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
0 m) K" j+ Z* g k; Y: `; d/ [3 O" Kglobals
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% A9 W. p, S8 {) v, n) ?7 f$ X8 W! ? max-grain
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! p5 E7 _; x# o! ]0 P% }9 z! |patches-own* m; L5 s* G* i7 c: M
[
; G6 {, O O5 C: K7 j0 J+ } grain-here
" i; _. A( _6 R8 {# e# y, Z0 l max-grain-here ) E: D# P# M$ h) j
]; o- m) @0 V# l) C9 F
; L' b! x$ h& i. L3 J F5 x4 i
turtles-own
8 E, P1 F# ?, a( ]' b! q[
" f' \: R8 F- h! \) z' x8 L) Q2 l- E age
' p1 n- v* G# u9 v7 P( T wealth
1 W9 I1 ^# ^0 U8 s0 T, @- w2 C life-expectancy
2 l& ]' _% @$ _5 T9 `5 B' g8 U: g+ m metabolism
* \2 Q8 d( Y1 R7 F6 Y B vision$ h2 w8 b$ b" r9 N& N
inherited
& s) W* I5 ?) J, @ []
$ K3 ^% D: j7 I" u5 c$ {% [( R) v5 c2 ^' b9 M9 N/ i4 F
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to setup0 i; V3 J3 u8 b6 x$ T! w% I
ca5 g# s/ J+ g. M0 v
set max-grain 50" H9 P' b q2 T/ e' y
setup-patches
! P" {7 X+ Y) K! R. ?* ?9 j/ Q. w1 f, Q setup-turtles" V l3 F" j8 x; Y! Z" m" a
setup-plots' j# R& \' X- Z) D
update-plots
! _$ m' a, O6 ?end5 |7 k3 m% v( A5 ?/ R
to setup-patches
, Y* D8 L; @% b6 x. h ask patches8 B( U& _& ?: U. i; ?. n
[ set max-grain-here 0/ w Q& X( P. \
if (random-float 100.0) <= percent-best-land P1 ^$ y8 v! O1 s$ m7 a
[ set max-grain-here max-grain
2 z- Y/ {, [7 G; U& j set grain-here max-grain-here ] ]
$ x) H g5 [( E repeat 5
0 D! ?0 a# W6 B U/ r) k [ ask patches with [max-grain-here != 0]
0 x+ S* g* r! @6 a7 E0 V) a, e. { [ set grain-here max-grain-here ]- ^ j; I$ Y2 z) e+ ]4 q. M
diffuse grain-here 0.5 ]: l/ J- N! X% Q
repeat 10
8 q x M6 `$ `3 Y" l4 | [ diffuse grain-here 0.5] ( ^0 T1 a' m r$ V5 _) H
ask patches+ U# Q5 s2 t% v5 U
[ set grain-here floor grain-here 9 v( V: C2 T3 |8 J
set max-grain-here grain-here + k' W# t. p4 m: N c \- n: T
recolor-patch ]+ `" h% W: K0 F- |7 w
end
! t* o& `( T& R4 C, e/ D, Zto recolor-patch
' A1 W. |7 a8 J& j5 q, Z* s set pcolor scale-color sky grain-here 0 max-grain
! o3 }$ u( a5 Q' p5 zend
. x2 x1 {. Z X1 N% B! pto setup-turtles
: c* J. t5 M) e; J! Y# q set-default-shape turtles "person") N# R& U( p& C: N' |
crt num-people
' t- e9 D/ \( Q: K$ N4 z+ D) _ [ move-to one-of patches
^% g1 x0 c/ N4 u9 C set size 1.5
1 k, L- U5 {/ k set-initial-turtle-vars-age. y& E+ m; i3 U" Z: N% D
set-initial-turtle-vars-wealth0 t7 B9 i7 @5 E# e$ w# N
set age random life-expectancy ]4 f/ ]5 D" q2 N# W0 ]) F" ~
recolor-turtles& @. H, n. t" U5 I# p& I
end
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to set-initial-turtle-vars-age. G5 V- F. U1 O- h7 P; |
let max-wealth max [wealth] of turtles& `- S+ W! e2 |9 y) j8 B, [
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ifelse (wealth <= max-wealth / 3): e2 l% k. |4 [& P }% P( a( @1 t4 j
[ set color red
" s2 U# U: |# k2 I set age 04 a1 S7 Z! R$ A5 Q+ o+ b' N
face one-of neighbors4
, m4 C0 y' [( C: K# P. U; ] set life-expectancy life-expectancy-min +
3 k9 ^! t+ E! l- Z% Q4 q3 ^; z random life-expectancy-max
3 X$ ?. x0 X" I, w& y set metabolism random 1 + metabolism-low
9 L+ U a. ~' Q- G G set wealth metabolism + random 30- U/ |8 O, `, m0 ?
set vision 1 + random max-vision( o" X* \# m2 j2 B+ K0 A, B
set wealth wealth + Wealth-inherited-low ]; G# m1 ~: Q# b5 @& R! M
[ ifelse (wealth <= (max-wealth * 2 / 3))
( V: p6 z, B% n5 i [ set color yellow : O3 t# N/ ?6 ]
set age 0) \6 [$ S' E# y6 {3 D7 m
face one-of neighbors4
7 X( X. D P& A. ^2 `7 G- D set life-expectancy life-expectancy-min +
; }; l4 k4 ~5 U0 Y6 e4 h7 y1 }# ? random life-expectancy-max + 1
* O& d! n! v. w) w9 Q set metabolism 1 + random metabolism-mid$ o- c% J2 W, N2 z# I
set wealth metabolism + random 30
, \1 j. Q9 t- G7 q set vision 3 + random max-vision
" U- C H$ U4 ] V0 Q. V set wealth wealth + Wealth-inherited-mid]
0 N$ b, P3 [5 M9 H9 j( ?& J6 A6 q [ set color green % q2 Y9 i! A" b8 a4 E$ v' a9 e
set age 0
" V0 I* M+ W% _! y, L& h& v. L1 g face one-of neighbors4 & w3 ~3 P2 |1 v# c
set life-expectancy life-expectancy-min +
0 E: b; D/ U1 n6 X$ j/ L+ a0 X random life-expectancy-max + 2
, f$ a( B8 M& q3 t0 n0 X P set metabolism 2 + random metabolism-up/ M$ J0 {! I4 T9 U) h# Y3 L. ^
set wealth metabolism + random 30; g& O L+ w) s" K4 _# R
set vision 3 + random max-vision& g! n! }& w7 k; Y+ x+ A O2 X7 L
set wealth wealth + Wealth-inherited-up ] ] ; u' }6 H( t$ {( q+ F% N+ @3 ]
9 c% a5 g. t6 k5 Q: c4 ]
end5 Z# D, ?2 {7 D. E1 d. R# ]' i
to set-initial-turtle-vars-wealth, ]0 V6 n$ j, q/ u5 A
let max-wealth max [wealth] of turtles
8 V) s. z; Y3 X* x5 o$ w+ S% k6 d set age 0
$ F3 Z8 R! H- I) `, z7 ?7 F face one-of neighbors4
5 d& f6 w) d9 `2 |0 `' B set life-expectancy life-expectancy-min +/ p! f, H/ ]; C; x9 ]: t
random life-expectancy-max
# u% ]' v" t: X4 S* d set metabolism 1 + random metabolism-up4 y. w- [* t- W4 D7 f) r/ ~- n
set wealth metabolism + random 30
$ M9 z3 F/ k0 M8 K! f set vision 1 + random max-vision
X( k7 E8 n! x2 i7 xend; z$ f6 z5 ]3 V2 R
to redistribution
; E4 z/ S2 ?/ [8 c/ m: Tlet max-wealth max [wealth] of turtles, E+ I- ?/ K1 f) r6 E* F
let min-wealth min [wealth] of turtles5 W( G/ q1 N7 {1 w% ]
if (wealth <= max-wealth / 3)5 `/ A" {# ~! K; z+ B+ {; i
[set wealth wealth + Low-income-protection ]1 i+ c4 `* m+ B0 o9 n
end$ ~6 O3 H: `4 _! D) w1 o7 \' }
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to recolor-turtles2 u4 ^4 _( h* C
let max-wealth max [wealth] of turtles
6 n0 d! O6 z' P1 V. H% f ask turtles
~) ]) `% v# C5 I4 z [ ifelse (wealth <= max-wealth / 3)
9 [! K) W) o3 ^7 k& G4 u [ set color red ] V$ E- M) d% x) S7 O3 E
[ ifelse (wealth <= (max-wealth * 2 / 3))& ^: A$ v/ w) w( I; X
[ set color yellow ]
% f: V- @7 ^# l$ m [ set color green ] ] ], v1 z$ ]5 l" p7 L3 Y' R: }7 M
ask turtles [ifelse show-wealth?7 @9 h5 `/ Z$ X* M4 a3 L
[ set label wealth ]$ m( q( O: w) T, W( m
[ set label "" ]]8 p) H+ O3 c4 ?
end
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to go
6 O6 H; c$ I; g% x, B2 ~* m ask turtles
3 T: X4 w3 s: o; |5 { [ turn-towards-grain ] 0 o7 l% Z: D0 w/ g
harvest
1 M9 ^" P2 d/ T( @ ask turtles$ ?# F) M: h6 a2 C
[ move-eat-age-die ]: I" X0 T$ o- w K7 o. p: ?6 D
recolor-turtles
. h% t7 q3 }9 Y$ A5 B if ticks mod grain-growth-interval = 0
# _( }) f* M5 Y9 T+ Y [ ask patches [ grow-grain ] ]
5 \2 R( U1 i/ d7 i2 Q5 s . c( A5 \6 y# e5 M
if ticks mod 11 = 0* t5 _- a( ]9 W- x; `( B+ Z0 a
[ask turtles" l8 [9 S0 [! Y& i. M
[ redistribution ]]' R6 A: D4 E1 z. j5 E1 I* c- L
if ticks mod 5 = 02 y2 S, q6 ?* e' a$ u. o! ~ F
[ask turtles3 ?7 H# D, K7 a
[ visions ]]
$ {7 a, h ^1 N& N D tick% O8 [( a! X5 t3 f$ ]/ b0 b
update-plots' I: g& L5 A' }! a5 Y0 I- I$ b/ B
end
* h5 H3 |, v: Kto visions
8 i: Q/ m3 H9 j& Q$ J7 j set vision vision + 1
& E/ {8 e* [1 x! ]end' n1 Q1 r5 z. ?. Z- k% V9 Y) X
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' w9 [ N+ P- N. |( e6 {$ V
4 D% Y; c7 w* L% C. b' t( hto turn-towards-grain ( v5 B, X* M) c7 e; N: c
set heading 0: F" H, s, t1 Z/ d( C
let best-direction 0; A& F; o1 p. `" l$ U
let best-amount grain-ahead: E- L" ~, Y, l) w/ j' u7 l" i2 w
set heading 90
1 A5 q! ~% l E7 u3 o if (grain-ahead > best-amount)$ w# D: w; F2 Z$ z: C. S" c0 {( O
[ set best-direction 90( D1 u+ d ?7 Z1 \
set best-amount grain-ahead ]
9 [/ J4 \$ \. Q# s4 @ set heading 180
4 U X* t/ _8 g! g- o3 L6 b if (grain-ahead > best-amount)) A9 X; u- G9 c: A( _, }% p! W* G1 v
[ set best-direction 180
. x! {7 e. ?0 _8 C/ M- t set best-amount grain-ahead ]# o7 c: \) v% [9 _% j3 k3 t
set heading 270
4 X% O/ u* g5 L5 _' D; ~ if (grain-ahead > best-amount)" I8 i0 W9 l) F3 i6 S( J) F
[ set best-direction 270/ ?# p0 E) g3 @3 F, ?
set best-amount grain-ahead ]8 v/ w/ e% u, M$ ^" u( Z$ S
set heading best-direction
5 U S _( U: Qend! ~" ~# T2 R3 j5 P4 ?9 P* e8 A+ [) d
4 v# _4 O! V) {+ N: @1 w( j6 K e! {+ ~: a1 _1 e0 Z
to-report grain-ahead ^3 k; u/ s1 D& ]# R6 Z4 O& |
let total 0$ `$ c, y. u! J3 \/ N+ Y4 M
let how-far 1
* @- L0 |, a0 C6 e0 ] repeat vision
; t- | R* d7 Y [ set total total + [grain-here] of patch-ahead how-far
" G" b2 p" L3 u set how-far how-far + 1 ]
" S- x0 A% e7 P7 n6 K report total% x7 M/ T$ z2 ?+ X' ?4 P4 m3 Z
end6 s4 k b: ~3 t$ {: o& M
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to grow-grain
. ]. M5 f" c4 M0 K5 b3 A- d& V if (grain-here < max-grain-here). d. g% Q# y1 ?8 I
[ set grain-here grain-here + num-grain-grown
8 ]1 n, \; L0 M. a if (grain-here > max-grain-here)
+ a% G4 F! k) N5 u$ g [ set grain-here max-grain-here ]
% f1 o; j4 X; z0 x+ c recolor-patch ]
; @2 |0 x" W: P4 jend
! b2 k; L6 b) x' eto harvest
$ R B( D# e9 {6 t- i# n, b ask turtles
: t# R% ]" X4 R# c, @2 ^3 g [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]; x& `8 e% H% S6 \3 I
ask turtles
2 r# S% @7 b. [3 i. u [ set grain-here 0
* e% i, l8 `3 h2 n recolor-patch ]! l" u' ^" b: q' w- L8 o
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: [4 j" Z& e) [$ `to move-eat-age-die
! `8 x3 \1 h& L/ ~8 e' S% P. \ fd 1, {; J# W% y2 B( W4 n7 d
set wealth (wealth - metabolism)
4 d1 _; \5 u0 a9 j. s2 b set age (age + 1)
4 R5 P7 m+ d& }3 ?% G. F if (age >= life-expectancy)
7 n f0 _% n- i2 u N4 g" `2 N [ set-initial-turtle-vars-age ]
% ]" g; ]$ H- V9 J if (wealth < 0)! _* e2 d: j' d( a! C3 n
[ set-initial-turtle-vars-wealth ]6 @1 H+ y/ a3 u3 |
2 B0 C( ^& ^* F" Y) i, C5 g' |end2 U4 \6 U, D1 B0 E- _- N
+ f: b' d6 h1 |( b+ ^$ @
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to setup-plots% Y: V* C K( s( ^9 |- H2 m
set-current-plot "Class Plot"
: N! S. j3 P7 Q& y0 N6 F8 X Y set-plot-y-range 0 num-people% U" E% ~2 t3 E& _
set-current-plot "Class Histogram"
- I# D% `3 g, j0 j" Q set-plot-y-range 0 num-people
7 v6 s4 G7 Z Z' \end9 K% h2 k* u y( e/ x/ Y
6 B Q# F; _1 x2 s9 J% I% Fto update-plots7 _0 L& w3 H" u3 g7 T
update-class-plot
% ^+ g+ d. d+ b0 Q% n update-class-histogram
; f" s2 K$ h4 J1 A! s update-lorenz-and-gini-plots
$ W, y5 i% O$ k. ?+ p% @end# J" i6 @- y% E/ \. T
, Z. y$ x; d3 T3 Y) b1 [. bto update-class-plot
. O9 j8 b" M( v2 D& s) v: U set-current-plot "Class Plot"# o0 v. ?) Z: w5 I# ]2 u0 X
set-current-plot-pen "low"
' _" m( l* D3 y3 s- Z plot count turtles with [color = red]' H$ l+ y( _) M' M
set-current-plot-pen "mid") [# J8 ^. N$ `# \
plot count turtles with [color = yellow]( c; S6 f' J+ E6 u
set-current-plot-pen "up"5 {2 d) }& u$ v- M/ A1 u
plot count turtles with [color = green]1 I2 l e3 j$ u$ m$ Q! z; ] M
end+ O6 v1 u, t( _& Z. A: a6 L& E: m
6 t. j( _2 w# L; _
to update-class-histogram
( F4 ?5 D7 R- h1 I# s4 C6 X( O set-current-plot "Class Histogram"7 [: d6 C. E9 |1 J) U* v j5 y
plot-pen-reset; ]- }. u7 T: D7 D( X. t$ J* Z
set-plot-pen-color red
/ \2 A, K2 a& f- s7 D plot count turtles with [color = red]& r' @: W* M" F/ T
set-plot-pen-color yellow% |+ _! z# `* L' O" c* X
plot count turtles with [color = yellow]' l3 O, x8 n- u2 r9 ]7 V. S
set-plot-pen-color green V/ ]* l& J6 `/ W. l* c
plot count turtles with [color = green]
. b8 ]0 l3 ]8 B* h. }9 i- Kend
7 u5 g/ J3 C4 W1 }! E5 J8 Qto update-lorenz-and-gini-plots
! y/ l/ a/ Y( I) A% I set-current-plot "Lorenz Curve"
- Q8 A& N: S. _ clear-plot0 A; X3 }1 L5 e5 k, b) S
4 A$ e D# \6 M$ m: Q% ^ set-current-plot-pen "equal"
9 U; f+ P+ f' l- X; g, M plot 09 t/ d9 o1 g2 F) d! F4 y
plot 100
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set-current-plot-pen "lorenz"
" x+ @9 g/ x/ D$ J& f9 m3 Q I set-plot-pen-interval 100 / num-people# ?" O9 {+ h" L$ m0 C* u
plot 0' c# i" l9 Y8 W- [' m! \
1 e# z# Q& q+ u( q3 j let sorted-wealths sort [wealth] of turtles$ ~6 a7 d1 o+ L2 `4 s
let total-wealth sum sorted-wealths
4 l4 n+ L. ^" T! k let wealth-sum-so-far 0/ \2 j) ]8 L1 ^, L& Z, d; w, T3 {0 X
let index 0. C. q2 i( A$ h( w& r! V
let gini-index-reserve 0" j3 | Z4 r8 K, }4 d' Z5 a
9 j/ l5 ?$ I0 R/ D. i
repeat num-people [
6 z2 i2 t% Y [) x6 {4 j set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
/ |5 W3 G& i* `4 O plot (wealth-sum-so-far / total-wealth) * 100
( l( G( i- G; n4 y( ? set index (index + 1)! }3 L. e! p6 a1 y+ S# m
set gini-index-reserve
) V9 i+ T' Z. G- M0 p5 I# u8 e gini-index-reserve +
0 d, ^# c: U) Z# I (index / num-people) -
3 h% n# M) ^* R) E* I (wealth-sum-so-far / total-wealth)
8 b8 b/ y) F; X ]
7 ` r( z3 ^( X' @
: M- g/ R" N3 }4 ?! G set-current-plot "Gini-Index v. Time"
1 {' N4 a; F# H- p, n+ n plot (gini-index-reserve / num-people) / area-of-equality-triangle3 w5 y" l2 e6 V6 ~; }: q9 D
end
$ h$ Q# R+ r! V6 ^$ s2 ?+ P7 yto-report area-of-equality-triangle
3 |+ G1 k, v% D) b0 v* e report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
7 e+ W* t/ ?. Y+ t' Tend |