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7 r+ Z2 W) M5 e. t
globals% p+ e% E: { p3 |/ v S
[
' z' u+ f5 t5 v% V% K7 Y max-grain 7 f0 S" V& `) f2 R
; u; u- }# v% x) K% e+ ?: m]: p. Z6 O% K7 P6 D
9 H" |( k8 h2 Y$ V9 ]: O* P4 G
patches-own+ z( s4 V9 L7 r; _, `: O8 N C
[
5 b4 ~6 Y6 G3 p. Q$ S4 [ grain-here
S7 v! [# M0 i% e% ^5 g max-grain-here & c. |/ m: G! V7 L$ p
]$ {' Z8 r! N7 h8 u& b- G7 M8 J
2 e& K6 c3 D# W! e |% v0 S f9 `, Iturtles-own0 `- R$ C+ |: R% h w! `
[
. [! C, y. v) T( |6 S age
/ E- [6 _ B" z3 O; V: w wealth
H3 J& J: K. c life-expectancy ) C$ ]$ `# G. {* a7 t7 z
metabolism 3 e1 i. y# y- G7 E' ]
vision) ~/ K, a" S4 q0 w. k7 [" @+ v
inherited
# v; i2 j! B2 ]9 s2 B. W]
3 ~8 f2 n6 Z0 ~
" M% r5 I) P# s
5 V& P, v6 G# i. E* x% j6 @+ [to setup2 M8 p+ l1 D/ @/ K$ ~+ g
ca. ]+ U+ M5 B" ~8 ^4 ~) }7 G) X
set max-grain 50% ~% q; ~ J# `9 Q; y* i
setup-patches* ?, A5 L( H x
setup-turtles8 l' z3 P! ?4 F. Q) ?* _, i
setup-plots
* Q/ N# Z5 w* G7 N update-plots H: A' u( w, [) T
end, C' ?- D$ m2 A9 W: Y4 A
to setup-patches4 P9 }0 ^" z/ j
ask patches h- ^' x! F4 w* c& i0 H6 d
[ set max-grain-here 0 n9 @4 A3 `+ O; k! p2 L
if (random-float 100.0) <= percent-best-land
2 z. T& v8 c2 M: h0 Q [ set max-grain-here max-grain
! U& j8 b5 M& d2 } set grain-here max-grain-here ] ] O! G! s6 d& D( L
repeat 54 q2 A8 u, I, `7 B" f' I
[ ask patches with [max-grain-here != 0]
4 a! n9 G6 O: k9 t5 @$ D) t" \ [ set grain-here max-grain-here ]/ R' \/ I" x$ @, K
diffuse grain-here 0.5 ]; B3 v! N% z( g; B/ V e
repeat 107 D1 V9 e8 N" Q, W. p: [
[ diffuse grain-here 0.5]
/ E" T7 v9 s$ V* L, C1 B! m, F ask patches8 ]5 o6 P& V8 J$ Z9 W/ {
[ set grain-here floor grain-here 2 q: u, g" q( O& r+ x4 B, a! z
set max-grain-here grain-here
' b. I I D; n5 { N) N1 ]% X+ J recolor-patch ]
& J& x! I) Z0 \end0 U3 K6 |! K4 U& R1 z. B, X: {
to recolor-patch 6 p( T% p* N3 i+ s
set pcolor scale-color sky grain-here 0 max-grain
8 {' F) l6 `4 |% S" N" @0 Y4 kend; v$ J+ d9 @. i o7 t* I. x; b" U1 c# \$ t
to setup-turtles
" c* m! W& j: p! ?) i o set-default-shape turtles "person"
' ~" \- J' _! D3 @3 x8 ]6 e crt num-people4 A# c+ T6 `/ y& |3 t( w
[ move-to one-of patches
! d, z* x9 B$ w4 N% | set size 1.5 8 T3 a/ l; t" |( k2 z
set-initial-turtle-vars-age2 w/ Y. r0 ^; J3 D6 F& W
set-initial-turtle-vars-wealth
* x) a) `3 V+ B% I8 L( B; A4 T! { set age random life-expectancy ]) f5 J% k& Y) j9 ?( p6 A
recolor-turtles: D9 w8 ^- D' U4 }! v0 {5 i9 m7 }
end! X) p6 d) s# j! z/ E: V" t4 ]
' H; `+ G3 |! M/ f# M, n: Vto set-initial-turtle-vars-age2 X) g5 }3 `1 u7 Z* O; B+ p
let max-wealth max [wealth] of turtles; |6 ^, V3 E% t; R
2 M" T. E2 ^ K! x: o
ifelse (wealth <= max-wealth / 3)
4 S8 Z/ X1 a/ I" q6 U1 Z: w/ R& I [ set color red
% u0 f9 I$ H5 W5 \ set age 0- f" _5 }: m L& s0 l8 {
face one-of neighbors4 3 H* x* Y5 j1 |- V5 c
set life-expectancy life-expectancy-min +
* C8 j- ?- G& N$ I random life-expectancy-max
3 [% [- r9 l' y1 a. z/ N' ~ set metabolism random 1 + metabolism-low6 @, W, a& `; E3 m0 o
set wealth metabolism + random 300 T, m; U) S1 w) y) s0 E
set vision 1 + random max-vision, D2 | F: @1 R2 w+ u4 e/ i0 e
set wealth wealth + Wealth-inherited-low ]' }9 y# k& K% W, R
[ ifelse (wealth <= (max-wealth * 2 / 3))
' W; {8 i8 Y3 Q& c [ set color yellow . h H, C F2 X' B6 n' b: Q0 p7 b
set age 05 w! O( m1 b1 q j: a7 x
face one-of neighbors4 Z# p. D: i& W. L o) ~
set life-expectancy life-expectancy-min +' d8 ~9 s5 A; U/ ~/ S1 V6 y
random life-expectancy-max + 1
$ Q R; w9 f3 t. J$ _3 O* Q set metabolism 1 + random metabolism-mid. |4 [# o- B) f7 v
set wealth metabolism + random 30
0 w% S: p" n) u# v set vision 3 + random max-vision
1 p) U7 e5 ]/ v( e2 U8 ] set wealth wealth + Wealth-inherited-mid]
& a1 H# P* u9 P! j6 A [ set color green
* _7 n& V# A6 Y6 l0 P8 X set age 0
- r- t w, h; v8 h+ o face one-of neighbors4 9 I) z4 Z. j/ ]) \7 V% e/ f7 w
set life-expectancy life-expectancy-min +
3 }0 c4 C; o2 L( ]* @: D# B random life-expectancy-max + 2 Z: k+ V. a# f7 k4 P
set metabolism 2 + random metabolism-up+ F/ r3 Q+ S8 }
set wealth metabolism + random 30
$ A! C o8 ^( u1 `' I set vision 3 + random max-vision5 e9 C! Z. k; l* `9 h! W
set wealth wealth + Wealth-inherited-up ] ] 4 K3 w5 M& k! w# R7 Y5 A1 B4 k5 M
/ A0 G: m" Q8 I7 d8 Rend u* a# @& b! q3 p0 k/ z
to set-initial-turtle-vars-wealth
$ |. g8 Y) {/ u4 u let max-wealth max [wealth] of turtles
# Q, t8 }8 N* W4 e: y, u5 r set age 0
4 ]) Z: e, b, X A b0 E face one-of neighbors4 5 r$ Z+ ^0 W0 Y. }; k
set life-expectancy life-expectancy-min +9 H7 Z& C" ]1 ^- ~" T( [3 E4 H
random life-expectancy-max # R5 y* j! b, @, W: B. U
set metabolism 1 + random metabolism-up2 p) C2 }( G, B7 E: D
set wealth metabolism + random 30
2 T/ _, G, k6 N1 q3 b+ n# r9 c set vision 1 + random max-vision ; r& ^/ J4 e, U6 [7 x' {. G
end: {8 q1 M! e. _, Q
to redistribution( E) U- E9 T: p) ]
let max-wealth max [wealth] of turtles
0 D) U. R7 @$ D% @5 Y' i+ elet min-wealth min [wealth] of turtles
% [) q; U2 d8 dif (wealth <= max-wealth / 3) d. G9 l2 u6 j6 ^4 g: O6 u
[set wealth wealth + Low-income-protection ]& _. J0 L. }" t( b& d# X% F
end
4 w* h' j# w5 W' b9 Q* c
) a5 r% R! O- a6 ^ Pto recolor-turtles
- n# ]0 o# g3 j) V: O' X- ^, ] let max-wealth max [wealth] of turtles
4 U* [7 x% q8 C3 l, w ask turtles
+ s- n3 ?7 A! b" ^5 H [ ifelse (wealth <= max-wealth / 3)/ P2 z- P& \2 c x3 u. ^$ I& R6 |
[ set color red ]' |% y; L( N2 V0 L& k) g# P
[ ifelse (wealth <= (max-wealth * 2 / 3))
G: J% Y# b" X% M7 T [ set color yellow ]
' ? D7 N6 Q! c0 o5 h# `& W [ set color green ] ] ]: Y9 S; @; c! x. h. p% n
ask turtles [ifelse show-wealth?
* v) Y% b4 H1 C: ] d, T [ set label wealth ]
& p8 |: L8 b8 F( @! Y* ?3 p [ set label "" ]]0 s2 ^1 N- D; d; M- |
end8 Q+ O7 g6 E6 S7 [4 @
8 C7 D5 F2 ~+ ^1 u: \. l& ?
to go8 w. T" G: B [" r/ ?/ c
ask turtles$ D) ^: k L; c# X( G
[ turn-towards-grain ] . L9 m, T% @: ^
harvest
6 H/ _* b# y4 y: a& v8 F6 t. \' q5 Y- v ask turtles
/ ~. R/ s: j9 `2 G% d1 v [ move-eat-age-die ]
& O9 W3 Z3 X; W5 V" J( R6 A J recolor-turtles
) [. N& s* x; K' s' F if ticks mod grain-growth-interval = 08 m, E6 N. B$ @( G* _6 {/ Q) I3 o7 l) w
[ ask patches [ grow-grain ] ]0 N8 [3 O: f7 i7 h% U6 w
6 s9 J/ g0 e( M- g if ticks mod 11 = 0) F O, o* W* i
[ask turtles+ N1 }& Y3 U$ s9 J2 e, j
[ redistribution ]]+ Q6 U) G# t _7 m# P# S- _! e
if ticks mod 5 = 0
; s3 W, ?; p9 U& I0 {& \9 b. r5 i [ask turtles1 m) ^+ \. L5 ^1 ^3 n9 b2 O' D
[ visions ]]
) h. r, y+ F8 t' D tick2 b0 e, I& ]4 p
update-plots
( c, F# E% |) Rend
5 A# R5 N n4 B7 D/ Bto visions
, [* V/ R7 G: B5 ~ set vision vision + 1
) z6 N( [5 T3 V" c2 uend
- g8 U! U" W2 d
6 j7 _# u: m4 [8 y6 s/ @
) T0 V' |* W/ Q& q9 b
1 q. D8 C! e" Q ~& M2 F$ Bto turn-towards-grain 4 C- Y% Y8 Z" n( ^6 ]6 ` v, ^
set heading 0
9 e6 f* l/ x8 j E0 P+ J let best-direction 0% v* b; J* A& N, C2 C7 `0 z
let best-amount grain-ahead
H. Z4 G# K, `0 _: h3 j+ G6 | set heading 90) o. e3 K' H9 c/ b/ |' G8 e
if (grain-ahead > best-amount)
7 B" Q# L1 ~ g; X+ Y [ set best-direction 90- B- C5 R/ n6 H+ [, I. O/ {
set best-amount grain-ahead ]/ D9 A+ z0 |9 S- L( |; u
set heading 180/ W% Q2 \0 ~7 C% B3 B" f# r: l* l' ]
if (grain-ahead > best-amount)
( I5 v; I; k4 c$ B( I5 M [ set best-direction 180
}1 z4 {/ w# m w+ D W2 [0 k set best-amount grain-ahead ]
& }$ k. Y+ V4 ~6 m: D set heading 270/ ~: ~2 ` \9 ?! s0 i/ q
if (grain-ahead > best-amount)
" r ]' [+ A$ b( Y) q6 N' S [ set best-direction 270
& X+ T8 ~& t9 v: M& w set best-amount grain-ahead ]
3 X% C& _5 z' i set heading best-direction( k% n6 n# T7 D4 l1 O
end
% H- `$ o1 s9 S2 H& e2 D* z3 A0 y9 k: @' i- T3 e
/ d- H# \% R& }
to-report grain-ahead ( c6 |1 x+ }6 |: j# o5 r0 ^0 P
let total 05 b. x5 {: M- o0 c
let how-far 11 Z* ]3 o/ h! m8 S, v7 M
repeat vision
2 p; |/ q. }7 P0 p [ set total total + [grain-here] of patch-ahead how-far
+ v# C$ p% `, |' L set how-far how-far + 1 ]2 z7 x0 H7 I4 W/ W6 {
report total
' X9 q$ W& J8 Bend% m9 u. E, h- v# ?
7 @% a# o4 m1 V3 ?to grow-grain 3 `: w2 O( e ]3 G0 M9 W, n- I- F8 L
if (grain-here < max-grain-here)$ Y3 Y! f; h9 @9 m/ r
[ set grain-here grain-here + num-grain-grown
8 K) U. `+ n, y* V: T& N6 s if (grain-here > max-grain-here)
. X0 B, I( s0 a, j- o) N [ set grain-here max-grain-here ]4 h* ]0 |, @1 {5 h
recolor-patch ], ?$ J( d) d6 j) p
end) {, O6 R5 {0 ?4 F+ { w4 E
to harvest
& [+ X. d% \. W$ L ask turtles
$ [. m& |+ D+ l+ |0 S; ? [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]; J" M+ n) o3 e7 d* L- i8 P5 k3 j
ask turtles, q) Y: O/ {( W/ f
[ set grain-here 0
' c. ^4 X' z) i recolor-patch ]
* _* e( L( G$ E7 c( C5 x: k5 W $ H, g P" s) Q2 S" ?! X5 g
end
7 U) }5 E+ d+ G; d( F$ Y% M9 \2 _: J3 W5 Q! _5 ]( c8 N0 o# e
to move-eat-age-die
4 m% r/ \5 }' _! H fd 1! ]* f6 R$ C" j) g5 E
set wealth (wealth - metabolism)( _! o7 |, K5 U' K
set age (age + 1)! @: H: O" _* ]- d z
if (age >= life-expectancy)6 c) |' ?( E0 ~
[ set-initial-turtle-vars-age ]1 h6 M! k0 k6 T: h% R
if (wealth < 0)4 I' K. S+ e) U) D% p0 E
[ set-initial-turtle-vars-wealth ]
" _0 H" q5 v* [! A; @ s
, v$ ~7 E# C1 a" K& \, Rend$ z& F- H# N5 l9 |
5 h+ C6 _+ M/ p( |4 J" c6 m3 B0 `4 y+ \" ^2 ^9 `4 o
to setup-plots) R( p' {; C% ~: S. |9 `$ @0 y5 [
set-current-plot "Class Plot"8 z9 V+ I! j8 R% z+ A
set-plot-y-range 0 num-people
6 e. Q2 m' a/ i" T% U& g3 X1 c$ l* r set-current-plot "Class Histogram"
( L# T- H0 ]. {2 K9 u: x set-plot-y-range 0 num-people5 R( a$ J1 V U( O0 h- n: n
end
( T9 K& G0 E5 d, ^
9 Y/ U( n" a# l# U {! A, D+ X Sto update-plots
% M3 }# f0 |7 _! q" z, e. d% b update-class-plot. T2 P: `$ U5 f) I
update-class-histogram0 X/ f- q( V5 ]/ T- X& p( W, P
update-lorenz-and-gini-plots7 ~. @. m) Z- m9 `% r: |6 m4 F
end5 J& i) G) C0 Q& Y" {# m: w
& [6 o' ]8 y0 i Ito update-class-plot
( k7 A' [1 S2 D5 y5 ~ set-current-plot "Class Plot"; m! k0 J" f( Z# r! C& D/ P; b
set-current-plot-pen "low"
% f. ~2 K- X' q. [- P/ Q' L" l l+ I plot count turtles with [color = red]
+ F$ `3 b" J7 b. G! a set-current-plot-pen "mid"
& P8 P0 A5 I/ q! v! M5 T! e+ {: m plot count turtles with [color = yellow]
! A6 k! l8 |9 T1 c' p; J6 z; o0 [ set-current-plot-pen "up"
0 N" _4 b( z7 g" v* m plot count turtles with [color = green]
7 p! M- X* _7 ~4 s4 Bend
: g# J$ M* W8 l4 T7 E
/ H. i) ?) J( L& Sto update-class-histogram
' {1 e* H5 i# h1 ~- Y3 u set-current-plot "Class Histogram"5 n* I& d# B1 [$ H2 D3 u/ P
plot-pen-reset! Y( h) Q \. D' ^) z, O5 q- t$ ?
set-plot-pen-color red
! J9 P' _2 V+ Q2 v plot count turtles with [color = red]
+ @* u: b8 \; t/ C8 n set-plot-pen-color yellow2 v" @1 b W; H. S2 T& g' c" z
plot count turtles with [color = yellow]
; l9 @2 T7 h. H set-plot-pen-color green
. X2 u1 H$ t0 ]6 v3 Q plot count turtles with [color = green]
, k5 l1 o7 \9 H: [end* ^& H v5 p3 @
to update-lorenz-and-gini-plots$ n. x+ Z6 {) u" }: v# C- O
set-current-plot "Lorenz Curve"
; T5 P0 A3 s2 ]0 {3 q clear-plot: A% I- [# Q% S3 d0 A
4 Y" b5 v2 b7 R- {' E5 A0 F, R: l set-current-plot-pen "equal"4 k& P, {: @) r( H
plot 0/ @, }; j) b+ \5 L
plot 100
* i6 z0 B4 X" s' O) O2 c0 x1 A5 m+ t' k5 o) v7 s* q
set-current-plot-pen "lorenz"1 [% ?$ B5 k* J. u: T* o/ {5 l0 _
set-plot-pen-interval 100 / num-people8 S; J% D/ K& X- ^( Z
plot 0: g. I u! s6 s. L, ?
& T% P- R1 g6 m& g2 ~
let sorted-wealths sort [wealth] of turtles
. S* a" [2 p( O5 a4 l. c% V let total-wealth sum sorted-wealths' t5 _' B8 L' g
let wealth-sum-so-far 0% i2 X8 E5 _8 @ K# x3 g
let index 0
4 c2 G. I7 G. _& @- Y. S6 ?* D7 X let gini-index-reserve 0
) j3 R J4 G% Y7 a1 V. `7 {' [3 ]! n ]+ h
repeat num-people [
# w+ h2 [) x- ?) _* } set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)1 j) ~% `. T+ z! ?/ D, e W
plot (wealth-sum-so-far / total-wealth) * 100
H- v3 g$ R9 o3 i1 K7 m set index (index + 1)
' O, I5 B: a3 x2 q) I' a set gini-index-reserve. g% \" Q& y- a/ X$ @7 v
gini-index-reserve +7 [) t* }7 P6 G' U% z
(index / num-people) -
, Y# N$ D( Y/ ?" `+ t (wealth-sum-so-far / total-wealth)
/ j/ Z$ K Q- k6 v ]
4 t4 e# m1 ?" {- i Y, p0 l6 Y
, z: l& \' U, Z: ~. v2 U set-current-plot "Gini-Index v. Time"
5 U) t# @* v/ f/ ] {1 d plot (gini-index-reserve / num-people) / area-of-equality-triangle
9 h: S- \5 h T6 Q& r$ tend0 ~2 q2 g& [6 Y/ \
to-report area-of-equality-triangle" a: ]) q* b" N& b5 o
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)% ~4 F- [3 k& I( H% k+ F
end |