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+ G; u6 `& r" v, o
globals, L/ w% L1 w! I) |/ f
[
( u- f& {/ U5 d6 O) s max-grain
0 H3 b! Q& a5 P
8 g6 u3 g" s. G]
+ D! V# W9 I2 E1 Q; ^7 a% \9 [0 K$ G+ R' }, T, E1 [# y
patches-own5 d1 ^$ q0 J5 p9 I+ X5 f' _
[" a4 h) ~4 W$ e! N+ c( z& G3 b* ~
grain-here
0 t; q5 C5 c/ [0 a max-grain-here . B0 n/ Q |" v! u) z
]
4 K) j9 F ~6 c+ s+ |! l
# d2 B/ Z2 y, k1 _7 tturtles-own7 R% X) Y, J ?. G2 U; }
[
9 [! m- Z# |9 F5 V, } age 9 v, Y; B, D6 w3 ~0 k7 \
wealth
, F+ u. j% n' f life-expectancy - Q0 n% p6 @( ^2 L
metabolism & `) j- g+ `/ y5 Z( d D
vision: T2 f5 Q# A, v2 O5 U* r
inherited 9 k7 {4 A- x- P0 U# o: J$ _2 R1 B3 D
]
: l5 a9 n! }2 E/ I8 _5 F F$ q0 [0 A- T! }, Y! B) K" k6 {; F
' h3 W7 a6 [1 P# @9 wto setup
/ M+ G7 z2 K) K# f7 K: y5 h7 t. h ca
9 T, P0 t1 ^4 u$ N set max-grain 50
' M+ ^7 P. J2 B5 u# j# Z setup-patches
0 E% V' T6 T1 t; ?; w' B& ^ setup-turtles C8 n. j" t$ L' T+ x: [, {
setup-plots
9 O0 r m* S! L7 M8 h update-plots7 K* j/ I* F! i. s+ q: z, R
end
+ o: _: O( j! q6 k* h' @1 ~to setup-patches, y1 w, ^& z1 l8 i
ask patches2 h* m: @+ {5 P: B& p" D9 b
[ set max-grain-here 0
, J) i1 [+ D0 E4 z if (random-float 100.0) <= percent-best-land; p* b+ J* v) h; d, G
[ set max-grain-here max-grain. P9 `# ]. d. B& J) t" k
set grain-here max-grain-here ] ]8 `' r; }1 L0 K) F
repeat 55 l# M8 f+ H+ A
[ ask patches with [max-grain-here != 0]( s$ n9 a Z- [3 _4 B! T2 q; m8 _
[ set grain-here max-grain-here ]
1 s$ m0 x' G& W8 w) {- x1 @3 b# N7 A diffuse grain-here 0.5 ]
. r7 v4 L, j! z4 d! h0 T" M repeat 10
3 w _1 o" ^& j- I0 A# m [ diffuse grain-here 0.5] / W, F% D1 R7 Z% I
ask patches [# e$ e; h4 B2 h
[ set grain-here floor grain-here
5 C9 g1 \# W% _3 q2 B: r) U' c' k set max-grain-here grain-here 5 S( \+ M$ [4 e: |$ z' L% x
recolor-patch ]" K; ?0 E/ H- b8 R; W3 w1 t8 A
end
* |. @: J/ K. Jto recolor-patch
) x6 i) q0 e; E( J" E6 N0 v set pcolor scale-color sky grain-here 0 max-grain
+ d6 u) a2 m* `+ {end* U: {4 U% |3 }7 {5 f* y
to setup-turtles& P) f0 b- k- ^" s$ E2 }
set-default-shape turtles "person"% r `0 }7 H J! a3 f9 q: U4 a
crt num-people
2 t) K% f) @8 q! p2 q! [* H [ move-to one-of patches 8 p3 Z3 z. D/ s0 A1 ]
set size 1.5 ; a+ K4 P- b0 o2 U/ z
set-initial-turtle-vars-age% i! G1 o8 U, N* w; D2 h" y
set-initial-turtle-vars-wealth
5 C7 z! k) D; B6 }5 ]9 q set age random life-expectancy ]( S. M& Q8 U1 ?3 o5 D3 d
recolor-turtles4 x$ s e8 a' k% y4 ~8 P' m; J
end8 _4 o# q8 S/ v; e: l1 p2 B% I
4 T# ~' k7 T! E/ k2 m, \to set-initial-turtle-vars-age
* `- ~ ^- Q* \, a let max-wealth max [wealth] of turtles; p I/ U0 p: } b% K
( v$ J& V4 y' l& l
ifelse (wealth <= max-wealth / 3)+ v$ s4 Z t w& K1 U) d. y
[ set color red
; m. _' f) S+ x- Y" B0 D: a set age 08 s6 ]( U' p' c/ ~
face one-of neighbors4 % Y, D' G0 R) D
set life-expectancy life-expectancy-min +& `- q) k* q/ `+ ?
random life-expectancy-max
+ v" e+ ~* t @2 F% W set metabolism random 1 + metabolism-low0 D# p5 o! @7 E; H9 F# J
set wealth metabolism + random 30
% b$ p9 _) |3 l O set vision 1 + random max-vision
* J4 _( f% G! g2 t0 Q set wealth wealth + Wealth-inherited-low ]$ p$ |5 b6 d5 Q2 A* V- @( u: C
[ ifelse (wealth <= (max-wealth * 2 / 3))
, h: D6 j% y2 T! J [ set color yellow
9 ?3 J2 i- K! m1 S, k/ m8 Q! s2 ~ set age 01 x8 n5 D: y/ G7 Q" e
face one-of neighbors4
- d7 ~0 i' K1 j! H. s; @( d set life-expectancy life-expectancy-min +: m' V Y9 ~/ p- W9 [/ t9 J
random life-expectancy-max + 19 f, w" ~9 ~) l3 T" V8 Z n! w
set metabolism 1 + random metabolism-mid
# ~& q2 X- Z3 y8 ?( V& Q set wealth metabolism + random 301 q Q$ \. E9 R _2 Q
set vision 3 + random max-vision
a, r, D5 U- H. v8 y/ ?+ i' w set wealth wealth + Wealth-inherited-mid]
1 O2 q% s; t7 I% @4 { [ set color green
) M/ n0 K: |! q" S set age 0
/ l' O* Y, K% d1 O1 U face one-of neighbors4 & J' Q. x. J2 P1 g, \% J
set life-expectancy life-expectancy-min +# U1 n# m" f4 I- A9 Z6 E: L( Z
random life-expectancy-max + 2; ^4 u6 [1 m/ ]$ s4 l$ D
set metabolism 2 + random metabolism-up
# l6 S( T, M, }0 S: S8 W set wealth metabolism + random 308 ?0 ?: o4 b) m M8 s* @1 t
set vision 3 + random max-vision
' @ Z0 b) r4 I& m0 _ set wealth wealth + Wealth-inherited-up ] ] & i: {$ I; K% t3 ?% s
( }+ y" ]0 W( e0 i( ]1 b' hend3 g5 I% z8 I7 @+ [* s
to set-initial-turtle-vars-wealth- T7 |2 ^4 o' D$ i8 v' `) L1 w* Q
let max-wealth max [wealth] of turtles
5 Q) F K0 e) R2 w. S H+ j: V* u set age 0
- K! `1 K# M. Z% B face one-of neighbors4
6 S% W" n2 {0 E) P set life-expectancy life-expectancy-min +" l! ?, O4 z5 N) P: b) t
random life-expectancy-max
: U/ Q' E: s o0 g. r% d set metabolism 1 + random metabolism-up
) f) @4 P8 S( y6 n set wealth metabolism + random 303 c/ s0 g! x7 x
set vision 1 + random max-vision
" {6 e6 B- V' q! E, G# fend
9 g j& K/ c0 kto redistribution9 @, ~8 z4 V( _9 w0 j5 s
let max-wealth max [wealth] of turtles; {2 ?$ m0 X5 `0 u- n' }5 b
let min-wealth min [wealth] of turtles- b" n* d& F% z' F
if (wealth <= max-wealth / 3)" p1 `0 Y0 O1 D [
[set wealth wealth + Low-income-protection ]
0 u7 G4 \* Z6 O4 O4 S. l" n" yend! n) X6 y" O7 Y) \% a/ H; s$ E
9 V7 E8 f0 ~' Hto recolor-turtles6 b+ `" ^' A' F' Y6 l3 p: B3 N! Y
let max-wealth max [wealth] of turtles6 H$ j+ L! i5 [- u6 q0 b
ask turtles- w* R, r0 l5 c" ?8 _
[ ifelse (wealth <= max-wealth / 3): p g) Z% g$ K
[ set color red ]# D$ N% D `5 h- G# Q8 ~
[ ifelse (wealth <= (max-wealth * 2 / 3))
# Y) @0 h2 A- u. O w$ M [ set color yellow ]! Z& K/ P1 R9 n) k1 Q* R( B
[ set color green ] ] ]
3 }: N& S& d) n ?- Y/ C$ u) d5 ? ask turtles [ifelse show-wealth? e V. a; }% H
[ set label wealth ]. a" A/ e/ n5 X# |6 u
[ set label "" ]]4 C$ X: u, ^2 }! p, w- U+ g+ W
end
) v G5 z8 T6 I0 [. g+ F5 p( u) ^0 l4 r: O4 ~; V
to go$ S" q7 W/ c% J0 e. m
ask turtles0 {$ {. A. t" ~! b) F
[ turn-towards-grain ]
0 a" X! Y+ ~' X7 H3 } harvest
7 `3 `$ G, ]" g9 E5 ^% F: b ask turtles
* `9 `1 X! Y$ {5 _8 e& D1 j L( b [ move-eat-age-die ]
+ O) B" ^. o+ a# k6 o& f recolor-turtles
: g7 v, l: v- ^9 c1 Y( R2 m if ticks mod grain-growth-interval = 0
; a. \/ B1 G% n+ Y- U; v [ ask patches [ grow-grain ] ]
t' r) m' U7 [! u
; k5 W4 _' B2 L! x if ticks mod 11 = 0
! N8 u; Q5 w5 {2 L' v [ask turtles
& h& |$ r; }) Q) C G5 E! U6 b [ redistribution ]]
5 K/ f& k' U) [4 F ^ if ticks mod 5 = 0 v* c- D! p5 |8 K
[ask turtles# H* T1 {: d# c
[ visions ]]
' V! \( m5 m, g5 b& j& k tick
% `. X, Q) w9 \; D7 i+ m5 d update-plots8 e+ ^; |& [! g
end
8 x/ w* Y! e( @4 ]4 E" }3 j( ito visions" j% N& V! Z0 i9 K, x
set vision vision + 1 + f; I" j7 f; l* [" I
end
0 b7 I/ f% P: M0 e9 ^3 Z# b( b
) R5 G5 X5 h( n ]0 H* Y) x- J) T& R1 F3 L4 R8 m2 R
9 I+ J; I. p* b% k! H" A0 Wto turn-towards-grain + ~: Z( }; O# l* s4 k+ t! R
set heading 08 a$ T& d/ t/ }
let best-direction 03 `! E Z5 R0 W! `3 @* K
let best-amount grain-ahead4 L5 k& F; b+ J' q' S. C
set heading 90
2 A" T( A3 ~" Z1 s- B; K if (grain-ahead > best-amount) I# U7 L4 ^0 t% E/ `6 n+ f
[ set best-direction 90* ]* U5 j, r# k0 o6 V |7 N! m/ a
set best-amount grain-ahead ]
2 o6 z1 ~7 G, Q% E set heading 1805 b2 E) m$ Y* p9 q4 ]# E! `; t
if (grain-ahead > best-amount)* O8 q& [& g" r6 [1 D
[ set best-direction 180
7 K4 f* i; V- @- M9 G set best-amount grain-ahead ]
) L" d, B& [( C9 O9 H set heading 270' L: c% R" J. S
if (grain-ahead > best-amount)! O6 R3 E) C4 P7 a
[ set best-direction 2702 S$ H2 P8 f% t4 K
set best-amount grain-ahead ]
. H. V" `; B8 j$ o& r8 a" a set heading best-direction6 \; x$ E6 A0 O! _0 B3 ~
end
+ i* U3 S+ L: v: e0 }4 {; R+ `5 g$ _% C+ {: A* n% J9 ^
4 o4 T$ q2 M9 Q2 w: l6 A7 C6 h/ l
to-report grain-ahead
; B: i, \- h8 F& t$ b7 A let total 0
: j/ A7 V3 Z& M+ i6 G let how-far 17 q2 U2 s5 |' L2 W5 v9 f q- C
repeat vision
& S, P8 V" X6 i L3 U0 ?( G0 p [ set total total + [grain-here] of patch-ahead how-far3 d E$ N+ |$ W" f/ n5 x% c
set how-far how-far + 1 ]
, j9 Y" z) ], c9 B, J( d# y report total
* u [4 |. I% T& |end$ E$ J# ~0 M8 D; L9 m1 _
5 C6 e4 V4 S9 _- ~/ B! K) t' ~
to grow-grain 7 D# `3 t! m R2 S e
if (grain-here < max-grain-here)9 H9 M L7 [$ \' Z' o( C: t2 T
[ set grain-here grain-here + num-grain-grown; F7 p8 }4 j! ~. J
if (grain-here > max-grain-here)
( E( ~3 @2 Q0 v7 G [ set grain-here max-grain-here ]: }, o: u! M. n" |2 l' U
recolor-patch ]
8 h$ P8 T# [& i- m5 \end7 p! f' f, }2 r! Z7 j/ M" u
to harvest+ T0 o) [+ k% a& _
ask turtles
! \0 Y* {9 m4 ]7 B' k. r [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]; q9 ~/ E& J/ y
ask turtles' d9 b5 @$ n3 U5 t; y; K; {
[ set grain-here 03 T. J8 J1 ~' |; `& X
recolor-patch ]( H: e6 ~- {+ A4 E6 f
8 T4 ^- ?/ K( q/ K" t; p
end
, j7 K+ x; j. |8 d8 h) Q. `$ S5 W6 B# C4 H8 D; O+ I
to move-eat-age-die
3 m/ S1 }" ~) K/ q) h fd 1
5 e3 S$ Y. b$ l+ I g. E, r set wealth (wealth - metabolism)( ~, @: `# Z% \! V* ?8 d: V4 N
set age (age + 1)
$ S& c9 n1 m( q. J$ s6 p) a if (age >= life-expectancy). K# T" S' ], E, ]9 G/ o
[ set-initial-turtle-vars-age ]
/ |2 M9 M4 a* }2 C4 b9 r4 ~& u if (wealth < 0)
5 E. O( N' a8 D) L$ } [ set-initial-turtle-vars-wealth ]- \" ^0 g) G: C3 h
l. T' \! Y9 X' e0 Uend3 c* X: `- K2 U% ~7 U! e
& y/ \4 E! D& v
6 v+ Q) k/ F+ [+ m; Y2 P5 }to setup-plots
# t: {2 e8 Y, n& l- B6 _# W* p set-current-plot "Class Plot"
! l8 D% N# \$ l8 E* z set-plot-y-range 0 num-people6 [& [; \% o# D0 P. B; k! [% g9 S
set-current-plot "Class Histogram"8 d, `% I% V" k g: w7 n
set-plot-y-range 0 num-people
8 |& x4 G s+ S; @0 c- i4 [end
0 P' c* f+ @/ ^6 ?! v, W* V: y$ [9 ]# M2 y Q4 k
to update-plots
9 @* a) H2 i8 l Q0 l update-class-plot
' j2 x- G7 ~* A; D1 o* d update-class-histogram# G& Q; j/ |4 o( I& Z+ G' w
update-lorenz-and-gini-plots8 g. g( V7 l! k! W2 q
end
! V8 h) {1 {- R9 H+ n) Y
% q. S. e# K7 m4 ^% \to update-class-plot
4 z3 q4 L# M3 ^# e set-current-plot "Class Plot"
' A' n$ g0 ^' r9 I* A) `3 T- _ set-current-plot-pen "low": I3 \0 j# j4 [# b; j# c/ P
plot count turtles with [color = red]
4 E. e6 W: y4 ^9 n+ i set-current-plot-pen "mid"
( j3 [7 S3 E8 l0 H0 M plot count turtles with [color = yellow] m+ U& [. w4 w
set-current-plot-pen "up"
, z! `0 `$ a$ b5 o plot count turtles with [color = green]- Z8 v( b+ k- F2 k5 ?& S6 a
end* Z2 e- b! O) P( C, b2 ]( p- E
& F. ?2 w# X0 m3 } X
to update-class-histogram
* l) p7 n- W( e set-current-plot "Class Histogram"
( |. [1 j) a2 u4 e' j, X' |* D1 _ plot-pen-reset
/ F, \6 B6 d) A0 G9 C2 E4 b) j: F set-plot-pen-color red
$ x# Z5 K, q( q* B( H1 g plot count turtles with [color = red]" w \. _5 T7 o# _
set-plot-pen-color yellow
# ^) x# S! @$ n plot count turtles with [color = yellow]
0 W0 Z& Y# a* U7 p. Z: ~ set-plot-pen-color green, Y) s& V' ]3 D
plot count turtles with [color = green]) f. Q: ~0 m: n* j' P
end5 ~. Q9 H( R3 q) _( \
to update-lorenz-and-gini-plots
3 }7 e" `. |8 y. V+ P1 H set-current-plot "Lorenz Curve"
: D0 v! z" n* m2 A! U2 s) t8 e clear-plot6 D* u5 m7 v4 L' [2 ~
' y6 C7 `3 p4 [, A& q4 s5 q" {
set-current-plot-pen "equal"1 r5 y0 ^' x+ t+ `& d2 {
plot 0+ z) d J; v5 U' A3 y' ~
plot 100
" Z' [. G4 a" @& L; t# G7 D {8 s( i
& m3 o4 H' b8 f$ L# V set-current-plot-pen "lorenz"6 u4 Y, w0 r; n, Q K% a- t
set-plot-pen-interval 100 / num-people
$ W8 O/ z& j0 x9 D8 W U plot 0) v9 N0 z3 l8 h$ Y7 ?+ ]
1 ]9 o( ^, x6 O0 t9 j+ V6 n
let sorted-wealths sort [wealth] of turtles" Y0 X! W8 q* J. {, H1 F
let total-wealth sum sorted-wealths
& O& G0 P8 }( Z% S# N1 K let wealth-sum-so-far 0 C$ o& I/ p- h" i+ Y/ k R- v
let index 0* v9 V$ u. d; G
let gini-index-reserve 0
( J$ P- L1 ~; J, g1 p) {: v4 _" ~" n$ i+ u
repeat num-people [7 ~% f+ ^9 N; e5 N6 l2 f
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
5 O8 ] i9 R$ s) f/ s plot (wealth-sum-so-far / total-wealth) * 100; ~2 N5 ^# E0 R+ X) A
set index (index + 1)+ k7 u2 {! h$ t4 a( o# T& y
set gini-index-reserve: x! g% i3 ]. i
gini-index-reserve +/ H( \1 t: ?' v* |' w" q( b
(index / num-people) -1 ?& }4 O" H3 g9 v2 {/ \
(wealth-sum-so-far / total-wealth)( J8 e! m& W: ~, y, M
]0 K- F- `- n- h( T
0 {0 Y; D% u/ @7 S0 G set-current-plot "Gini-Index v. Time"( R3 t" {8 m6 _ k
plot (gini-index-reserve / num-people) / area-of-equality-triangle$ d1 c5 J9 h7 I) |1 c
end
$ Y" }, K; m2 \( Kto-report area-of-equality-triangle
! @7 z8 }$ F4 B3 R report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
; r! ]3 @" o+ `; o& @: H* d" [2 rend |