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, u& q8 }4 v; U2 i: A* O( Y5 U
globals" t7 s! @/ [% _# J! J5 D
[
' f+ ]) a/ @6 e" n. M8 T max-grain
3 V/ k6 i* l9 d$ d' ]+ c9 x x" z8 {" p6 r4 H; X/ d2 U
]) a" o; i/ e: s
4 B2 ?/ R: L; Y6 Z; T9 @patches-own A+ x$ ?5 u2 W" U m \& G: O
[) E2 W3 O: I4 _) T8 G+ A \2 _& ]
grain-here
. e' p, W1 E# J' q' ` max-grain-here
; k9 [9 ]( O) b]
1 w: }$ Z5 ]$ J6 f5 H1 G; X( o# o3 E V6 C; W: z, u! l% e; Y
turtles-own
( B2 A; G# S( r- r; S[ d) `3 T; `# }+ \! ^1 S0 l
age
& y3 n7 m7 L0 c wealth
4 W4 H1 J* q# I$ {. e life-expectancy # y/ y9 _9 B2 a) B
metabolism 0 q/ m* Q$ o; {7 y* j
vision% B Y f# b3 ?' }: B
inherited
6 w; [5 ~2 P2 V]) c! s, C/ j6 v |. K
1 d0 X# g0 g. `( t- r
9 {8 ?1 g; Q5 ]: xto setup% b5 F( z+ I4 S
ca
! B3 l5 c9 g; h; p% R# S" N8 C! G! s set max-grain 50- U' R% k" |/ V: f* I8 ^/ T
setup-patches
, Y) q, o) ~& _ setup-turtles
4 f. T& v6 }8 o3 F5 m! w setup-plots
% i `5 w9 r. Q$ g update-plots+ \ u& f+ z( G# ?. x3 z
end! O9 ~% H3 T$ }2 x4 \, M
to setup-patches
4 L0 ?1 I0 q1 y8 s2 w ask patches
! ?9 u" F8 R5 r. P9 n' f+ d1 P [ set max-grain-here 0+ P; H# s3 i% n
if (random-float 100.0) <= percent-best-land' B; l, k$ [' b- E _5 }, M
[ set max-grain-here max-grain
' J* B! _$ {# z# \+ g: U set grain-here max-grain-here ] ]
1 [0 v+ V0 A! ?& R/ b# l6 R/ `# Z5 f repeat 57 B$ N t3 q; S5 q$ T+ ?5 f
[ ask patches with [max-grain-here != 0]) S/ j1 Z$ x6 S1 e) W
[ set grain-here max-grain-here ]6 j/ W. N7 ~: v( A3 Q
diffuse grain-here 0.5 ]
# x) I* z$ N, z) U8 b; p8 ^1 E repeat 10- V- Y. r3 h n" ] K1 d2 l8 @
[ diffuse grain-here 0.5]
/ O m8 M f% H* g& b* S ask patches: Z, u) d, W$ ~8 d! v8 [0 w& w
[ set grain-here floor grain-here
* s" a Y m8 ^- O! M set max-grain-here grain-here
2 V/ @5 W9 {' x9 b$ T recolor-patch ]6 j, x1 c/ b: ~( g& q4 R: z$ B7 h
end7 h4 e( D! p2 O6 h. g- S5 f0 U
to recolor-patch
. x* s8 a' f9 U- H( | set pcolor scale-color sky grain-here 0 max-grain, D2 H$ { j6 Y2 p- X5 }3 F( U$ c
end
: k4 M* ?! Y6 i! x9 m. R1 H" gto setup-turtles
) ~' \9 p( I3 C: N2 N( F8 B set-default-shape turtles "person"
* F% f; o( k, |! L$ E$ [ crt num-people7 f/ W6 O. e: e9 ?1 I
[ move-to one-of patches ( x6 O+ ~* r6 e% `: J/ c. d; K
set size 1.5
$ s' b) Z" D; [0 _: g set-initial-turtle-vars-age
8 v" C5 n: {# W3 E; U0 N set-initial-turtle-vars-wealth
, {) S( _6 x) w8 V9 H set age random life-expectancy ]& @5 j0 |* O+ _9 N8 Y G! J
recolor-turtles
0 r D# C8 {4 l7 ^3 kend4 D5 P* v ^2 Q0 S
) C* g; p4 j3 M: y
to set-initial-turtle-vars-age% B9 [; S& k I% F6 B
let max-wealth max [wealth] of turtles m& U& K1 _' R4 f) P4 c+ a
^* [) y* C( n; Y% w: J
ifelse (wealth <= max-wealth / 3), |# N- g* N/ r' J' j1 | i
[ set color red 8 b. T' ]. x; f, s3 } ?0 r
set age 07 }: z# H* k& o, A$ r! t/ |) T' C
face one-of neighbors4 1 U4 C8 s7 F2 b& b0 a1 @9 n! M: m
set life-expectancy life-expectancy-min +/ l( c- U+ B T- `$ ^( I9 }+ N
random life-expectancy-max 3 _" A% V/ w* ] {; X
set metabolism random 1 + metabolism-low
9 r" Q6 |" Z. y1 z5 M set wealth metabolism + random 306 k/ M0 z1 H1 P+ n1 l) Q/ ~
set vision 1 + random max-vision
( _# C- S; Z& o# g/ q$ i% ?: T set wealth wealth + Wealth-inherited-low ]9 s+ Y( O% H- l3 b c1 w5 \
[ ifelse (wealth <= (max-wealth * 2 / 3))
9 }+ f% j. v9 ^4 u [ set color yellow $ b3 v/ c4 T0 o. Y, m% o" K
set age 0& k; P' Q! b, r& x& q
face one-of neighbors4
; ]3 i8 k: l: e set life-expectancy life-expectancy-min +$ E5 T1 M/ N; w2 A2 u6 A+ ~
random life-expectancy-max + 1. X! u0 H2 P. }5 z# s
set metabolism 1 + random metabolism-mid7 P# @$ E) [/ t
set wealth metabolism + random 30
; s6 }4 g) I; o3 s set vision 3 + random max-vision6 b3 {0 `$ p/ [+ ]* o+ w6 ^
set wealth wealth + Wealth-inherited-mid]
( C ], H- X/ W& f8 q [ set color green + A+ a5 f- Y: n) S) J* ]8 h4 W2 R
set age 0
/ ?+ F$ p$ [& B# B& i8 z5 Q face one-of neighbors4 2 k, l. Y! w" n) [1 |7 V
set life-expectancy life-expectancy-min +5 ^! d8 H/ v8 c9 K' l
random life-expectancy-max + 2
& w" Z+ {9 J$ \ set metabolism 2 + random metabolism-up; e5 H) N M8 c5 Y
set wealth metabolism + random 30 y9 `- k6 v y( T5 x7 U! q, t/ V
set vision 3 + random max-vision7 H" h, t$ E2 \- Z7 @* ^& Q* ]1 a
set wealth wealth + Wealth-inherited-up ] ]
+ ~0 S1 M: u- z" H/ {
' E* I8 w: w6 }4 ?, _4 ?end
" F+ _2 _$ N: z3 \to set-initial-turtle-vars-wealth. y/ z# I7 ^; W( \ N5 J, X- ~$ r
let max-wealth max [wealth] of turtles
3 g' v" R; u" F set age 0; x, P' ~4 S- J) I
face one-of neighbors4 , \5 q: f) P- i' J. v+ j$ V) @
set life-expectancy life-expectancy-min +- \. ] `# m: Q
random life-expectancy-max 4 S' X1 O; S1 T$ M& Y
set metabolism 1 + random metabolism-up
1 S! ?" U6 a6 t* r: R: n set wealth metabolism + random 30; O" y7 m# t" S
set vision 1 + random max-vision & o0 Q, B7 b+ ^ \3 `% I8 a
end
5 H* a3 S" L+ {. ?, c% r' {to redistribution$ r2 R3 _* P0 v! i
let max-wealth max [wealth] of turtles
7 \3 v t' k/ U2 K7 j/ c& alet min-wealth min [wealth] of turtles: @1 Y4 y9 n. s5 A
if (wealth <= max-wealth / 3)
8 r& b) a; R# n8 t* ^1 I, p [set wealth wealth + Low-income-protection ]
9 O+ q3 v* i! f V0 Z% E3 I1 p2 m. vend
0 K( X" [0 U K! S& j$ n1 E " h, g, D9 N* y E& {
to recolor-turtles
( T# R8 S: i+ F; ~5 X let max-wealth max [wealth] of turtles% V; ], a0 L, D# G) e
ask turtles/ Z: `% [6 [4 l( C4 b" U) U( ? z
[ ifelse (wealth <= max-wealth / 3)
5 w2 z N- N8 N A5 f+ ?0 p- ` [ set color red ]
9 O. L9 U. ]$ o7 V7 Z [ ifelse (wealth <= (max-wealth * 2 / 3)): A2 b! y5 m" _5 ` \% ?! G
[ set color yellow ]
4 D5 ~% a1 f8 T5 k [ set color green ] ] ]% p. X% e3 V3 }+ f j
ask turtles [ifelse show-wealth?
% e8 z, k/ y9 J( ]% s [ set label wealth ]) s# P/ ]5 v/ ~8 I6 G5 ~- T7 n- m
[ set label "" ]]
. U0 `$ \* @: _3 A, m3 Z6 Eend
8 X# H! W8 W6 c& q ?
: U1 Q: f- o4 Y8 `5 Ito go
2 b! ~0 h d2 i: o5 N) z ask turtles
; ~$ t, z) N6 i. V [ turn-towards-grain ]
! T; V) x7 [7 i( S+ J/ c harvest' z1 G) P- `# Z8 ~) O9 B
ask turtles7 G- ^, C7 [1 ]7 h
[ move-eat-age-die ]
4 l$ h) I( v, {1 J9 L recolor-turtles
8 H9 Q) P% p4 \+ b, S* {2 |2 w if ticks mod grain-growth-interval = 0
. U& S" Q2 b# B) o [ ask patches [ grow-grain ] ]( D" M% F% a% R6 }' `8 b
- w& I* Z; K' d' R+ ~
if ticks mod 11 = 0! L/ G9 A# x, e, B3 y
[ask turtles* m" G9 S6 T3 Z4 E# Z# Z& n g
[ redistribution ]]
, X- l& x0 I. f2 }7 ~; i+ @ if ticks mod 5 = 0- `% e& O! B4 p1 k
[ask turtles% g" z7 v) I H/ v9 K, u; Z
[ visions ]]
0 d1 @% [0 j0 g# ~- v: t" e tick7 P" u8 |& j7 r% L1 C$ j
update-plots
2 q1 T/ Y, Z' dend
! G# D5 y2 x" M9 W5 Z2 _" Eto visions
7 e2 t \0 i: R0 J! ]/ N set vision vision + 1
, J% ], {; o5 N* H ?0 x+ I/ zend0 g* p, X- S; R; t
3 t: v1 d* [5 E7 l. q
1 D" \' h {7 s+ C2 Q' |. m( b" T, c, U) [
to turn-towards-grain
( L2 K9 y, N' ?) C. S set heading 0, s2 h1 f; g! q4 m: H! ]# V, q
let best-direction 0
* g; ?* ?# m4 p" z2 W: z let best-amount grain-ahead
6 T- k1 r) t& @! e1 ` set heading 90
4 l4 h/ J3 `' g$ ]1 G if (grain-ahead > best-amount)/ L; e( I8 K5 r/ \
[ set best-direction 90
' j5 i& C& Y K; p+ C set best-amount grain-ahead ]
6 J5 J: Q1 ^/ y! J( v) G% o( E set heading 1802 t6 O+ Y( e* N. |+ h% A5 X q2 g
if (grain-ahead > best-amount)
/ Q/ A( S' L; q3 n3 t [ set best-direction 180& Z/ E9 u3 C. T
set best-amount grain-ahead ]
9 h' a, E% n( g) y8 Q set heading 2704 q: M( V3 d1 ?& g3 T
if (grain-ahead > best-amount)
+ i4 B0 M) n# E/ H3 M [ set best-direction 2704 \. ~3 Y4 n- _# d5 ?/ S9 s
set best-amount grain-ahead ]
2 J8 T# k4 k( a0 P9 _ set heading best-direction
' K' [4 {$ ^, h. t* J- \end5 a; t3 _, e0 K6 u4 o6 D
5 _. R2 h+ J1 |# x
+ ?& e7 X/ J2 k6 Y
to-report grain-ahead % {9 i2 D) X2 z% A
let total 0& q! n7 u; x, g1 H/ ]
let how-far 13 ^# C8 W6 w8 `& b( H( N5 Y
repeat vision
! t% w( m8 U0 G* E! N& Q [ set total total + [grain-here] of patch-ahead how-far
) J! Z- u7 I6 L$ N3 H5 k3 E0 M set how-far how-far + 1 ]
8 [3 @% m7 {! a9 ]& @) T; w6 q2 E report total- U" l" t6 s+ z1 ?7 \$ f
end6 h7 Z3 }% p- C% M- n
. F) l4 |# h+ b( U# ~to grow-grain
' N! s2 X( t& ]& Z# G5 A ?( p if (grain-here < max-grain-here)
! _ U* h7 @- k1 j7 q0 W5 x [ set grain-here grain-here + num-grain-grown! Y. q/ x& e/ `1 M& Q, v
if (grain-here > max-grain-here)
" A" O- b3 C! t. W' k [ set grain-here max-grain-here ]8 J$ @/ `/ p, T5 i( o
recolor-patch ]- U, g, s7 i$ N7 R1 j
end) C0 w+ N) e" |7 h; Q6 m& x- m
to harvest# Q- F2 q' t8 p2 u# \
ask turtles' C7 d! q5 J0 @" O& v
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
/ f1 }3 Y8 w2 M' S$ _2 p4 h5 \7 i ask turtles
; v. S; U1 f9 R7 X1 F5 t. u' g [ set grain-here 0( A k9 f! }1 u; S, Q/ g, L. b
recolor-patch ]- Q. r$ c& M7 T4 O
; g5 G6 I6 W& z3 q' ]* D) Q. a, A+ h
end. P8 P. i. X" b: W' Q
/ C Q5 a" B5 y3 d( N; y% `* @/ ito move-eat-age-die
6 a& i; \+ H% e7 c% R$ E fd 14 J, P5 L3 P$ g0 \" y& \9 x
set wealth (wealth - metabolism)1 J- ~& v4 E! D9 ^+ i3 i7 r
set age (age + 1)
5 p! _% w) \! p M7 x if (age >= life-expectancy), b1 H. O# |. G; k8 M8 I t
[ set-initial-turtle-vars-age ]7 p5 h' D, y ]. I! _" o2 c
if (wealth < 0)
1 w. C% l: t" Q( w [ set-initial-turtle-vars-wealth ]6 A# g( I* }% {: H
- g% l7 z- ]( d4 F; u# Z' {' Zend
* Z5 j, E7 e8 a
- S0 Z7 R& ~8 p+ s
7 i% A7 i) _0 p; Q- _$ ~to setup-plots
% r2 i$ u$ C% E0 v' q( P' B2 { set-current-plot "Class Plot"
; G7 {) ^: D; t7 r set-plot-y-range 0 num-people
( S% W" X S: U/ J: E& j3 p8 b set-current-plot "Class Histogram"
. w& W5 H! i4 d1 C- Q7 t set-plot-y-range 0 num-people
( T5 d% A; z3 e1 @+ j7 J7 Send
, z5 z6 ~+ s [" Z% ?( ^ I! {3 @
9 t1 g8 ?0 |9 s5 V* \0 P3 N$ I7 \to update-plots N2 K. j q' b
update-class-plot
( u/ Q0 [+ @) c2 e) @" J1 t4 K u& q update-class-histogram
& f$ D' U9 R: j update-lorenz-and-gini-plots
& y' ?2 O& Y+ c u: [end/ w Z8 @+ Z, d8 S
8 M% e. x; U) I) R) d$ f/ a8 Gto update-class-plot4 Y3 f6 s/ g: U9 A6 V- \
set-current-plot "Class Plot"
5 u! B) I9 u% m+ b9 x set-current-plot-pen "low"
1 i& }% K* j: \ n2 o. c plot count turtles with [color = red]0 [1 s6 }( O% k+ m5 A
set-current-plot-pen "mid"+ y! O/ D* `% f& i
plot count turtles with [color = yellow] m+ a% v1 C5 Q6 K: ?4 k" w, _
set-current-plot-pen "up"! p; e5 a& z; x# P
plot count turtles with [color = green]
% o$ h4 { o! i* k r) v) L c5 A0 `end
& a% B8 ? N: u+ p1 k3 D# B; W
to update-class-histogram- ^: m% ^" q& U: A
set-current-plot "Class Histogram"# l/ `6 d+ S1 k0 v0 `& }9 ~5 @1 N
plot-pen-reset
0 O& j$ g& c( F# J0 ^ set-plot-pen-color red: y# U& U) l+ s, l. X9 C! t4 ?
plot count turtles with [color = red]
8 a% l9 P" D! b8 u: R set-plot-pen-color yellow" M/ x. p; E4 B9 G, V
plot count turtles with [color = yellow]" \! f+ R; r( f. d( _4 y, `
set-plot-pen-color green
0 f+ ]+ p! F& s( F, j: j plot count turtles with [color = green]# K! c# Y$ J( p: Q: s; Q
end
! z$ {# y$ i/ r+ n( J4 o: t5 jto update-lorenz-and-gini-plots
$ S7 Q7 t. q8 ^7 f" o* [1 t set-current-plot "Lorenz Curve") A3 b/ T: r3 w0 c- S6 j% g7 ^
clear-plot2 d' t2 q4 J0 d9 M8 j7 x) F
6 c, V9 }1 L- d
set-current-plot-pen "equal": H3 V0 J0 U$ l% f( k/ Y
plot 0
% e5 Y% |4 T1 _4 @ plot 1009 T, R+ u/ W' E* O- K4 A: A
% W, T. t, S F set-current-plot-pen "lorenz"
( D% l1 R- }% X" t5 X set-plot-pen-interval 100 / num-people# k# P G. ?/ r/ e
plot 0
1 l$ @5 _6 s8 U6 p; s
& K1 S" a/ G+ g+ v let sorted-wealths sort [wealth] of turtles6 d" e a7 [. b) k5 l
let total-wealth sum sorted-wealths6 w7 e' U6 X! ~! J
let wealth-sum-so-far 0
" U/ p# ^$ J/ c7 Y) | let index 0
# b& M A% `( ?% \ let gini-index-reserve 0
) _2 a F4 ]" D/ g9 F; j7 X
. [5 n1 ~2 p `6 h* z4 | repeat num-people [4 R( y& B* h4 I% o6 m* ~
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)/ W+ k3 z7 z! a% H/ J6 m. Y# t
plot (wealth-sum-so-far / total-wealth) * 100
4 y- S- a, ^ p% j0 R% ` set index (index + 1)8 X% b5 @# Y! R' v0 w8 I: I; u F
set gini-index-reserve
& Z5 w( I, \" o" l5 A gini-index-reserve +
; M" Z/ L' x8 k5 m9 O2 e (index / num-people) -0 x$ Y9 Y; _& f2 m& f
(wealth-sum-so-far / total-wealth)
1 c$ Y2 A0 R* [6 S k9 E, ] ]
) ?; _, D* j9 a; h6 f6 f* R" W% r1 S' s8 l2 H( i" l2 H
set-current-plot "Gini-Index v. Time"# q. c+ B6 e+ g, J; A
plot (gini-index-reserve / num-people) / area-of-equality-triangle
5 f: f; r2 p9 Wend1 g8 _1 R" M: N. ^& e2 \( Z8 _9 @+ Z
to-report area-of-equality-triangle
4 n* w8 f" \3 L0 D- a/ ~* L report (num-people * (num-people - 1) / 2) / (num-people ^ 2)8 I" l& k! Z8 x( s) ]
end |