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4 |3 d. F: g1 ^# R5 f
globals
. W) U/ w9 L" H( H; L9 @ ~[
, S! i' F, D# b1 m& s# Q max-grain 3 |; C5 _& e/ J: s7 L4 f
+ A3 \4 g+ `: |3 _" F- B/ H- H% C/ p
]) ~* f4 j5 ~3 U; a0 G: g
, ~) o! {' K7 Y2 l v1 V: F( G5 Y
patches-own2 c- y# Q# e- ?6 B0 k! e
[
% e7 d& ]9 z+ Z+ m$ d# x1 B% [4 L grain-here 0 \( F( I; ~9 X X7 \
max-grain-here
/ A) U8 n. u' \# v: ^8 s2 c2 T' z]
( ?/ g2 e( b O' X& I) _0 x/ E' Y7 H' R4 f. ?: x
turtles-own
) `* A$ C. I# P[% v6 |" q" N+ N
age - h1 F% H* y' u7 H
wealth
2 a! L0 Y1 @1 r, J7 M& K" Z& M life-expectancy
+ f, A( N6 I% s+ ~% a metabolism 9 D Q h# n* |2 a0 X0 n m6 S
vision
; @4 u! A" I& r/ I+ I inherited
$ @% j( E8 V5 b/ G) y; O+ v) c# f]
' o+ |* C% s2 }0 j$ V: t F' h4 C
! T3 Z) _; u2 d) i
to setup
! S; J3 d# v( y6 U; ]0 a ca- K. h/ p% _& c$ R" |: Y
set max-grain 50; N+ N8 _/ C! o
setup-patches
( \' W# _( O D setup-turtles. b- I5 `: X" t* f- R
setup-plots
. ~2 }' b0 Q5 T8 W/ d) j update-plots% L( i% u* ~7 ^0 q6 X' E
end
9 [, J* q4 p; a* h' o# Yto setup-patches
, l" S" P! G& Q$ @/ I ask patches
; s) L$ x3 B2 B" Z0 a; N [ set max-grain-here 0
3 O6 V9 [* q2 Z+ k if (random-float 100.0) <= percent-best-land$ D# l, u4 q# ?; S, n5 b' O6 A* T2 X
[ set max-grain-here max-grain
% e; j& j, n: o. ~1 J3 t set grain-here max-grain-here ] ]; c! z5 S5 X7 L0 A2 K
repeat 5
: m5 D& a* q+ | c( f; [ [ ask patches with [max-grain-here != 0]
0 b$ y. }. u8 p3 }5 W* j9 Z [ set grain-here max-grain-here ]2 j- B( {9 e0 M: u: f" E2 b, X7 w
diffuse grain-here 0.5 ]( j2 ~2 U3 u2 K8 c7 Y2 C: `
repeat 10
; C; n, V: c) S# g [ diffuse grain-here 0.5]
) T7 v8 E5 E, i; a( U7 M) b ask patches" m3 B' F1 `- o3 t
[ set grain-here floor grain-here
( I: A# v( b% {! q/ K6 f set max-grain-here grain-here 4 r% v0 T. o8 o
recolor-patch ]
# P4 D( F4 E' k% Z# f+ Mend
9 u/ m! J6 T7 a( Z0 nto recolor-patch
( T8 V1 J$ p4 N% ^ set pcolor scale-color sky grain-here 0 max-grain
) ~- o: j# _$ |: Vend
8 e# ^& h$ q; S# J; v% n; B# Dto setup-turtles
* y ]+ d* E8 G. e! K set-default-shape turtles "person"8 @& O+ t3 ^% Z* O, g- B0 }
crt num-people; \( M+ d" d( _
[ move-to one-of patches * z* s2 n7 ~* m2 h% B
set size 1.5 7 i* C/ L; l+ M
set-initial-turtle-vars-age1 P7 D/ l3 q: h
set-initial-turtle-vars-wealth
3 h# {: O- ]' N. N' c& | set age random life-expectancy ]
4 }- q1 x4 b4 w6 x recolor-turtles
8 v3 e* x6 u- V9 D: m- Bend
" G' j) K$ V1 q0 Y+ P- m$ |9 ?7 O h* M. ]
to set-initial-turtle-vars-age
3 E& e$ d+ i. Q, @! `% ~9 @ let max-wealth max [wealth] of turtles
2 f4 k8 Q( K0 j! j8 h! b
. \8 o2 o+ ]8 w9 C7 O: n5 v ifelse (wealth <= max-wealth / 3). {7 s/ K+ m, F" v+ J; V: _
[ set color red ! G& G( {& [ a* i% N1 [
set age 0% u- g" C* h5 E
face one-of neighbors4
, \+ D! f8 T1 o9 v$ T set life-expectancy life-expectancy-min +
8 F( ~, v _# F" R: D random life-expectancy-max - z3 p# s% T+ _8 W, R! @6 h3 U* O
set metabolism random 1 + metabolism-low/ t& I/ Z0 o! M# s( `* U
set wealth metabolism + random 30+ a4 b, U4 X9 v% ~: i
set vision 1 + random max-vision& \' a9 P8 K% r f
set wealth wealth + Wealth-inherited-low ]
) c; j. i2 A8 O9 m5 b2 c [ ifelse (wealth <= (max-wealth * 2 / 3))
% y G2 x3 [; `( }: h [ set color yellow % X3 ~$ ~% Q& N* b- O
set age 0. e* h& `% u( U( [3 [+ z, I d6 K
face one-of neighbors4 & m) @! R8 N# W0 f
set life-expectancy life-expectancy-min +* T, D! _2 L. ^2 _( N; f0 Q
random life-expectancy-max + 1
9 ]8 ^3 g0 Y6 [9 }( y* n3 i set metabolism 1 + random metabolism-mid
7 K/ L3 k6 s8 I% T1 A( K% X1 i set wealth metabolism + random 305 P( ?# n F3 P; h+ K4 ]+ p0 s
set vision 3 + random max-vision
- M' n' j9 s: ?2 C. y- r set wealth wealth + Wealth-inherited-mid]* j% z) r: G/ B2 g$ C: |2 J2 b2 ~
[ set color green
) }: p% r/ x! `% C; N set age 0
0 g' k6 Z% j6 s* \8 ~ face one-of neighbors4
5 E k$ d) M+ A+ z1 `$ d$ d \; A set life-expectancy life-expectancy-min +
) `+ d# m1 C; e+ y8 U- Q* e& o random life-expectancy-max + 2
. k9 V4 a" A1 @8 K, A' |( n2 T8 [ set metabolism 2 + random metabolism-up" d+ H3 {3 m i- E- ?9 e" s
set wealth metabolism + random 30
% `8 q9 P( F1 [: z: u6 d- Z$ B set vision 3 + random max-vision
; q* }+ C3 f, `/ K& z I, S set wealth wealth + Wealth-inherited-up ] ] . q/ G: e7 j4 i! G. b8 ^% k$ r
2 Y7 \, i4 ^# Q& c: d
end
5 [$ g+ N1 ~& A2 [, Z9 r( sto set-initial-turtle-vars-wealth
2 r5 n2 w, ^' ]* s* c; B let max-wealth max [wealth] of turtles' P0 v$ U1 w( v: {5 M# u
set age 0" Q) \; Q `0 y" S0 o, ]! @; F
face one-of neighbors4 3 I) P+ I! S' K1 m' e; Z
set life-expectancy life-expectancy-min +
8 U/ g- \: `) Y8 U( f random life-expectancy-max
2 E) z& {7 W& o1 \' c9 z set metabolism 1 + random metabolism-up2 @! a/ `& X0 w& \- l
set wealth metabolism + random 30
% d$ _8 {3 K6 d$ L. j) h1 ` set vision 1 + random max-vision
* V0 t( j9 |$ R7 `: Oend
! o& W/ T1 k+ h( ^to redistribution1 S( \- S8 n: J+ }: D4 T0 T8 x8 {3 ^
let max-wealth max [wealth] of turtles
! v' E' x+ ~/ xlet min-wealth min [wealth] of turtles
( T2 b2 I4 \' Iif (wealth <= max-wealth / 3)
1 b# b) L, X ?" a# @" q; P [set wealth wealth + Low-income-protection ]
. p* | A; S( send7 t4 z' e8 z3 V2 I
) V% Y m, D! \
to recolor-turtles
7 {8 K6 ^ c$ i0 F6 E& E let max-wealth max [wealth] of turtles: R: Q+ @# w5 ]$ d0 t/ b$ ~. ^
ask turtles- k- r4 G4 _6 G% W# f0 t
[ ifelse (wealth <= max-wealth / 3)
( I3 I) ?& g/ }/ u) Q3 g [ set color red ]
4 ^+ [* e9 P1 g* X: V. E% ^/ q6 M [ ifelse (wealth <= (max-wealth * 2 / 3))' W5 _# V+ W. f; h! L
[ set color yellow ]+ C+ n; ]- I! {% X
[ set color green ] ] ]
* s9 q& H, m; Y ask turtles [ifelse show-wealth?9 J u: _- F4 r% D6 i* c
[ set label wealth ]
4 v* N+ W: g0 O) y [ set label "" ]]
9 ?; ~9 P# r) jend$ k7 U' u. f9 b4 U# u; }/ C
! s9 a& o' q) u5 |) @ |, n. }to go
" n- Q$ o5 a8 h8 R ask turtles( W$ O$ U) J `; |6 O
[ turn-towards-grain ] 3 z) @+ E0 k+ s* Y! `! ~
harvest
# t$ C' C# D0 Y$ T ask turtles
8 J; q# N* [* C. p4 ]8 {. W4 ~9 u [ move-eat-age-die ]
& C8 ]5 G2 n5 h( l recolor-turtles6 {+ t' i$ b- W! Y u8 |% {
if ticks mod grain-growth-interval = 08 ?/ P$ C, a: t- ~: R
[ ask patches [ grow-grain ] ]
' x" n1 A5 ^' o2 G: p 4 v0 t/ {0 I$ H+ e- w
if ticks mod 11 = 0) K9 X& d V& q2 [" |4 E* o' a
[ask turtles* x1 \0 t1 i2 t9 C' ?
[ redistribution ]]: Y, q% K( l/ k, U
if ticks mod 5 = 0
E) h, O, U5 D [ask turtles& o- O2 o, z! @8 x" [9 ^4 s
[ visions ]]
& `) F5 o$ T: b* L9 D# f tick
+ O$ F" x g \5 A8 D update-plots& H2 w2 d0 l' ^( o. e1 o& ?
end
: Q& ~$ K! ]8 ato visions+ e4 P$ H6 n$ c7 V& v6 ]& C' J& b" o5 {
set vision vision + 1
3 R/ W: } v: t* E1 \9 ^" Gend
$ ]8 ^4 p% m+ c' H/ H+ P8 z0 e4 h( b& c) m6 Z0 ~ f
4 ]' o& d; S/ I4 v2 L. J1 B7 V1 ?. x) s: s) ~$ P* K; O
to turn-towards-grain
0 t; I2 T+ D- |. j9 J* Z5 j4 r& Y set heading 0& | T% y; p, D
let best-direction 0' y% @* i3 m3 l( S( c7 |! P) {" U
let best-amount grain-ahead) V9 f1 s% ~7 Y K/ R& i
set heading 90
* g, S" \: R. F, y9 b if (grain-ahead > best-amount)4 z E1 S0 c! r: [% x' b" Q/ @/ ]
[ set best-direction 90: T1 K+ ?" R( h
set best-amount grain-ahead ]
( v7 {( R9 [4 K2 v! p set heading 180 [ D; I/ \& ^3 P
if (grain-ahead > best-amount)
) k; B, w2 t; V3 ]- g; @4 a6 g [ set best-direction 180- _5 g) J1 W1 D3 d( N( o% U7 N' i4 y
set best-amount grain-ahead ]
2 b2 I2 b# [. a7 P0 U$ U0 O set heading 270
5 x& v _8 w: s4 p0 T) t if (grain-ahead > best-amount)3 D: |5 g' \ n' Y+ S0 g0 J/ ]0 P
[ set best-direction 270
4 N- x/ V: z2 a7 ?+ } set best-amount grain-ahead ]
" u; ]3 t$ t! |/ t$ N set heading best-direction- R- U. l) I% Z" V# q
end3 m- S+ Q1 l6 e0 V* b' K8 z
. j# _/ N4 y9 `
6 w. \4 k. G6 n+ Q/ E' Bto-report grain-ahead
- _5 Z' J1 `5 U; @, s: T let total 0
: }) {1 x D( U9 o ` let how-far 1
5 I+ Z; t7 h' R1 Q& N0 N repeat vision
( t7 T7 D( v5 v2 Z8 d [ set total total + [grain-here] of patch-ahead how-far
9 t. A2 r4 [( \* ] set how-far how-far + 1 ]5 j" j8 k @' ~6 u$ @0 u+ l5 w# t4 s
report total Q8 Y( \ \; u" H
end: z. P" O; g) y. Z) F4 V" A; u
( @: o: C# S! ?) l5 S3 t x tto grow-grain / i" _1 m' }0 K: I, c' q
if (grain-here < max-grain-here)
3 V1 p% c Z. m: Q& R7 f g1 I [ set grain-here grain-here + num-grain-grown
- }1 W2 l$ p7 f; o7 T if (grain-here > max-grain-here) 8 s# v' K) w# X' f
[ set grain-here max-grain-here ]
: a) \' q5 V- o3 e recolor-patch ]
( u( f. S& a" t* eend
; X) y0 X5 X5 F5 L$ {4 ato harvest
1 Y1 k. _: V' {8 ^% d X& R5 i9 z ask turtles& n( m( a" v6 F" _0 E* s/ v
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]5 L+ k' o( `# x: Q6 U
ask turtles
+ n1 n5 Z+ C6 s4 E( ]1 C [ set grain-here 0
- \# f$ O; _4 l9 j- _8 p# T/ N7 c recolor-patch ]9 a; S; d* K" o+ m4 j+ D& _
! C" `/ R6 S$ |) v& G; aend
1 e5 U& ]& t4 K. G; D2 L% d, E( I1 G
- e, J1 ]1 e6 U; l5 C. J4 \0 jto move-eat-age-die 5 V/ n- Q* [; f9 f0 Z/ m5 b, a
fd 1( ?7 A. N( a2 m$ N' K1 D
set wealth (wealth - metabolism)
7 J" ^% \2 ]5 g' I3 x; s9 r6 { set age (age + 1)
0 U0 ]& k. ?* ^& a5 T if (age >= life-expectancy)
' ]4 k' Y1 E( u; b& N; N+ o' S% l [ set-initial-turtle-vars-age ]
* W% H8 q1 G4 s0 Z7 {3 Q- t% O if (wealth < 0)
) o6 i/ ?; t3 x [ set-initial-turtle-vars-wealth ]. C$ |) @ z# s( i! H) j
5 V8 z: R- Q3 Mend0 R! W0 l3 e0 p" l s& e* ]9 Y
, \- k7 F# k( c/ j
# u; m: L" m5 w! W4 N" Ito setup-plots
% j x8 [; q: F8 E- r set-current-plot "Class Plot"
1 b, H5 D% q. {$ V8 E7 x) U set-plot-y-range 0 num-people& w2 h/ f: p8 x2 R# M4 j0 |
set-current-plot "Class Histogram"" `, k8 b" \ r/ b% n
set-plot-y-range 0 num-people$ X* N- n2 C" Z* |& F
end( L; q% ^7 E" E9 K6 W; G. {4 L% t
; f! ]/ Z( {7 A: [1 f5 _ y
to update-plots; r! t6 X" |7 ?# B
update-class-plot$ d K& h, {1 n5 X% l6 T: |
update-class-histogram9 ?' d5 q1 s; [, I# W& A' Z6 N
update-lorenz-and-gini-plots
6 ]& Z/ Y5 I# Dend
5 I# M$ O1 D. P) c4 V; y1 q O0 ^- q- i& c* T3 c5 S, G
to update-class-plot
9 U. H$ E7 F- e0 D; | set-current-plot "Class Plot"% C H$ ^6 p% e/ B6 q4 l% K2 f
set-current-plot-pen "low"
% p( G. T4 v V$ B2 v) q plot count turtles with [color = red]. [% T0 K8 M$ v
set-current-plot-pen "mid"* Y1 c/ }/ O0 x* E4 w' ^
plot count turtles with [color = yellow]' L* j b5 Q' H, k4 z# B
set-current-plot-pen "up"
4 b/ w. l# M/ B$ {/ _ plot count turtles with [color = green]0 i8 g3 e. g1 K" q3 x2 W" ^
end
$ g$ z% U5 l( v7 q7 [. G: R
- o |# @& `9 r2 M( k' o2 jto update-class-histogram
b4 k$ S# H: k9 u7 @1 u set-current-plot "Class Histogram"
) _- x) X! e2 k; {- r: V plot-pen-reset
3 g4 y+ T' ?1 g. X9 f set-plot-pen-color red
! Q5 `( o( Y* v3 ?/ O3 { plot count turtles with [color = red]
/ ?( G' [! A7 G; k5 G% n set-plot-pen-color yellow
, _: {0 t0 _5 _3 ~! S/ S; b! c- F plot count turtles with [color = yellow]
- A- v. Y3 a p4 ]. j% e" S set-plot-pen-color green0 K4 t1 Z% {7 I/ [
plot count turtles with [color = green]
/ |8 {& H" e2 s& Mend
. w( ^3 {7 j8 a k( f) `to update-lorenz-and-gini-plots
; P; s& F* u! G i set-current-plot "Lorenz Curve"
0 g$ g. p% x2 @6 E1 C7 S. V clear-plot
; @% l4 M6 c* c' g; r# F1 c
, q6 p1 }2 w! B' O4 U set-current-plot-pen "equal"# q! R/ i; T( l2 Z, O' V( `* O
plot 0
* e: ]% n+ v8 P/ M `# y0 b4 C; v: q plot 100
; D0 J! z8 S4 a1 B P
. [, u0 D+ d; d- s set-current-plot-pen "lorenz"+ t& u4 Q. I u5 V' j) a
set-plot-pen-interval 100 / num-people) {3 X+ q4 e( I( F D7 F
plot 0# w M* a" K' Q* u8 Y; j' U
& h: e: ~5 B# U( s6 n( ~# h
let sorted-wealths sort [wealth] of turtles
- W v7 k( m: x" O let total-wealth sum sorted-wealths* B& d$ G& L/ h# @) |& H
let wealth-sum-so-far 0
\3 a: U) H/ X: w let index 0& x5 e* \, R% |; G3 |
let gini-index-reserve 0
7 X5 O3 h( w+ x7 h9 q
$ |* L1 X2 }& @2 Y5 ^1 c repeat num-people [
% \! S6 Z0 [: b$ L; v: s, |7 c9 H# j set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
% ^/ }1 [" O/ e7 b. n# N plot (wealth-sum-so-far / total-wealth) * 1008 T3 c7 ~ W9 K2 I2 j! ^
set index (index + 1)
3 V; K0 i& G! [7 J set gini-index-reserve
8 ~" H8 I! h8 m gini-index-reserve +0 _& W7 K4 a8 Z
(index / num-people) -
% [6 g) \: t; |- [ (wealth-sum-so-far / total-wealth)
9 m P9 k* h5 L) h) G- P! S ]6 G. g8 e# {- c% D- w1 s8 A& f
- G2 X, [1 _: A- L
set-current-plot "Gini-Index v. Time"
0 C) M9 o+ f* k plot (gini-index-reserve / num-people) / area-of-equality-triangle- k% T& w# u# T7 o Y$ o& S
end
* T* v* Z1 C( J% E# U9 L* D2 o% G% z( Yto-report area-of-equality-triangle
( ?/ C$ X. Z1 G; G* g. Q report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
9 d$ W1 m L, ~$ d5 Y" Gend |