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
/ E1 E8 A6 B( H+ I7 sglobals
1 X: p( ~ R: g* b, T9 A# J4 \. Y[
2 \3 M: G6 J/ U max-grain 8 g. i, O9 E" o9 V3 Z y
: J; O$ {( \2 o: ?]
3 J) |6 V$ n: n+ X4 U6 Y! p5 \6 e
patches-own
/ J( k- M/ b# |3 e6 r" U4 K[
h, v- j( s* [. S grain-here
, J; a* M5 \; j& E) g; q2 @ max-grain-here . M0 s$ H' G( Q; ?: X4 L9 Q
]6 c2 `% H9 G7 n6 w, t
0 A$ A: E0 R$ x0 q+ R |' Dturtles-own5 W( w0 @, L" R: u2 o! j
[
4 Z' ?' ]' q7 i$ w age # k0 f1 @& R' }/ _
wealth ' }! c+ d" C9 U2 f0 O9 ~4 f7 g
life-expectancy & c4 w# j2 N( E5 L; v7 q
metabolism
, E4 e" c7 y: s+ O4 D vision) Z/ S+ {* i! k1 X; `- U" I( c
inherited
6 Y" G( K0 O [: }+ |]2 [' @4 H6 l1 Q6 @0 T2 y
) S: G5 @& k: ^/ c& Q5 ]. K
. Y% p7 O% T# O0 _% K$ t. E4 wto setup
/ _! r6 g9 _" Q* c ca8 D5 ~! Y$ l7 n7 p; d# _
set max-grain 50
6 Y9 a) D7 N8 W Q setup-patches
0 r: ~% y4 B* @5 N: m/ E setup-turtles2 q; `* o6 o& a* g# D M
setup-plots3 F; v2 t9 Y1 K
update-plots4 l2 S9 i! G4 J* v7 D7 C) M
end1 f' u I" E5 T
to setup-patches
1 t( l2 U9 R+ s6 S ask patches5 X2 s! J9 |) X# f: x. Q" w0 q
[ set max-grain-here 0
: Q8 M! Q$ c; {: d if (random-float 100.0) <= percent-best-land' g. y/ V! j, I1 j# S+ [
[ set max-grain-here max-grain& E1 \& R& D1 ^* N9 E
set grain-here max-grain-here ] ]# Q: b# E# z4 H: u; s; T3 J
repeat 5
4 p# B0 V- V& Y/ T' k" Y/ L [ ask patches with [max-grain-here != 0]
% t4 F/ ?* v0 N5 i) S1 U [ set grain-here max-grain-here ]
! S/ f0 C% C$ ^) c diffuse grain-here 0.5 ]" ?; w' w. A$ P/ L! c0 d
repeat 10& ]5 k) e; m0 P0 F; K: Q4 p& j
[ diffuse grain-here 0.5]
/ u$ s% {' S" r ask patches
T3 Q# ?7 H5 R [ set grain-here floor grain-here ! m8 V$ z/ d$ H& b; }1 u$ C
set max-grain-here grain-here 7 a! @0 h, ~3 A6 N' s
recolor-patch ]
0 _7 z* ^9 k; c6 ^end$ Q5 ~. Y) T6 H
to recolor-patch 1 v7 ]5 `3 s0 ~) ?; k* L) r
set pcolor scale-color sky grain-here 0 max-grain" J& c: ?( c* a& S& M( `3 j
end
. N) y; B! n- S9 |+ L) q' M1 uto setup-turtles
' C1 }; T, g" N% \) O6 Z set-default-shape turtles "person"
7 X. |4 Y9 n2 M9 D8 Q! K. \ crt num-people
5 F' S' z0 q1 C5 X( z [ move-to one-of patches , N0 g6 f, y' Q& i" S% x
set size 1.5 5 [, q* W+ q2 L! O3 n
set-initial-turtle-vars-age2 Q; g- v( T' f, B K
set-initial-turtle-vars-wealth
6 U: f$ w' W0 I( T: R set age random life-expectancy ]% c0 O+ ? O( w' I7 D3 E$ D* q
recolor-turtles. W/ D/ c, A; g" x4 V6 H. a- G
end6 l- g8 b; |4 u" k
6 F- u, [2 V5 G# V& Ito set-initial-turtle-vars-age7 r B# ~6 V7 Q$ F' z) o% k# ~
let max-wealth max [wealth] of turtles. l4 e; R, n5 {$ N3 u! N% R
; ~# R, g7 b. _; i ifelse (wealth <= max-wealth / 3)/ {1 t( {+ w6 U9 z8 F
[ set color red X$ f% d3 l: \% w c* p$ D* W5 @
set age 00 M1 Y" \# S4 e1 G6 S" j
face one-of neighbors4
2 M6 ~8 i6 ~ a# }* }1 V set life-expectancy life-expectancy-min +8 }$ S. L" e u. r5 e) R
random life-expectancy-max
5 o5 j' X3 U( h/ q+ l* Y2 q+ ] set metabolism random 1 + metabolism-low+ Q' C) e/ C' D& Y
set wealth metabolism + random 30: [5 O9 H; J4 K- E( S8 Y
set vision 1 + random max-vision' b4 k: y. ]" x2 ~( h
set wealth wealth + Wealth-inherited-low ]( s' i2 @' t! m" ^, Q# [2 d
[ ifelse (wealth <= (max-wealth * 2 / 3))
! I m z4 ^* c/ \8 O [ set color yellow
* {4 }! A+ d" G9 Q1 G" ] set age 0
9 m, p0 X0 u: }. P* E# o% z& l1 y face one-of neighbors4 + r; ^& q8 q5 U1 p8 Y) U! T
set life-expectancy life-expectancy-min +
3 _ U8 w' _& N$ E& I: G random life-expectancy-max + 19 O' Z( Q6 S1 i) g& M! r6 P
set metabolism 1 + random metabolism-mid
' ]; W, D+ p+ d3 d set wealth metabolism + random 30+ w. S6 }% i# R3 p0 ^9 n" x
set vision 3 + random max-vision
& f1 d: w1 ~& z1 ? set wealth wealth + Wealth-inherited-mid]
h" Q, h& [" o# w, N; K [ set color green
3 V# H/ r; |, `0 b! Z2 P$ J set age 0! N5 X4 |4 B J* }
face one-of neighbors4
# Q9 a: ~; F- E) v: j set life-expectancy life-expectancy-min +
5 c" @) t7 U5 r3 a* K* E3 | k random life-expectancy-max + 2
. b" C( P7 \/ h set metabolism 2 + random metabolism-up8 R4 D7 w/ G2 Z8 e J$ k7 s, R
set wealth metabolism + random 306 q7 s6 d& z& k# F
set vision 3 + random max-vision- L) U8 n5 Z& ^8 G8 c
set wealth wealth + Wealth-inherited-up ] ] : q: D1 n5 R/ s7 _. D/ z
: D! ?$ q4 D" m* m5 z& k
end* U! y) Z( |2 N' N
to set-initial-turtle-vars-wealth
" h1 v1 f+ g% J4 P) ? let max-wealth max [wealth] of turtles
+ |; E" q& F2 B% x5 F5 I set age 0: N- t% Y) ]' z7 N: K. W& @
face one-of neighbors4
( N. u' h/ |2 J/ e% A! r set life-expectancy life-expectancy-min +
2 K: r4 t, ?8 l9 l I4 o random life-expectancy-max
" N; E6 t; I* g1 L3 l) q set metabolism 1 + random metabolism-up+ `2 P; I' v& V m$ u) n% ~
set wealth metabolism + random 304 l4 t* h& r/ G: D
set vision 1 + random max-vision
, d" U* |0 h1 q9 z' r9 v# K- qend
) ^: e& v/ r0 @0 o2 X+ s8 g0 ?8 Hto redistribution# E6 i/ e% Z8 j9 I; r' O: O! i6 A
let max-wealth max [wealth] of turtles
: ] a" t# q n l+ {3 Ilet min-wealth min [wealth] of turtles
& J, U1 d/ _8 t4 `+ g7 a4 ?9 C1 x- {if (wealth <= max-wealth / 3)
( u% R* P* T5 o) j0 V [set wealth wealth + Low-income-protection ]' X3 y* K: A6 m7 Z' F$ s
end
|: H1 i, \1 f9 ?; y5 s! G ; a/ d+ e q! \2 P) B
to recolor-turtles- u1 e( n# h. K) t5 @
let max-wealth max [wealth] of turtles+ K M) S3 ?7 F4 u
ask turtles; K {/ n" F B. n8 \* o2 f% {" e* O
[ ifelse (wealth <= max-wealth / 3)0 A) D) f5 l' D: g% H
[ set color red ]
* x7 Y, F% r9 ^ [ ifelse (wealth <= (max-wealth * 2 / 3))0 k' i% {. S+ i4 K1 j8 D0 H
[ set color yellow ]9 X5 c+ T; Z6 n# e5 E8 W5 D
[ set color green ] ] ]
2 I' E, } w$ u3 Q& w' ]/ s+ l ask turtles [ifelse show-wealth?
$ n' e) y7 @: K$ r6 c' ^" Z [ set label wealth ]% ]8 O( a! t, i: J7 _1 o8 c# K3 ^
[ set label "" ]]. [8 D: S. W6 ?0 B
end& E* S6 |4 v- q) L5 V# n
# z7 M$ d/ h6 b: l
to go
- Z1 i0 a/ ^- I. j1 d ask turtles0 ^3 k: K( d+ \% p
[ turn-towards-grain ]
0 \& S$ w7 W" } harvest
9 i2 V% O$ H* w) ] ask turtles* q8 [# B8 Y! L2 y+ O" Z$ Q
[ move-eat-age-die ]
0 V' W3 A4 `. o4 Y recolor-turtles
+ B+ |7 \: X7 F1 Z if ticks mod grain-growth-interval = 04 z7 b8 T& I2 O- f$ h
[ ask patches [ grow-grain ] ]- ]4 A/ T+ e' y% g0 e3 [% D
. Z# L' m+ c6 i$ ~2 q& H1 G7 a2 X if ticks mod 11 = 0
2 ]1 Q2 ^& v! r8 t, a/ M* G( J [ask turtles* \ ^$ k M9 m2 k/ G( H! {! @; Q
[ redistribution ]]' A% v6 E. o" d: V. m U
if ticks mod 5 = 0' J$ K _9 Q+ W# D2 S) p& v
[ask turtles) A$ v8 ^# Q9 U/ f
[ visions ]]
( h# s( _% N" U. ? tick
5 L1 t- j: _4 O- v update-plots# R! Y0 X$ q2 v% ] k- G$ ~* h
end
& y; h2 z7 M! J& f/ C* Z+ Gto visions( s( t( d$ J4 x, {7 b) W
set vision vision + 1
5 v3 c. L7 ^1 wend
$ d" e3 D/ I! C7 }
! M! }4 i+ f) r/ i, k2 ]1 o1 |1 j& Q* \' q6 a' H$ X
* K" I: q% p. h( h: nto turn-towards-grain F5 c. z0 a6 I: w
set heading 0
' Y; _2 ]7 K# Y7 j let best-direction 0
7 a4 V0 ?- g8 @/ s) ~! D% O let best-amount grain-ahead
; Y4 w. M4 z$ X7 K0 ] set heading 90
, w* |8 \3 X5 Z+ W t: s4 z if (grain-ahead > best-amount)5 S4 Y& K" @- q( p" t* |
[ set best-direction 90. Z9 t3 o$ b% b0 Y. u: I9 V9 W# M
set best-amount grain-ahead ]
* ]; z) a. N- l8 ~7 [8 w. I9 I9 ~ set heading 180
2 L0 _* Y( P# h2 X4 S+ I- C if (grain-ahead > best-amount); ^9 A4 E) _+ U: K
[ set best-direction 180
9 `! Q3 t4 t! ?/ a set best-amount grain-ahead ]
9 z& s" f' ?! ?! t0 S0 N set heading 270* ?: E& \ k) v
if (grain-ahead > best-amount)% |' W% W( \% m1 L9 k. b' w _& ?. M
[ set best-direction 270
5 P. Q# ]) G" E* K set best-amount grain-ahead ]. V( w# Y. d& e+ S. M" ~2 Q2 l
set heading best-direction9 H' j2 e! Q% g" e0 {
end$ q/ [! l v# d) ~
/ k# J/ U' u$ n. d+ ]% r/ }# J( k4 H" O
; ~/ P$ w1 {; S9 h/ h5 n& ~5 Vto-report grain-ahead t/ ?$ ~0 i T! v" S0 v& Z% q
let total 0
4 f1 R6 U* R+ ?9 u8 y5 t* M let how-far 17 T. X9 O2 N6 N6 z
repeat vision' g% ~/ x& |2 i6 R, h* Y
[ set total total + [grain-here] of patch-ahead how-far
2 d! C8 h* w, \ set how-far how-far + 1 ]3 C4 I: Y" n, r, S
report total. X2 ?0 S+ ~6 j3 U9 |# Z
end
# L5 J" s& J* K) [9 ?! X
! [: F# H% D! o6 `, xto grow-grain
9 r/ Y x5 F+ s7 v, ]5 Y if (grain-here < max-grain-here)$ e" f) A, R; T/ z1 @3 U
[ set grain-here grain-here + num-grain-grown# o9 J* x/ `: O4 L& b3 v
if (grain-here > max-grain-here) 4 r: f2 \, o- P# C
[ set grain-here max-grain-here ]
2 }* N& G& \: u6 w# a& F* _ recolor-patch ]
5 {0 R3 R# Q, B6 c- _! @end
) e& T |7 e" l4 ~( A( k/ c0 [to harvest
5 |# Z( p* F! t+ _- P& v ask turtles% ^ L" c6 d/ K& W. n+ i8 ?) W. A
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
* e( o: M' B3 Q( s ask turtles0 c8 ^/ ^7 a' l
[ set grain-here 0) H% y8 x1 y# u0 b* z0 c8 H3 v2 D& t
recolor-patch ]
8 @2 j. S/ N4 ?0 N, y& y 5 ]# r% r% O* v* m. F
end
% i) Q! D) S( q" L1 v: e: q) m) ?! J) B
to move-eat-age-die ( h+ M) ^+ d2 j/ ]( A$ O, }2 L+ C, I
fd 1
* I; m% H, W, c b' ` set wealth (wealth - metabolism), e' _5 s E) V& W6 v
set age (age + 1)6 H b+ ^6 V. @" f6 w
if (age >= life-expectancy); b" z' ]3 Q* R7 z7 B
[ set-initial-turtle-vars-age ]
) i* P2 D$ p1 J if (wealth < 0)0 p4 H0 G8 d8 x/ Y* z
[ set-initial-turtle-vars-wealth ]' N% O' n7 p" M5 B8 V+ ~
& a: e) }( i( L/ O
end
6 m) m: M a- Q$ W: [( J7 ? V/ ^: Y( E3 p7 t* D
5 e. d% W* k( B) _9 C0 N7 w {
to setup-plots
& `6 @$ V2 @6 s set-current-plot "Class Plot"
- \# u9 y5 ]: g5 |- q: M set-plot-y-range 0 num-people) n9 o% O& J, W3 c' M2 T
set-current-plot "Class Histogram"
) W* _4 v8 s& u2 ]5 v* y0 ] set-plot-y-range 0 num-people
! T& Q! }# a+ D" k, A# T/ n% k2 d4 g. Rend
4 c. `4 @1 k$ {( d1 z B! O5 e$ I( d; N- g+ Z" X( X+ a
to update-plots* O y% u/ r9 H/ I; e
update-class-plot8 c8 d. i. b8 Y. Q/ w2 q3 W$ t' h
update-class-histogram J9 w" d f' G
update-lorenz-and-gini-plots% x0 t8 k L9 W# H8 t
end
; C5 g. b$ _6 s5 T) M9 i. D) H$ _" g9 h% H8 A8 p
to update-class-plot
6 `; |' ]/ X+ g; p, q* f8 H set-current-plot "Class Plot" U& D( \7 F% j! s0 W
set-current-plot-pen "low"* ?4 a9 z: } z* n1 D) u: e- {" x
plot count turtles with [color = red]
2 q/ T/ C, V+ J' G8 ]' y- | set-current-plot-pen "mid"
+ p! V4 }& h0 z5 J4 O( [ plot count turtles with [color = yellow] W9 H, I( s( i" s5 ~" Z
set-current-plot-pen "up"
8 P% e2 Y. Z0 _) R0 I# C) f, d plot count turtles with [color = green]: s5 A4 @ j. [: A8 ?& l! x/ P
end( b% a2 `( U2 \# x! k
- P& m# i+ n. Wto update-class-histogram
! a+ N' F$ C5 t1 i set-current-plot "Class Histogram"
! F* M) r e( H2 d6 O plot-pen-reset
- W3 q( I6 ]' e& x/ R7 z set-plot-pen-color red
$ T/ y. ^8 g$ \4 n: d$ {- D plot count turtles with [color = red]
+ w b: x4 u' [$ g9 Q) { set-plot-pen-color yellow
' C4 B" a# F5 N$ | plot count turtles with [color = yellow]9 {- u! C# R! q: J$ Y! L$ U
set-plot-pen-color green
: D! c4 r( ^! ?; C plot count turtles with [color = green]
" r8 P' ?7 |: J& @end/ H) C9 d& Q3 p* h
to update-lorenz-and-gini-plots
' \, ]3 U% R- f, X+ T$ ?, J set-current-plot "Lorenz Curve"
% C2 P7 g6 g$ n' l8 A4 c clear-plot, T% W$ r( U; T) S+ n/ C, \
9 Z$ q3 x. z3 Y. F- g set-current-plot-pen "equal"' j. K% p+ ~0 k) j2 r6 R3 ]
plot 0
6 d# x7 g$ X- T plot 100
) y" z5 A) _: i4 g/ q8 \ W! y- [& M# I7 }2 I
set-current-plot-pen "lorenz"
! N4 l+ Y4 `9 u% h1 p) G) C set-plot-pen-interval 100 / num-people7 c+ y6 |' n/ _' W$ H( n# |3 m
plot 0* K/ B; M& _2 H6 g$ ]3 Y9 |
( p% [' [5 d, {) s6 |+ A) `# V let sorted-wealths sort [wealth] of turtles
8 J r' Z {' R8 J e let total-wealth sum sorted-wealths
+ A/ ^/ F( O) @5 b! p let wealth-sum-so-far 0, Q, c0 R% m! }! S
let index 0
" s6 I8 [) t* { let gini-index-reserve 0; |; w6 Q) R- _, y0 B
5 K' h5 Z6 E. h" K repeat num-people [* v4 J7 I8 {+ R* K) l
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
! F( L7 K; B0 |- Y plot (wealth-sum-so-far / total-wealth) * 100
0 M5 K% V( R, C set index (index + 1)2 s, Q+ e3 Z- v
set gini-index-reserve& N/ g6 t( e$ j2 Q/ E
gini-index-reserve +
/ v; M" U. t& ]3 q- Z (index / num-people) -3 {1 z5 u/ g" f( y, v
(wealth-sum-so-far / total-wealth)
h( g+ ?2 x/ S: b2 B ]1 K$ u% K7 O. H0 {* D& K& Y+ u
* K& r, S0 w) W set-current-plot "Gini-Index v. Time"/ {3 |/ A' i1 C- A
plot (gini-index-reserve / num-people) / area-of-equality-triangle p/ l7 x. T# A$ X% f) T
end
' Z( q) A! X5 `2 K: h! f; a) Qto-report area-of-equality-triangle8 a' [; V5 f4 C3 R
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)& V* [9 ?$ e1 V: b0 N
end |