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( }; |1 Q1 v$ i' R# R. f/ i6 C' D
globals
9 y1 T) c9 W8 j! s: o: ~[- y3 _- {, f4 i% s
max-grain 9 ^9 i" X* r4 M4 p( ~* k3 J- D
q3 W- q6 s2 A3 R]% W; G8 G% \7 y. e7 j
@! l7 r( Z# Wpatches-own
[' t# R3 N$ O2 Z" ?: O[
" [; d- }9 J: q* I+ z( v s grain-here
" c5 f: H" Y4 v3 q0 ~% @ max-grain-here # s t0 h! K8 F, o! y! d8 h
]$ J5 P E, u+ _, \% @9 [4 U2 T4 d
0 w4 ^* x4 i/ oturtles-own
$ J+ i0 I+ ]0 T8 x. K[6 i! R# a& X+ c3 q. f
age 8 Y) B) m# x+ d) J; n6 J/ q, o' _9 Z
wealth
6 R2 z& z' N1 N life-expectancy
8 l$ u# s( S Q& j* u* F metabolism , ?) u/ ^ b1 m3 Y) d
vision
, M1 P6 e* D6 L inherited * a, N% W$ B. a* x, D8 X4 @2 S
]' o: |3 b+ \ M0 {
& }, ~& v: X s: {4 s9 U; E4 {
4 m/ l4 l5 N bto setup- W, p1 V! J) F( G* x
ca# i! P/ r; O0 d' `2 s/ D( c
set max-grain 50 ?" p% G6 e$ E$ C
setup-patches
: i$ F% h* ?! d: z" u setup-turtles
K3 D1 a8 P! Q' d1 n setup-plots
5 j& y1 _/ z7 S) Q0 [ update-plots4 l) \. h3 A/ M
end
% N9 j: ^+ `" ^5 Q1 \% n; ?4 h! Tto setup-patches# b1 w& g0 u4 w' }. X5 U I" b# }
ask patches
4 ?/ y6 ^# \5 @ [ set max-grain-here 0
( w3 K, Q/ d8 U. K& C9 Z if (random-float 100.0) <= percent-best-land
0 o, O8 q9 s0 f; R4 l: [" X' i [ set max-grain-here max-grain
6 C6 e2 R |' i+ ?4 i5 z1 i$ U. x; P set grain-here max-grain-here ] ]
" J) B7 D# ^" C* M; A9 U( O repeat 5
8 N& o& u6 Y, o3 G0 f [ ask patches with [max-grain-here != 0]
7 }9 w$ h( R& b2 p5 V [ set grain-here max-grain-here ]6 q b" @+ q9 [; w7 `) j+ p
diffuse grain-here 0.5 ]! L2 P @) s* M# B; c @3 k
repeat 10
8 P$ X' R/ a4 k+ T. q* _# R t [ diffuse grain-here 0.5]
" W, w% f/ d0 }, i; K! d ask patches" w% W3 A. x1 L9 K' p) N9 A
[ set grain-here floor grain-here
# M/ k; s7 R, x S: A set max-grain-here grain-here , ~* F" C% M- i2 f( N# u2 c' b' x4 M
recolor-patch ]: S7 I _# H5 [$ S- x
end
D: b) l3 s1 n* g* hto recolor-patch ) |% N( I) k! b |! v/ x0 H
set pcolor scale-color sky grain-here 0 max-grain
/ @" V" G1 q6 r5 qend9 W0 E \# Y5 E6 M2 u% M7 [8 O
to setup-turtles2 ~' i, y% ?2 q
set-default-shape turtles "person", Y: J% j) n+ A3 i, B4 t
crt num-people
" P& M. v, P& V% |' a, u [ move-to one-of patches
& U$ }0 O- G4 q6 ]* G set size 1.5
0 Y9 W4 v* [, r! A# Z set-initial-turtle-vars-age
8 x: i6 ~1 H, l: J8 m set-initial-turtle-vars-wealth
0 c, N8 }" `8 k' k set age random life-expectancy ]/ c A/ I$ u6 N! m1 u# \6 K/ S8 W7 j
recolor-turtles2 L3 B* q: {9 P% X" j% @
end8 o F) q9 t f, \
) B& i( o; f2 _4 b- k O
to set-initial-turtle-vars-age# a+ i0 t9 k' \
let max-wealth max [wealth] of turtles3 ]! P4 F2 w# v6 K h
4 A* b2 [2 n7 M+ ~2 } U. c& D ifelse (wealth <= max-wealth / 3)
) ?* R% E w. ^1 J [ set color red 2 ?! X Z- I Q
set age 0
9 e& u5 d/ c: M. Z8 N) _ face one-of neighbors4
# n, p; o& a4 `. E, B; E set life-expectancy life-expectancy-min +
2 i0 m$ ?- e) I random life-expectancy-max , [3 x: A; C* c$ p
set metabolism random 1 + metabolism-low6 l& J+ F, k2 O
set wealth metabolism + random 30
! Q& z; n. ] Q2 L% g set vision 1 + random max-vision& w2 I* n5 T" G N
set wealth wealth + Wealth-inherited-low ]
: l4 P* t, E/ j1 U/ F3 h [ ifelse (wealth <= (max-wealth * 2 / 3))
- x" s. F1 ~+ L+ D" ?( [$ F [ set color yellow , [) y# P5 \4 M! W7 ]5 y: _# n
set age 0" @7 f3 v9 G$ W+ s% j! d1 ~2 p6 ^
face one-of neighbors4 [8 k5 n, I L+ D
set life-expectancy life-expectancy-min +
9 c3 M9 G4 M! g/ E; Q$ ^$ j random life-expectancy-max + 1
) m/ ` q/ Q3 G) I set metabolism 1 + random metabolism-mid( N0 i% [. z$ ^5 G; R4 e0 }% d
set wealth metabolism + random 30
! V |- L- d8 V! Q& }1 f7 a9 Q set vision 3 + random max-vision: P" \# S3 ?, w9 w3 O& O
set wealth wealth + Wealth-inherited-mid]- m, X0 Q: O6 [7 \- K/ D
[ set color green , O( C5 R% G4 F$ _" S$ h" H: D2 K0 ~
set age 0
9 E- {9 W1 P3 N face one-of neighbors4 ( T. e1 T0 P( N h7 C
set life-expectancy life-expectancy-min +
: v# `, y; O4 f' a v* x5 X3 { random life-expectancy-max + 2
& O) G7 i; I( G7 k! ` set metabolism 2 + random metabolism-up
: }, _1 C {* U; O( G+ s* B set wealth metabolism + random 309 s- j/ X# R. k
set vision 3 + random max-vision* h% |5 j2 o* t& I
set wealth wealth + Wealth-inherited-up ] ]
- ]9 Y7 k( Z4 j5 |2 K ) d r+ H6 _; O6 s6 s8 q6 X
end* e8 B) x9 d& q2 L
to set-initial-turtle-vars-wealth
6 L0 B1 Z+ c' _, p let max-wealth max [wealth] of turtles7 D5 T5 H$ u4 X8 Y$ j4 o9 Q
set age 0
! e7 @3 P* _. V7 l5 \* B face one-of neighbors4
/ H9 M+ h2 i0 S& a7 K8 [ set life-expectancy life-expectancy-min +* K }& Y7 D4 d. `! I: j4 |
random life-expectancy-max % [- x* P% G9 N- J. e) A( e
set metabolism 1 + random metabolism-up
. j* d% H# V7 E set wealth metabolism + random 30
3 ~$ x. J O4 M set vision 1 + random max-vision
9 @. k \0 W. F# s; u+ Vend
) D8 b& K' V- ]& a: J8 c+ s1 Kto redistribution
2 Z$ Y& n& |8 v: w* ]6 hlet max-wealth max [wealth] of turtles
! n+ M- M( f) \3 r6 w9 {1 plet min-wealth min [wealth] of turtles8 @( w" Z; M( H; A4 s2 ~. N3 [
if (wealth <= max-wealth / 3)6 o$ j$ }# x9 R
[set wealth wealth + Low-income-protection ]9 b. d$ F1 ?- M
end
4 r' E3 Y" ~2 C0 p8 j4 g * J% K" z% t' D( ~( }. T! S
to recolor-turtles
$ g' A: _$ i# D4 U: Q' W: m9 d8 g0 h let max-wealth max [wealth] of turtles8 Q; \& ^5 |, { g$ O6 R
ask turtles* ?3 \8 _( E |- R4 `2 Y& n0 H& r
[ ifelse (wealth <= max-wealth / 3)- J8 Q! A; d- @
[ set color red ]& J) L9 }2 w+ d/ ` |& y5 r5 X
[ ifelse (wealth <= (max-wealth * 2 / 3))
* {8 e+ f. |, | [ set color yellow ]2 u/ B- b! B0 F/ s
[ set color green ] ] ]) j! G7 s/ W# h
ask turtles [ifelse show-wealth?
# L5 }) ?) c- Z7 `* x' q% N [ set label wealth ]
, M4 ^/ e5 k! C% ]$ i [ set label "" ]]+ k6 C( i# N$ @. X0 e( t
end, [" I4 O6 c W7 \) J3 V) C# j
; A5 C6 a- ]1 r" z3 R
to go
y* U3 M4 C0 h: O% B: j/ }8 p: T ask turtles
2 w, Q4 l7 p, F( y3 p5 @5 H [ turn-towards-grain ]
4 q& j3 D1 R+ n; U harvest) \" B8 i# _! X9 a
ask turtles6 Y5 ~1 X5 j. H4 L
[ move-eat-age-die ]
% T( O% y8 E; v) q: s$ k recolor-turtles# P: e4 \' r; G* X6 _4 k
if ticks mod grain-growth-interval = 0- G! q. k, S3 F0 l
[ ask patches [ grow-grain ] ]
2 K V9 Z: C/ P
. R. }$ z* G) D! p# {7 s+ u" l3 D if ticks mod 11 = 0
6 w j, H' Y* p2 R. c4 ~ [ask turtles
7 s, ]8 h l1 m7 X% b [ redistribution ]]& ~1 x. c+ N8 M
if ticks mod 5 = 0! r- M n* L6 x1 u
[ask turtles
. f6 Y0 U) S! L8 H7 H# L" | [ visions ]]4 t& p+ h8 Y% e2 ]; L1 U) \
tick* _: T2 M% i8 B( L) H) f" b* o8 N
update-plots9 b& C' k7 {/ B/ I6 l9 v
end
( S( h4 f7 I# B- i3 N4 _8 G1 @, sto visions
! ]* l! b1 Y, Q set vision vision + 1
v' s" K, ?3 I B9 S0 o9 C' lend
- i7 |6 D, _) `$ M5 b. U4 [& F0 z$ H2 ~! L
% y# t' I6 R& ^$ _* Z7 [8 k& A' F
3 T; M* i5 W6 W! h$ }, U% H
to turn-towards-grain
6 {# J1 ]+ [& D4 i set heading 0
n4 ?1 j3 V( ] u6 I* C- h: O let best-direction 05 E& Y, J* z8 R1 d# L- @8 m
let best-amount grain-ahead( a. m) S- C7 n2 @' R- A; ~4 c) w
set heading 90
& q& l. d7 V3 T0 B, Y- u if (grain-ahead > best-amount)7 {( f* X" E, B0 t7 b) k
[ set best-direction 90" w. r' e# p8 L* G3 b9 R! v
set best-amount grain-ahead ]
+ R) t- L3 X% K1 z set heading 180
1 C& H& K% j8 V9 G* ?' G2 A if (grain-ahead > best-amount)
: [! e8 c) B; y! p& ?5 f( E [ set best-direction 180- K& j; B" E1 U8 a
set best-amount grain-ahead ]3 ]( ?. ^2 W" |8 c$ M+ r: E5 D
set heading 270
( \( [/ p% F/ `7 c% ^4 P if (grain-ahead > best-amount)- H/ Y: M& \* w! S" z2 B
[ set best-direction 270
7 M7 U6 u. F7 b5 X/ g' u* W2 ^ set best-amount grain-ahead ]
5 O X+ w! j# q# _" B3 H set heading best-direction
) n' p( R5 g0 @$ o3 wend8 A# A7 ]7 U/ b6 l5 o+ ^+ h
$ v3 N. L- n4 ~) O2 m: S
% V0 I5 l" I4 ~- }
to-report grain-ahead - l i7 r! T- Q# K
let total 0) u" z( ]& Z1 k( E( a! g# S% F
let how-far 1 A( a5 ?: B( s2 U5 J3 x# Q
repeat vision' |1 K. Q) a0 g4 _# R. y
[ set total total + [grain-here] of patch-ahead how-far
' E2 V3 M3 j+ r7 J4 a set how-far how-far + 1 ]6 ]% k. F/ K) U8 B' ^( N
report total
6 q# E5 s. [, j, m& ^" t5 Vend
/ @( p0 K! S+ @% W2 P8 Z1 C: e: O$ G. I1 ]( ~. M( w. {5 F
to grow-grain
- `9 q9 R" _9 A& B; U2 d9 ~ if (grain-here < max-grain-here)
# e0 {; h: }) ^& Y0 ~0 y+ a [ set grain-here grain-here + num-grain-grown, q+ z" |2 N& ~; Z
if (grain-here > max-grain-here) 1 h X2 b, ]% D* O L
[ set grain-here max-grain-here ]
" f, T* N1 K! X4 M* i# S" N recolor-patch ]$ h2 x0 V- A8 D4 a
end
, W K2 g9 S9 V. T' I! A& U' F6 ^to harvest
6 `. U: K: [4 K! P7 E) s a ask turtles4 t1 p4 ?7 r8 M1 ]
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]* @( k! A% N, F3 S9 ?
ask turtles
/ e" l5 G, ^% m [ set grain-here 0- b G$ q, w: P1 Z" q: r
recolor-patch ]5 L7 n# q' r/ ~& k) P& F
5 s( w9 @3 w9 ~" J" s# `end
; ?! u$ d$ c, Y9 _3 I3 ]. J4 w, A
to move-eat-age-die 1 ?4 U* r1 w3 z' g) O! G
fd 1
0 `4 k$ x8 b/ y. C( d) Z8 d' Q set wealth (wealth - metabolism)
: o w1 ?* g+ k7 V# l set age (age + 1)
/ x* n' Z% Q4 f$ \; S P if (age >= life-expectancy)* ~4 k& K* g# R& b8 n, Q; @
[ set-initial-turtle-vars-age ]
: ^6 N6 P& d, C+ s if (wealth < 0)
8 a" b. Y% c" a8 r0 E2 O, _ [ set-initial-turtle-vars-wealth ]
/ j& {' L' M O# U# {, t& t" i( `
+ B$ d: Q9 |+ P6 l: V# ~6 Qend
# s C# @- T2 z" A9 B, t1 U# G& G
/ j. ]+ d$ z* ~$ N! V w6 g- f" x/ z U G/ Z8 U8 ~6 L) \, H) I' v
to setup-plots
9 n+ k4 o$ M( x- i; d5 i* I# W set-current-plot "Class Plot") b6 B6 ~) Q9 G [" A2 z2 b2 b. ]
set-plot-y-range 0 num-people; y$ K2 Z7 o7 h% |2 z3 `) }
set-current-plot "Class Histogram"
+ B4 [- ] U2 T3 |" J set-plot-y-range 0 num-people
, c; Q" G# C9 T. X0 D! nend
, M! U ^3 m; `6 G
! N5 h6 K: i1 s: ?' Z) F; Zto update-plots
/ G. l+ f/ h. N: } update-class-plot4 E# \$ s2 W/ _& S8 E0 c' y
update-class-histogram* s+ y. n8 H( n# q7 l- v
update-lorenz-and-gini-plots
) a0 Q* w( y5 q4 _' m& b' b4 Send
G# ^: D( l9 p0 g- z
& O% S+ j7 s8 M6 G9 A) ^5 ~to update-class-plot' s2 w/ T: B$ O4 Y, Y* A" X5 w
set-current-plot "Class Plot"0 d0 S% N( `- \; ~1 P" h* h% [% D
set-current-plot-pen "low"
* W* r+ z9 M! L6 c* Q8 s( B plot count turtles with [color = red]
8 x4 N0 y% R& W set-current-plot-pen "mid"
# U- }/ i% C; V' m plot count turtles with [color = yellow]: q7 j* E: H1 H7 B' ?
set-current-plot-pen "up"
+ O& U. M" V6 q/ l plot count turtles with [color = green]' J/ _. ^/ E+ o& c7 y
end7 d/ e9 o" T3 {; B
& I! i' \* V( k& R* h1 Vto update-class-histogram6 a- }4 u3 k8 _% b/ z
set-current-plot "Class Histogram"$ {( F9 Q1 D2 o- x: U
plot-pen-reset
/ s7 ~/ o- X+ \- P set-plot-pen-color red2 h: @. z+ S7 W+ f+ g3 C q
plot count turtles with [color = red] U/ @( }: ?% ~: ]
set-plot-pen-color yellow
0 k( H: a6 @! g! ] plot count turtles with [color = yellow]
: s& M6 ~/ U, I- j3 V$ u7 C, ]( x! ^ set-plot-pen-color green# p* E/ [. }3 h9 {' |
plot count turtles with [color = green] ^ a ^) u+ J4 m
end
) V, ?2 A9 T4 ^, j2 |% Jto update-lorenz-and-gini-plots8 J8 n/ H/ r3 v1 h8 M
set-current-plot "Lorenz Curve"
; Y: o6 o9 H, l2 k8 R clear-plot
( W7 j7 e% I" L& b3 b. t: u- L0 [* w- V
set-current-plot-pen "equal"% h% F* k( ~ b, o$ z( B; U
plot 0: X6 c/ D' m6 h9 ^% s7 m8 O
plot 100
8 i$ V A8 H$ J7 a. f: ~/ P
4 d* A! c/ w1 f3 A1 Q( w set-current-plot-pen "lorenz"
" @: j+ g1 ?8 V5 m6 v6 P1 N \ set-plot-pen-interval 100 / num-people
$ U1 w: w& R- ?8 ^9 ^3 |$ p plot 0
& |. s" E) @) }* K& @& O, L: ^4 D; W/ Q
let sorted-wealths sort [wealth] of turtles4 Z* O2 H& ~ a$ y: W; T. V
let total-wealth sum sorted-wealths
6 s, N" b0 q1 i0 d) v5 Z [9 e let wealth-sum-so-far 0
^/ B- q8 J4 {2 L5 F/ T' ] let index 0+ i" b& j5 [' n
let gini-index-reserve 02 Y! x& I# S; c* r
0 T% v& u- R2 J& d: \% k; A0 r repeat num-people [, |1 z, B0 C- ]; X( i7 s+ s Q
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
5 x( m& C# }* z) M) v* E plot (wealth-sum-so-far / total-wealth) * 100
1 u; n3 j2 s3 Z/ u% |" K$ L0 _8 C set index (index + 1)
7 @ z: S- V, r" O1 K0 t: n set gini-index-reserve! w5 t& i' I8 D3 s1 Y( r
gini-index-reserve +5 V- j8 V' P: o% c- f# @; s
(index / num-people) -" f( G: p) f+ D7 c9 t
(wealth-sum-so-far / total-wealth)
+ z* m8 |2 k8 T ]
) M: b+ e% b7 L; o
u! k# ?$ {- x4 a$ A w8 m set-current-plot "Gini-Index v. Time"6 ]3 Z: [/ H* h, l0 @# K
plot (gini-index-reserve / num-people) / area-of-equality-triangle, ]! n' {( Z0 U; z5 }- _3 B
end
# a% |; \- ~; I; w8 Z% ?+ [2 [to-report area-of-equality-triangle( h. [/ ^6 @& t: _" K0 [- w q# g
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
! n# @0 n9 m; a8 @7 W. nend |