x, @
ask turtles
" `$ h8 e4 F& I4 Z: _# n- P [ turn-towards-grain ] . x$ s4 b6 M {" v- [$ H
harvest
$ N. X$ }7 k6 ^" d ask turtles
% L; b( \. Z: h6 w* |- R [ move-eat-age-die ]: ?, e/ c3 q- |" Z( E
recolor-turtles7 X8 J. h4 `: E/ D- K' A
if ticks mod grain-growth-interval = 0% ?0 s6 w2 [$ E% b; B1 t
[ ask patches [ grow-grain ] ]! C0 C# R* A( O/ i9 Z9 ^& \6 x' _
. Q) S4 D3 N2 p/ B& {; c. \1 D if ticks mod 11 = 08 g x2 N7 z0 t! V0 `5 d& p
[ask turtles& f; M, F% O6 n2 B4 A
[ redistribution ]]
3 l) m! g3 m" }- s if ticks mod 5 = 0
! l: X/ i# [/ o$ h4 D [ask turtles
# e. J1 J6 W; R- Y$ W1 b2 i# l [ visions ]]# ~) c* S& b; w
tick$ V7 K/ `0 [5 \# p( ] W: y$ ^
update-plots
- g8 a, |! s' U- ~' X: C! gend% n2 H1 \' c& V; f3 g
to visions7 _5 p) F2 a5 X8 l8 @: h
set vision vision + 1
& l0 c# Z: Q6 j, iend- Z! z) ?; j2 \+ i5 w8 H7 Z# ~0 a1 `
- e# d! }, M2 ~* H+ r/ Z
( t) m. y. v4 k& R% Y( O3 f" m4 u+ Q1 d1 V
to turn-towards-grain
% Q- X+ z9 A: s0 F. S( ? set heading 0
8 d( D5 J1 h: `! [3 {4 _ let best-direction 0( G: p: p, A3 P) l+ x! S7 E' {
let best-amount grain-ahead4 p, V0 w- ^3 c9 o; R4 N6 V
set heading 903 C( W% E6 d+ o" r7 S
if (grain-ahead > best-amount)
; r5 g' p5 L) g! V& ` [ set best-direction 90
. ^6 u- R! T/ M# o/ E: Y set best-amount grain-ahead ]+ G: O5 R+ ]7 U* ~
set heading 180
' n3 F$ `4 F) W* m if (grain-ahead > best-amount)3 F9 @, V3 z: F, F5 M( [( F
[ set best-direction 1804 y4 S; D# p9 v3 w. w
set best-amount grain-ahead ]
6 U6 K) T' E1 K5 K1 ?: R# P' R& t; @ set heading 270% N5 y, l/ z8 T0 B$ Y3 n
if (grain-ahead > best-amount)$ m, h; l* V9 r" a k
[ set best-direction 270
. ]0 }$ j% i7 U f) m0 V9 f set best-amount grain-ahead ]
) e! _0 {3 U, u/ w+ v4 h set heading best-direction
: z' H- T' x/ v/ B. Rend( ^3 Y; @ D7 \1 j- I: F
5 f0 V- m% z( @- F* u
8 V: i3 k: @4 a# u; U4 ~
to-report grain-ahead
& {" a/ J+ D2 A4 u$ ? let total 0
7 a& I; P+ r) k9 R4 T" a: d( X let how-far 1' Z: |. ^3 U) K# C0 b1 h2 ^
repeat vision: J+ I% |1 G9 _) s( L' L# A
[ set total total + [grain-here] of patch-ahead how-far3 ]$ ]6 d1 o: Q) r
set how-far how-far + 1 ]
+ ^% x7 q8 j' a2 _8 d* E' r report total
5 d7 U# ?+ ~7 R# Iend
) k/ |0 w a3 M3 w
- s$ s( k$ p, \! S* n5 }6 @to grow-grain " c( u( O( K+ G
if (grain-here < max-grain-here)% A5 Y7 {) T/ o5 g# h0 s$ A1 j
[ set grain-here grain-here + num-grain-grown
, I- b# K3 c% i# b if (grain-here > max-grain-here)
: b0 T: z4 z3 F [ set grain-here max-grain-here ]
& @0 f8 p5 H/ \& y5 |) W: k' D recolor-patch ]1 }1 g8 U6 T( X4 A) t- p/ o8 N: g
end; j; X; `; o4 A
to harvest
6 I; t' ^; O9 A" |0 }; D ask turtles: j( w) V! K/ ~* N; F& Y
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
0 q' c' X9 U' c$ |/ K6 D+ F ask turtles/ `$ ^/ T8 w/ Z8 p0 G5 |" Y
[ set grain-here 0
; }/ ?8 U0 z. Q$ V1 ?/ Z recolor-patch ]
Z2 c/ ?5 y$ ^- j" A/ d
1 N/ T% @2 p$ k [" }end5 |" ~ Z" f+ b$ b P k, k7 H
8 X4 m/ I1 _ ^5 U0 n' D" H5 d# b
to move-eat-age-die
5 A4 Y9 ^6 B& }2 q7 F* e+ [1 F fd 1( z% I! s; g5 f4 U: q
set wealth (wealth - metabolism)
/ H+ y4 m& Y; \) m4 U6 p/ |, g7 _* X set age (age + 1)8 n, Q: u H- k/ Q
if (age >= life-expectancy)
1 `# ~+ O; \, N: q [ set-initial-turtle-vars-age ]. n2 I) g& W4 L
if (wealth < 0)" R4 A0 _' k4 s( A6 d" T3 R9 L
[ set-initial-turtle-vars-wealth ]! H0 q" h+ \. c: G" l$ W
9 i0 w* r! ] n8 g# M) @end+ F6 H' ?; ^# Y O3 E( O# S# Z
9 j9 i" z, b9 B3 f1 Y
* Q8 B' x5 p8 W ^* @
to setup-plots* }; i7 R' i. Q! ~; ?
set-current-plot "Class Plot"
: w' `% N. P0 L set-plot-y-range 0 num-people3 v! C$ p8 R2 \) Q3 n
set-current-plot "Class Histogram"* q5 t, j$ U, {7 i* b/ n
set-plot-y-range 0 num-people
+ f6 t' c5 @1 h) ^5 \end, t1 c5 A; }4 ]9 Z$ c
; L- w* ~% A3 `" k( h
to update-plots
& r3 @' {/ h9 P8 S* y update-class-plot. W! w9 N# j, o+ k
update-class-histogram
4 w# ^: d2 r; y9 i# L update-lorenz-and-gini-plots
4 { \9 L& f, C8 l3 a6 P3 Qend
& H! K0 N4 f: t6 W# l% Q
( |. N+ d5 v( `# lto update-class-plot) K+ _! L- W' ^- m$ X0 P
set-current-plot "Class Plot"
* w8 s" _, N, C6 N) a* b set-current-plot-pen "low"
" [. e/ n8 l( X" g& h plot count turtles with [color = red]$ \4 O9 a2 l* z* O7 {
set-current-plot-pen "mid"
/ x, L4 p8 `) _, Y+ s- H! H$ _ plot count turtles with [color = yellow]
: \: Z/ K" ]6 U5 T set-current-plot-pen "up"1 @" t2 ^2 p' s0 h5 X1 ]3 O4 U; h
plot count turtles with [color = green]6 J' i* e+ \* b- Z1 D4 a- K* F5 ~/ _% [
end1 b! A5 u3 k- s' K2 M& k- Y
# n/ @% D, n/ y7 V+ U' xto update-class-histogram) L% y$ A) Z! V: n- l/ t3 b
set-current-plot "Class Histogram"
, Z3 Q& e4 Y/ @ U( F. N0 v plot-pen-reset L$ X7 L( o' n# W% o# v
set-plot-pen-color red. Y1 R; x+ a$ _
plot count turtles with [color = red]: E9 m; i2 ~- \: T% E3 B: ]
set-plot-pen-color yellow- V4 P# \" [ S, @6 c) f4 F
plot count turtles with [color = yellow]8 Y B) o9 C- y# |
set-plot-pen-color green. U4 g- i5 N4 A$ D9 k& W
plot count turtles with [color = green]: {8 }) Z$ n) ]2 s
end
6 R+ |1 v" B6 B2 Dto update-lorenz-and-gini-plots; \$ z2 y& _+ [8 h
set-current-plot "Lorenz Curve"3 L$ ~* y( _; V
clear-plot7 i- M" n6 ^4 }# `$ k! t
+ h/ [) R+ e$ S% T4 B' v8 M1 V: Q( s4 @! C set-current-plot-pen "equal"
- |& L6 _, h) s2 e& t plot 0
9 x7 @$ ~: j% w; _. H( s; T plot 100
% ^. u+ ~; ^2 `, f% B1 r
: y3 X" j$ @7 V! V! v% E set-current-plot-pen "lorenz"
! k4 I1 q! Q0 |. C; W set-plot-pen-interval 100 / num-people
+ T5 g G- T! A8 q plot 0
" Q/ y/ U/ h, H& m% [
2 e+ }# q, ?# K! y" v3 R2 S let sorted-wealths sort [wealth] of turtles
o# k$ ` d; x4 D4 E& G5 o( e1 w let total-wealth sum sorted-wealths4 V. S2 ?; |8 s8 u- |) ^- l) [
let wealth-sum-so-far 05 k+ v( [! H/ y7 K' M& E
let index 0
: {1 H/ ~/ b8 J# c1 |- i2 N let gini-index-reserve 0
2 v3 i2 @. O6 R( _. y
6 x8 s/ I5 \) {! j/ j7 C9 h repeat num-people [7 |" z3 p$ f, P$ o* ?( L4 J
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
4 \- u6 e. U+ e plot (wealth-sum-so-far / total-wealth) * 100
) g2 G& ^. ]: N0 U, z set index (index + 1)
+ d+ C8 `; n) r' J set gini-index-reserve8 e8 \- n! {- f
gini-index-reserve +
& M) l2 C4 ^" B0 P: t. q" w (index / num-people) -% i0 x) J. j L3 }3 X
(wealth-sum-so-far / total-wealth); P8 {" J. s+ T8 j) T' f a0 G
]
( w1 k% O; K1 A: o# l
6 [4 K1 E' p5 |& }3 O set-current-plot "Gini-Index v. Time"
, Q* F2 V6 S4 D( ?6 D3 o plot (gini-index-reserve / num-people) / area-of-equality-triangle( S$ {$ h8 D* r9 U, h( _8 @8 z
end
1 b/ b4 o$ w9 Uto-report area-of-equality-triangle( x2 u2 h: E; \9 k7 H) D# f9 a6 v& I) R
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
# i4 W) ?, U) P5 T% N. Tend |