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 ~" q( f" K, E( z% p5 e. Lglobals& S% w" I- t9 [3 P3 r0 n5 Q
[
5 q/ y, N' s9 Y z& ^+ C max-grain
! T* t( Y/ \, Z2 W. B, _1 {
" u1 D0 y G- y8 ?2 p. n], v$ }2 G5 @( j( W0 \" L7 t6 j
0 J l) y+ S6 Tpatches-own
$ C- s# j2 M2 o/ u% ?) J[5 m( U: J( H3 Z
grain-here
# S. V5 A9 O. F5 L4 G max-grain-here
?) k6 N8 M0 c A7 w( o7 k+ P/ I]
$ u) }0 X- K5 h# @; f( w' {9 P% m* F4 ?0 v
turtles-own
! q3 U; M& `/ R% X2 X; f* P[
8 ]2 ]+ J/ F5 A4 r- S: Z9 h age
! G( C8 C/ f' X2 V" O wealth
. y' q8 {/ u3 k, s) J7 b6 X life-expectancy
3 G. ? I4 O% O( F* [4 K metabolism
; h; t3 Y0 l5 F4 B vision7 s) B, D( ~: @) @, [; U
inherited
* }$ S5 u, Z2 W' m% l]; _4 |: J* U" H" @
" {& l, Z$ r8 P+ H: W5 p
d( k, T" F, }2 b" }0 T- U: Tto setup
5 Y) u# S5 h% X1 x0 y ca
- P6 y; E1 p! P+ o! B set max-grain 50
* y/ D: |, U, A# w t7 s9 g setup-patches6 G2 T9 g8 u; b ~
setup-turtles9 k& @2 c6 B2 R# E5 k
setup-plots
?2 }7 K- q/ k update-plots
0 r! S6 p+ b# w: X% `6 b- g3 {% O+ Rend& ?' K* p5 X/ k/ q" {
to setup-patches
3 e8 R& t- X, y: N$ N' J: \ ask patches' q* D' }2 e7 H! f3 E6 P
[ set max-grain-here 0- d- Q% k6 g' `& u( f
if (random-float 100.0) <= percent-best-land
3 p4 v. R6 v4 W3 |, p [ set max-grain-here max-grain
4 {) `/ p, N9 p2 e" j5 z set grain-here max-grain-here ] ]8 N: C4 P+ S4 v7 `# I2 ~$ C
repeat 5
5 }' T9 v; T. F [ ask patches with [max-grain-here != 0]
3 W3 L; W& {( E* ]2 L( v* u$ D1 G [ set grain-here max-grain-here ]9 D# M: @" T; n3 O: g1 O. d$ t6 p
diffuse grain-here 0.5 ]
) D& l$ O9 a- x/ [& w/ @ repeat 10
. A2 ?# I" D$ q+ q [ diffuse grain-here 0.5]
- A. Q/ h0 ~9 p- v: q% [, l ask patches6 N3 U! R. H6 o8 W$ c+ _. ~! r
[ set grain-here floor grain-here
- c. N3 a& [! ~( t, d set max-grain-here grain-here
8 Q6 w& ]' T; R, e6 z recolor-patch ]' B# U: }% D$ w' U' M& n" M
end
# J1 {3 |% D3 h' C7 b. `' |; gto recolor-patch o- l8 ~& s# h! Q& [6 M4 D
set pcolor scale-color sky grain-here 0 max-grain
^ _# ?1 U5 Aend0 g' v+ }* w5 ~3 C/ a
to setup-turtles
& p( N/ z2 F4 {5 B5 D set-default-shape turtles "person"
) v, h; |: U2 |# H2 b3 Q crt num-people6 I; y8 l' Q/ \
[ move-to one-of patches
/ y# i- e$ U* \; u" y1 ?6 @* C set size 1.5 . R5 I9 o* E; |/ k8 C1 B/ |9 @4 @
set-initial-turtle-vars-age
2 [6 I5 X0 l |. E) H& c% | c: h set-initial-turtle-vars-wealth& Z6 B$ o9 o" P+ U# E. U( r
set age random life-expectancy ]
' H( E5 i! L; j% o+ D3 l1 K6 x recolor-turtles
2 q3 E$ N" i4 ]% Z+ pend
( T! b* D3 e5 o" b7 x0 \) L5 i' x. _# R
to set-initial-turtle-vars-age4 X5 j9 I# k2 B( s
let max-wealth max [wealth] of turtles8 f4 @& J4 x$ M
5 v ]. b$ [2 e4 d& y ifelse (wealth <= max-wealth / 3). M: ~8 v$ m; C- m' q, C% X$ ~
[ set color red
# [" ]' x, C# F) @5 ^; g% Y, } set age 0
& C. ~. D: N Z& H# D face one-of neighbors4
( T# q, c: ]8 t! v$ K/ z1 i& c( ]: p set life-expectancy life-expectancy-min +
' v* [5 V( s8 D# m/ y random life-expectancy-max
3 o* x5 B8 i( Q) q" o2 U u! Z set metabolism random 1 + metabolism-low& X+ I; R, G& K! E! R
set wealth metabolism + random 30
( S# R2 f* e( w+ |$ G set vision 1 + random max-vision5 x# }* \7 D: {* C! W
set wealth wealth + Wealth-inherited-low ]
; B" H, W/ L. h5 |7 d! X [ ifelse (wealth <= (max-wealth * 2 / 3))
" |% ]* l( [7 s) t5 N* A" R5 B [ set color yellow
0 i8 j8 ]6 ?1 x* b( Z set age 0$ Z9 }- ?0 f$ J" M% D* d* i& N- \. R
face one-of neighbors4
1 D7 k$ x/ K) K& V. o) k; a. _ set life-expectancy life-expectancy-min +8 [ n" f2 p7 |* ^; C; [
random life-expectancy-max + 1; K: W% |2 J# }( n; W; r
set metabolism 1 + random metabolism-mid6 s! H8 n2 a' [1 N; ]6 s) p
set wealth metabolism + random 30
/ E# F+ @" @9 h4 z9 D0 k set vision 3 + random max-vision
$ t/ r. y% |8 q6 C6 { set wealth wealth + Wealth-inherited-mid]
, T3 r/ ]) {* Q1 @. j [ set color green
( W& s0 t9 ], m3 [8 o# Y8 q set age 0
; T! N5 a6 n1 P; Y: ]% } face one-of neighbors4
! V$ I9 C* N1 } set life-expectancy life-expectancy-min +' r& _; V' W& H
random life-expectancy-max + 2
R( L- X+ _# @& f2 n+ S5 q. X* P. V8 t" E set metabolism 2 + random metabolism-up
- Z2 D: R2 C, _ set wealth metabolism + random 30+ T# F q0 H6 o; u% s% s
set vision 3 + random max-vision3 G! z, l* y& ~ A& V
set wealth wealth + Wealth-inherited-up ] ]
E. l; R6 o. |* k; }( v$ w % U% v& V6 A" \: m/ e. j
end2 B7 a! \ }+ R+ p
to set-initial-turtle-vars-wealth8 n& q: k' \! p1 O6 |# ?
let max-wealth max [wealth] of turtles' J7 d0 T0 s/ X! p+ F6 c+ d
set age 0. }% D& y4 |( z; G. x0 d
face one-of neighbors4 ; Y) @3 [7 B& e, K
set life-expectancy life-expectancy-min +
8 {5 y. d" v# g6 m; k random life-expectancy-max
7 C6 r9 B6 _% i0 a" b% J: S set metabolism 1 + random metabolism-up
5 s5 x. V6 V3 f- n set wealth metabolism + random 30 \, |6 [, i' D- S" D2 S& h
set vision 1 + random max-vision
/ x9 J; c. N' G/ g" m0 @end J& @+ f9 H4 R' Q$ B( T
to redistribution5 ~, A( C% S9 R# p* c- k* ?
let max-wealth max [wealth] of turtles5 V7 Z* ^6 K2 h) Q7 S- G0 D$ a
let min-wealth min [wealth] of turtles
7 Q; e2 l6 g6 e0 l5 @if (wealth <= max-wealth / 3)% ~& V. {! L1 B. L" L+ u
[set wealth wealth + Low-income-protection ]6 O/ \& {1 G; A. j
end
9 T' i9 B& K) d$ X* b' l 1 h1 @ I0 d9 u/ t U" H
to recolor-turtles
- Y3 M E" N" U! |& ]6 [ let max-wealth max [wealth] of turtles
1 Z, w* H* |6 O1 e ask turtles
, f7 a1 G% M# j, d. @ [ ifelse (wealth <= max-wealth / 3)
n( s3 D. k# x5 M) X [ set color red ]
; c: z/ G# N" J( `4 {4 F [ ifelse (wealth <= (max-wealth * 2 / 3))+ Q: f/ ~3 i# C0 _4 g
[ set color yellow ]6 g' n5 X4 F* G# |% y
[ set color green ] ] ]
, d9 N0 J1 T5 ? ask turtles [ifelse show-wealth?
/ W+ I: y- U+ i" M0 s7 f3 {0 m6 e [ set label wealth ]
: v4 u O) _' j3 D# L [ set label "" ]]- Q) H6 W, E2 r# @. l& c
end
( N6 d7 `3 F* h- i/ x
# u0 L* ~. u3 b6 o8 eto go
& t! s# l+ N% N" n ask turtles
% m+ {5 d/ M# v/ z, `; E1 p# \& Y4 Z [ turn-towards-grain ] 4 W7 t5 K# V9 L9 c5 v# o) [5 f- ^/ G. H
harvest
. _) Z* f2 Q& O5 }' e+ F V0 t$ c ask turtles0 A3 W+ j7 y, h
[ move-eat-age-die ]
/ p# b& z! G$ P; _. p( P. N6 ]# r7 ] recolor-turtles
4 G; e+ X( @! [0 g( g7 _, l if ticks mod grain-growth-interval = 0
* P5 s* |2 ?8 u$ K. z$ Q* T" T [ ask patches [ grow-grain ] ]
7 A* u" f: [% m- z1 X & x6 T0 j, c7 y' ~9 o4 u! D2 r
if ticks mod 11 = 0" ?1 M: F0 I% [. I) F
[ask turtles
, L; o* {) B4 M5 e) J [ redistribution ]]
1 Q3 F2 m' i4 a. H, _( e( W F if ticks mod 5 = 0
k; z& v" r. v n: V [ask turtles
# T2 G$ ? {- I& H- c0 q) u$ B5 w [ visions ]]! M! n" K; k2 F; G/ x& n
tick* T' p$ W9 D: n; ~4 \0 F* Z
update-plots
) P' X; L+ n5 S. I4 v7 U) \! i$ xend; H" h. {8 |& H' \
to visions
2 J8 J3 }2 b, f S6 z2 r+ C set vision vision + 1 9 Y5 A+ W( O4 I5 T
end- g2 H/ k/ O( D( d& T! o; l, b
- R4 g5 _/ q% o8 _/ C7 J- U6 b; s
, Q; ^( u; m& _$ x0 k, h
# D* R. ~/ d3 s% Y$ G
to turn-towards-grain - n. I+ t9 h& z; ? w# t% Z
set heading 02 g2 c4 }& v7 |8 X
let best-direction 0 S/ q9 b* ]) p
let best-amount grain-ahead
. u6 y/ s3 u, i/ _7 M% i- m6 } set heading 90
" W3 L+ O% P" S- p7 s if (grain-ahead > best-amount)( n# r% ~; u; h$ }# q! }' [
[ set best-direction 90
8 w- k! v- F3 ]% v0 ?* P! X set best-amount grain-ahead ]# G" r- x5 a* U
set heading 180
7 v d5 f$ J4 v% Z7 _0 ?% w: I if (grain-ahead > best-amount)/ Z) y3 p+ P8 p
[ set best-direction 180
# u2 c8 X3 t5 s1 U set best-amount grain-ahead ]
# J' C% l5 k, E& R set heading 270
4 X3 Z" D0 L2 U8 ^5 P if (grain-ahead > best-amount)
) D6 c& H2 ~ ? [ set best-direction 270
+ t0 P& h* c" @( I set best-amount grain-ahead ]9 m& L" n1 s. y/ g* `
set heading best-direction' P( b8 j+ j f4 J, P5 p0 |
end
, U% @: C. d6 n( b% q3 n2 n$ W3 L9 Y* }0 K9 M, N
) c' M1 ]7 x& Tto-report grain-ahead 7 E" t( o: l% G- \# i" g9 ?5 [- o
let total 0
9 a8 [8 b/ H% i( C8 A; [4 R& R+ p let how-far 1
0 Y1 x8 B+ w0 K repeat vision
& a7 y, n" n7 ^! D [ set total total + [grain-here] of patch-ahead how-far2 N# V0 H& {# Q \) a+ n
set how-far how-far + 1 ]
" T7 v8 s/ t6 d1 J/ t1 ]* i7 O9 a* I report total
8 X, w/ ~: g& l: send [! R. f3 \0 R9 \$ u
1 N" B h) k; w
to grow-grain
. F# b9 D7 c; F if (grain-here < max-grain-here)
' r6 G+ `- ~% s( q! U$ t, \% r [ set grain-here grain-here + num-grain-grown5 T$ m/ b ^$ Z7 w c8 c+ z; f
if (grain-here > max-grain-here) v& _! s/ T7 P& J
[ set grain-here max-grain-here ]: w) h9 f4 S% Y+ K) A
recolor-patch ]
% _3 z" V2 ^- G# {end: ?" D, _" k, c" W
to harvest
: n2 m0 }1 h& Y- { ask turtles S9 Z- v: R0 |8 F2 K$ t# ~
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]/ ^5 I5 ~: o; I. Q& K, L0 U' K
ask turtles
& u9 I" Q# b1 g: A% \ [ set grain-here 09 ?$ N" i- }" N5 p8 e
recolor-patch ]) I. ^% d% R' @$ a" p! h
3 q' Q- \* v# G3 q9 H/ e
end. O( H; l9 `( k$ B
2 x6 `! }# R) m" D" T9 Y
to move-eat-age-die
) D. f: S9 T" Z! J fd 1
; S- u. G2 K: u! m set wealth (wealth - metabolism)1 V5 t K2 j9 Y7 U
set age (age + 1)
5 z" @/ d3 e+ ^/ g6 b if (age >= life-expectancy)
% a/ g e4 `% \% L2 A0 y [ set-initial-turtle-vars-age ]
) t$ [% K/ a/ s+ ?' j( w# Z if (wealth < 0)
( d9 ?/ w. x' M. G Y% M9 O [ set-initial-turtle-vars-wealth ]
. ?5 }! {( C) Q1 D - v8 u8 }7 L7 \, ]3 `, b
end
* u& ]* V) |7 @- g9 ^
; M! A) U: p: z! n6 g
4 n1 W" ]8 w. T3 h$ Y. v% U6 a: gto setup-plots- r1 m$ r6 {8 ^0 S! X
set-current-plot "Class Plot"
* S% T/ _& k5 \2 V) c' [6 G3 l$ Z set-plot-y-range 0 num-people
9 s6 a! b9 o Z& W* U3 h set-current-plot "Class Histogram"
, u/ E7 B. \7 Z; X' h% E) T" S set-plot-y-range 0 num-people& y$ p/ i; O$ n/ Z9 s) B
end
* Z. C$ A8 e0 C+ x# z4 [
5 E/ P: {7 |% Z+ g5 rto update-plots+ M, w& G) x' v6 X$ n
update-class-plot
1 l0 z. i O& d6 A update-class-histogram
; Q" n4 Q5 P: r, f. h9 Z update-lorenz-and-gini-plots
: I) F" e- ^& M. k& E6 Vend
6 d/ `' `% O1 |! N" U# B
& J5 g0 f$ k* ?to update-class-plot
4 o, e% c5 L0 A3 S9 {# o" e" B1 n set-current-plot "Class Plot"1 P) r4 o( a6 k# H5 i
set-current-plot-pen "low"7 N& g. P. `0 w8 S
plot count turtles with [color = red]1 Q( H( A+ }' P6 Q, m+ E! a5 \
set-current-plot-pen "mid"
) c$ U, E7 |% x1 ?) R4 ~8 L plot count turtles with [color = yellow]
' P0 U5 q7 g) n set-current-plot-pen "up"
9 X+ e- ^- X: j# ~2 p6 Q1 L plot count turtles with [color = green]: D. N/ M3 j8 i$ U5 L1 p
end2 K% R3 @- Z4 N+ l2 k& [' K
- g& k0 N5 A2 |( A/ F
to update-class-histogram
" c. Z) j6 ]9 R5 v set-current-plot "Class Histogram"
2 ]( v' c) A% T! y plot-pen-reset$ a5 j: f% s" b9 |- u- F# P
set-plot-pen-color red
" f! x$ s6 o- M/ @7 Q plot count turtles with [color = red]- H- S7 U/ V, A
set-plot-pen-color yellow9 Y. Z; v6 I6 n2 F
plot count turtles with [color = yellow]/ y7 p: G; |7 z4 a1 `
set-plot-pen-color green
' P5 }5 a! M( f/ h3 v u0 D: i- p plot count turtles with [color = green]
2 `! f8 m7 x e0 k* `end
& y w. m2 I/ `* c" ]to update-lorenz-and-gini-plots% z) U' U7 w4 O# E
set-current-plot "Lorenz Curve"
$ D( W/ V4 `" U4 @2 L clear-plot) d- O% \; N1 `7 L. I; y5 U# s
8 k/ g+ F$ Y7 b8 m set-current-plot-pen "equal", T' R ~7 x% Y' B4 D0 M- _% v
plot 0
2 u1 d. f$ M. E( a7 @+ R0 T7 y plot 100- N: o7 Z) H% X# P B8 X
6 Q) f0 @' X# f" S8 | set-current-plot-pen "lorenz"* C% ^: I% d- A: i O
set-plot-pen-interval 100 / num-people
7 T/ U! ^, v/ ?4 X% L s plot 0
2 o- U1 A) b6 t3 y9 H; p& E9 O" G3 ~+ L( X; |( f# T% n4 p
let sorted-wealths sort [wealth] of turtles
) C% ] x; C/ N. Z let total-wealth sum sorted-wealths% K7 F' n, I8 Z
let wealth-sum-so-far 02 q4 n7 l& u: p% Z2 N
let index 0
: G0 C& |7 I0 m8 i. m; a# V let gini-index-reserve 0
+ B: w( w0 F. A' ]- E3 L! T# O# h7 p3 Q
repeat num-people [3 ]8 f% j$ W9 L2 n! i1 y
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
# j+ E5 J! P/ X8 G* ` plot (wealth-sum-so-far / total-wealth) * 100
2 d+ U( G w( }% f: A9 }8 E8 L set index (index + 1)
3 ^6 U! U7 Y2 c' y set gini-index-reserve) h& J* `! ^3 Q. q+ z
gini-index-reserve +1 { v$ T! `- s+ @8 }1 g/ \& L5 J
(index / num-people) -
4 R5 v$ Z3 f" m" P0 [$ f (wealth-sum-so-far / total-wealth)
3 }# t' a% b. U4 ~ ]
8 o2 z3 r! _, |$ r. U1 X
$ j$ \4 p) V7 L set-current-plot "Gini-Index v. Time"0 x7 N7 j8 u. ~: J% n4 A& O
plot (gini-index-reserve / num-people) / area-of-equality-triangle
7 p! U& E/ {/ M3 @ tend
8 d* w& e, M' D0 [; _- A; X, d7 ~to-report area-of-equality-triangle9 p5 C9 J* K/ [* V
report (num-people * (num-people - 1) / 2) / (num-people ^ 2). x X# S8 b3 E, ^. b
end |