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' x8 q5 s9 V7 i/ q& K
globals
9 c0 j; P. k2 w8 L( e- P[. i ]* K1 a# t. ~7 l, Q# A
max-grain 9 @; m( v+ c1 M/ b+ _! x
; |* U' e, o& _' k
]3 r3 I3 H0 m0 u- I. c
0 I [" r1 q6 k4 P3 K
patches-own
' u) p( p m( L: Q6 P/ l3 `[
J3 c1 C2 w+ h" H* l5 E, c p0 h grain-here ( N: d+ l+ `4 i3 d4 _
max-grain-here
+ z, g6 \0 e' D]' z w9 z# y1 g
4 Y x9 L. V* C0 J7 b, z0 u
turtles-own
) z, q5 x, _5 L; o5 U& ^[
0 d. ]4 E/ }* y! W+ h/ e age
) q k; l5 v5 S4 e q* F wealth 5 O% z9 W+ r1 N& A) x9 z) ]# |2 z
life-expectancy
' R. _5 ^* |2 ] y- j metabolism
0 g& G6 Y! @% f vision
8 D; A1 B# D- N$ j& a inherited
4 l" j+ n% g! U8 v8 m1 j]
3 I, ~5 P. t! A" S& u# s! ]. ?$ H/ ]0 [9 g) b0 A
; H8 w: x, E+ T3 ^/ a
to setup
1 H& ^; J2 n" y# s* d% o ca
& H: ~# `5 F' I set max-grain 50
- w9 j. U% g S setup-patches
) e. p$ \/ d, @5 F6 F3 u# Y! a. F setup-turtles4 I9 u) f% \. j4 I8 q
setup-plots
& S2 f8 d1 I" Q, Z+ y$ T% m update-plots
7 K8 z7 y6 l/ I5 K( vend
- f3 @0 Z# L1 \. t; ?to setup-patches5 |! k7 @+ a; }8 E; Q
ask patches
* ]+ O1 L9 d/ p$ r7 @! i, k. D [ set max-grain-here 0
" ^+ h! Q- f! X2 t* }4 K if (random-float 100.0) <= percent-best-land
3 d# w8 W: M) s' c. P' G# f [ set max-grain-here max-grain- }2 V# a# N k( F; N$ S3 |8 V
set grain-here max-grain-here ] ]
% ~; ~) A) r- R7 H, J- j repeat 5
4 M- F4 k4 R! W, S* k [ ask patches with [max-grain-here != 0]5 N6 O/ }/ g, b
[ set grain-here max-grain-here ]
( C. N0 C9 E( Q& Z diffuse grain-here 0.5 ]
; g# \: a* H. f9 V2 a- a2 h repeat 10
/ v X# o- l( t! N# i% l7 F [ diffuse grain-here 0.5]
5 F) c! Y7 O& d6 Y: h ask patches
8 i4 ]1 Y2 y/ Z6 u# L3 F& r [ set grain-here floor grain-here
! s; e0 n& h1 e( B0 Q4 I: F& Q set max-grain-here grain-here & L! U: }3 {; ~+ g9 q
recolor-patch ] F- A B2 H- P0 b+ c- s# N+ Z
end. n5 P& Q4 z/ b
to recolor-patch
8 \5 _# [2 C* J8 A: l set pcolor scale-color sky grain-here 0 max-grain
9 C" d* D) P" o a2 ]end: u' [& r/ ^4 U: U9 J# `( _; H
to setup-turtles2 c3 l, a- _# l. l! X5 p3 X
set-default-shape turtles "person"- v8 C5 G. d9 m9 b& U8 L" [& r
crt num-people
$ U) `. n! p& t/ Z' L7 }7 K- C4 f' b" i [ move-to one-of patches 0 n( k6 N# s% S5 ~+ U8 S2 d+ |
set size 1.5 + J" N: K( S# R: S8 q! s% ^- u: K4 o
set-initial-turtle-vars-age
3 p2 f y% j" j) S5 N set-initial-turtle-vars-wealth
- n2 H/ ]% B z3 k set age random life-expectancy ]7 z% g. F$ D4 g7 R3 d
recolor-turtles
, f* e/ d$ `* P; ^4 ~# a8 V+ r, U9 pend: C8 Z0 h" z% Q
! h4 ~$ f# \9 `' I
to set-initial-turtle-vars-age
8 q* ?, k2 v/ L+ Q( @ let max-wealth max [wealth] of turtles, M4 h7 o0 }; W) k `" k; F3 w
' E- {; x3 Y% k+ @% k
ifelse (wealth <= max-wealth / 3)) S2 c2 ? U! \1 B; O" k! s, I
[ set color red
" j1 ]2 k! J- l8 W/ r; h set age 0
/ z" }* @+ L$ { ^2 ]8 T) {$ E face one-of neighbors4 2 s9 v; S* V1 Z$ t
set life-expectancy life-expectancy-min +7 F! U; J& ?& L3 H E9 }' l2 J
random life-expectancy-max
# ?! ^$ @+ C- q* U. Z2 a' F set metabolism random 1 + metabolism-low% L$ @; V! J; h j1 w4 R4 u
set wealth metabolism + random 30
% z$ y& @0 F* G( W set vision 1 + random max-vision6 v8 J8 Q- V, a& p3 w# m
set wealth wealth + Wealth-inherited-low ]1 Q y, G6 Y8 U# s) l; c/ O
[ ifelse (wealth <= (max-wealth * 2 / 3))7 M. ? K3 V! x6 u4 v8 w% J/ M6 y, X6 j
[ set color yellow 0 X' Y* t/ H7 ^- z+ H5 b5 F
set age 01 g) D& d+ E; c' Q
face one-of neighbors4 - \9 j8 g! o' I+ s; D/ T
set life-expectancy life-expectancy-min +" ^: u/ J6 m0 e* l& Z9 [
random life-expectancy-max + 16 i. X+ W$ N1 A! z
set metabolism 1 + random metabolism-mid" [! L" |1 Y1 \8 b
set wealth metabolism + random 307 S0 e' p3 p3 h4 i: W9 c
set vision 3 + random max-vision
9 y3 C0 f) `& }3 R set wealth wealth + Wealth-inherited-mid]
' @) x! H# H3 l8 p [ set color green / ~ s% X/ ~: U0 k, ]6 B
set age 0
9 }8 T( B3 g4 `+ r/ G" R- C face one-of neighbors4 ; O ]( c# u3 a0 G
set life-expectancy life-expectancy-min +3 h: {- R7 g' p0 l
random life-expectancy-max + 22 e4 l; j5 V2 x! T5 w" K+ p4 d; k% B
set metabolism 2 + random metabolism-up2 T' ^3 `% G, V/ z: v$ k
set wealth metabolism + random 30
7 O' K9 t; c: N5 z6 ?3 V/ A+ X: t a; O set vision 3 + random max-vision
( y+ p* ^1 e7 c# p1 N set wealth wealth + Wealth-inherited-up ] ]
1 v6 F p0 z* w/ `
+ h! M+ H& d. Bend# L( Z' B/ g& K" v7 X
to set-initial-turtle-vars-wealth
' ]' N7 `/ e7 F" y let max-wealth max [wealth] of turtles J7 l, m/ p! z# s& I1 w+ l7 I
set age 07 M3 {5 r" J) r3 S
face one-of neighbors4
7 J- G E: U3 O( {$ x+ A set life-expectancy life-expectancy-min +
* g( a2 O4 h) N+ ^5 K random life-expectancy-max , ]1 D/ f+ M2 l8 w5 A: o; Y4 ^" b
set metabolism 1 + random metabolism-up
6 M+ K& Y- \( t, C8 R9 U3 X set wealth metabolism + random 303 V' Q' B) \ i( x
set vision 1 + random max-vision
# c+ D# D t& T; v9 y3 q* lend
; W1 J) `" W5 X' c! Y9 uto redistribution7 m4 N N; H# t
let max-wealth max [wealth] of turtles7 O( E( ~. M0 Z, x
let min-wealth min [wealth] of turtles
2 J \; ]% c8 Z Q. V4 o! f" \" kif (wealth <= max-wealth / 3)# N$ o$ q4 H; k6 r2 I: R5 k, ^& E
[set wealth wealth + Low-income-protection ]
8 W+ O! c B* o% x% a8 l. x4 |end; G( B& F. ], \! U# B: `
& _9 x$ m, `1 \to recolor-turtles2 ?: A, A2 O5 n" Q
let max-wealth max [wealth] of turtles
! R3 L3 e2 f7 c5 F7 e ask turtles% c. ^9 i8 L' w# i4 P$ Q
[ ifelse (wealth <= max-wealth / 3)
3 U# H* z* z/ t% L( N Z% D6 P% ~( p [ set color red ]
1 Q2 _1 z( A0 L: X [ ifelse (wealth <= (max-wealth * 2 / 3)). _9 l( `$ u! | ?( V1 r
[ set color yellow ]
& Q/ ~' K- X J2 }+ _) {1 K [ set color green ] ] ]3 Q5 Z. Q! @6 U
ask turtles [ifelse show-wealth?
5 m; |. x: j ]0 Q! A [ set label wealth ]
4 T5 e* Y' }$ n, q0 r [ set label "" ]], i4 W' o) d& I" D. R" L* Q
end
1 O0 d( W+ g$ W+ p. H4 C0 S) @. [9 n7 ^6 A' u/ G* k3 u, O. E
to go
$ T/ u8 W( S, l2 \5 q+ A. h ask turtles
' k' P9 K6 L" T7 ]0 \! B Y( Q [ turn-towards-grain ]
5 A1 u) G" I9 }4 i0 B harvest; g% [6 l( h& X% J
ask turtles
' ~. @* ?, x5 O' j9 f [ move-eat-age-die ]
* }% v1 D9 {4 y. a; _" o1 o recolor-turtles
$ V4 C# J/ }7 u( F( q$ A5 m& M if ticks mod grain-growth-interval = 0
- E! ? j: ]* z3 g [ ask patches [ grow-grain ] ], Z9 T& R0 [+ S- B; Z9 M5 b: I4 w; I
+ E( f" W2 u2 a' ] if ticks mod 11 = 0
+ J9 |1 o: d7 X, ? [ask turtles9 L- }6 e) J/ `) j& Q
[ redistribution ]]" V' Q* x" g) D' o: |7 o: S. A5 u7 Z, `
if ticks mod 5 = 0" b5 A" N2 I4 X* g1 m a# k
[ask turtles
$ {2 H, V- O# T5 `1 m* L [ visions ]]
, u: E: b4 C# N# ?: J. T7 G- O tick% {8 {1 e H8 D2 G9 S' n
update-plots, ^: }3 Q$ Y5 ^& D1 E2 O
end& f" E9 k1 r; P; V9 z7 ?
to visions0 R% R, {7 A n S# z* i# V
set vision vision + 1
/ H! ]" V6 |+ m0 Q+ N9 |5 _2 cend
( B" n9 n; R0 m" \, B: ^1 v( x' L' x2 m- {
- S6 t, r4 A% f5 s
' F+ Q9 d9 Q9 C$ @( T+ J3 s+ qto turn-towards-grain 8 F2 B7 ]- {5 X$ t& U+ n! c4 R
set heading 00 Z4 r$ z0 @5 e2 U* Y( z1 i% ?
let best-direction 04 R* Y8 K. ?- Y+ V5 L: ^# h
let best-amount grain-ahead6 z( [$ B1 G, l
set heading 90* }, Z9 g. K1 \4 i; U
if (grain-ahead > best-amount); h7 Z1 d4 Y3 V# G
[ set best-direction 90
0 V+ m% {! Q9 K0 ~, i set best-amount grain-ahead ] d5 t% N' b$ v2 U$ [% W
set heading 180" x. L" t# Y5 J6 F i+ \
if (grain-ahead > best-amount)( ?* T7 M% r9 E- n* s: E
[ set best-direction 180, ?2 i; t) H% i5 ^( a# }( X3 `
set best-amount grain-ahead ]" E; z; M* \, t' n
set heading 270% e/ f; `9 o* R7 f$ A" i
if (grain-ahead > best-amount)
: a2 ?9 W: w9 Z: |) F+ L- \ [ set best-direction 270
) a8 ]8 \" T2 q! P% e set best-amount grain-ahead ]
; i3 E, V, n; \5 G P& R set heading best-direction m: m7 T5 U6 T- D7 G
end1 H, Y: S' G& ^( K$ a. `+ S$ ]
$ t( n2 @. P( @4 a9 j6 j4 z
% d# K0 E H! _ d$ K, I( y, Cto-report grain-ahead
5 a1 e9 \5 p5 U: z6 I let total 0: t% S! f- _2 j
let how-far 1
, c6 g7 M8 X5 w repeat vision
3 Y/ _. |) L* A [ set total total + [grain-here] of patch-ahead how-far% J$ R9 S& `7 X9 e! V
set how-far how-far + 1 ]+ C! n: _9 l; |0 v5 _, L
report total- K5 C# I: X/ T" Z; @+ b. \
end
! u7 b8 n: U; L7 F2 @9 P2 u8 g" X" ?9 Z' `) c
to grow-grain
9 g8 M' B8 d3 [: i9 s- v$ q if (grain-here < max-grain-here)9 p7 ]6 V& b4 j* |' N7 `
[ set grain-here grain-here + num-grain-grown
# @ n! Q C2 m, |, t/ f1 {- Q if (grain-here > max-grain-here)
- S: U8 k. z o5 m7 X8 ~ [ set grain-here max-grain-here ]
9 X5 Z0 c6 s% O# {. Y3 ] recolor-patch ]
, g- k- y' ^ g" \end W8 R `! W* ]/ z1 `. a0 n
to harvest; k' [- z- ?# X" X5 C
ask turtles3 W/ A. y( d. L5 Z. Z
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]) [- M+ i J$ t3 y( ^' R6 E( t
ask turtles4 {* @4 w5 D% Y; J! }0 P8 x! n
[ set grain-here 0: h# E n% U% a
recolor-patch ]
3 y- K- k" F0 k7 y 7 ~: g+ j. \. t, F: n
end
$ [9 \7 z$ W6 h( C3 l
( U8 [0 P, q7 [. K$ _to move-eat-age-die
' L' ]8 U0 |9 }! B6 x. d+ _6 }/ a fd 1& @/ S* f! z, |* L7 q; Y3 K( L0 Z
set wealth (wealth - metabolism)
: y; l0 [: q0 Z8 a/ A+ v2 \$ M7 K/ @ set age (age + 1)$ S1 y" y/ q& q$ o' s5 r' U
if (age >= life-expectancy)" _) N2 p6 E# v3 _
[ set-initial-turtle-vars-age ]& {; i) _! u4 Z D/ u: m
if (wealth < 0)
" S& i7 g/ V" k/ H, X6 } O [ set-initial-turtle-vars-wealth ]3 s9 A0 C5 ]) o
l7 W. Q( x# {! ^# x0 E
end- M+ `. p6 Q4 T" r
. H g( l0 x- l
8 f4 Q$ q8 l& {" G0 _
to setup-plots5 K& {5 v' W6 L9 X3 s. i0 X1 G
set-current-plot "Class Plot"
; x9 h* q1 Z) f+ z8 t- y% u5 f set-plot-y-range 0 num-people
! X a9 H$ W; g8 Q# ^7 V" i# | set-current-plot "Class Histogram"( [" f/ d9 M% C
set-plot-y-range 0 num-people
5 s5 T `6 _& w5 Y. hend
7 S8 |- H3 o# }" ^- Y7 |+ D8 U7 j7 l0 C9 n# A
to update-plots
+ O J3 k+ U" I3 n% p+ i4 Z' a update-class-plot
) W n* Z( p5 k' [* P8 }" @% P update-class-histogram
) D/ n& P1 N+ m update-lorenz-and-gini-plots6 s9 e9 k; b' \* }: O* p
end
1 @) ~9 O/ {" m7 Z
4 x5 N8 M; t' ], |. tto update-class-plot. {$ X/ H2 U$ v; n- U9 L/ |& [
set-current-plot "Class Plot"
) k9 o! p8 x. ]3 M8 y% ^9 E- Q2 t4 Q" ]: b set-current-plot-pen "low"
t' N4 j1 M1 @& P% S) V- x7 C7 E plot count turtles with [color = red]8 L: ^5 [( k9 K2 y, {, \
set-current-plot-pen "mid"
! B" I0 }& f2 v: @* y x, y plot count turtles with [color = yellow]
" M1 A: N# h5 E E c4 f set-current-plot-pen "up"2 `/ `2 G% C1 t; \3 V. _
plot count turtles with [color = green]
0 _# n# b2 B! O9 e* C, a6 C5 jend
; `- i2 ^9 y% F, I' r: z5 f& u- V( ^1 k J' x) Z* t7 q- G
to update-class-histogram4 C* `' r$ S' G) r8 O3 _3 w
set-current-plot "Class Histogram"
1 V2 _+ D4 R, H4 D! |& e7 T plot-pen-reset- c9 i3 d Y1 M. V! ^
set-plot-pen-color red& x% W1 _7 U9 V
plot count turtles with [color = red]/ `& _; _! z$ R4 _4 l' u' p
set-plot-pen-color yellow
5 v- d+ i4 B* K plot count turtles with [color = yellow]
9 u/ m7 ]0 Z4 C/ P set-plot-pen-color green
. Y' j1 p' D+ l i9 o plot count turtles with [color = green]9 s( g! m% H) y3 J( i/ R
end3 L8 T' p$ m- M$ |3 G
to update-lorenz-and-gini-plots
, |* Z$ \9 \+ T' {, w set-current-plot "Lorenz Curve"
$ v9 J4 d3 |2 F8 ^+ K clear-plot. C, `" X( d( F2 K6 ]* }
# Y* d2 P* C" D8 e: u set-current-plot-pen "equal"
) _" {6 e3 w: x- v! j) \ plot 0. Z" E! o2 L; ~. d# z
plot 100
k' F1 V/ f3 l, E8 F: Z
) x0 ]7 C5 n$ a+ u! H& \' R set-current-plot-pen "lorenz"4 Y' Z5 v) k; J, _& o! q6 o
set-plot-pen-interval 100 / num-people
( S; r% ?, M8 z. y6 _6 \/ g( J plot 0$ @. X9 O. U6 N; t2 ?9 _( R+ [- N
l% k, V5 K$ L2 U8 V let sorted-wealths sort [wealth] of turtles& T( q: B! a4 G' C( B# O
let total-wealth sum sorted-wealths. v G& H$ U0 ^9 ?
let wealth-sum-so-far 0
) Y- R$ u' q4 ]* j let index 0
7 d$ n, N, v0 C6 O2 M5 M$ `1 E let gini-index-reserve 0: `0 ]+ j4 g" }8 N
' z) o1 g5 e3 O3 z& L9 u
repeat num-people [/ B$ n# {. b1 g
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)' t$ H: i7 h5 p$ e" M" G" N
plot (wealth-sum-so-far / total-wealth) * 100
; m- q) I4 ~/ \. T2 e set index (index + 1)
8 u+ n4 b; o- [' b set gini-index-reserve
( o( s: h1 P7 J gini-index-reserve +6 z6 F! ~; |0 ^9 N* k- F1 ]/ E& I
(index / num-people) -% q, O8 r0 ~: d8 D5 a% r! K
(wealth-sum-so-far / total-wealth)
, u3 U* o) \9 N& f- D% \# B ]& E7 z) W: K \7 u4 P
" W' m) H3 ?* ?
set-current-plot "Gini-Index v. Time"
' v& C1 S5 a7 T$ V( c plot (gini-index-reserve / num-people) / area-of-equality-triangle8 I7 d' u* V ]- _7 s
end, f- c$ ^. d6 A: I: G+ X
to-report area-of-equality-triangle% c! Q: ]2 z1 L; ~
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)% [# |1 \! ?5 t& O
end |