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: v+ v" b/ M. ]. c
globals( e9 K( _: y$ T$ i# _
[2 M n2 T" K; H$ t
max-grain " \4 n H V, C2 z4 @
' |4 l( N" r' q! I/ A( G]
' G$ B- ?8 A! v" o& F- b$ P$ a8 U& d6 g( Z
patches-own
- E+ p: d* w" M' `( H8 O. R9 U; b[
" V" O% W$ {4 @4 }3 M9 J9 q8 _; L grain-here 9 M& }, O S2 K0 R2 u3 m+ f% ~
max-grain-here
+ J+ }5 }6 X8 b]$ \% ]1 U: x' p$ |' V
; Y" e$ A- r2 z" S4 Q$ D1 f. Xturtles-own6 E2 U+ l- y- Y5 a1 o4 g" p
[# U* H" {% Z! J* {+ @# h; q
age
5 n3 U! H3 U4 W5 t wealth
- E1 \3 F4 f/ W+ k% ?& K) y3 K life-expectancy
" V' Y {4 u4 G3 c$ g q8 O# j metabolism
% @8 t1 d% i$ e3 T% z vision
/ w0 r0 J3 B5 M& q% f/ X inherited 6 Z: C; Y5 f. @$ F9 \7 S, |
]( m& Z& w. N' T6 t# _
# U. H" W p. N
. j8 W5 @$ l! Z2 ~to setup
) Q* X1 R6 Q! V4 H& \ ca/ o, o& u( {9 T3 A! l% o3 n6 Z
set max-grain 507 {% M9 s5 D) N" S/ |) v* t% U
setup-patches& @% k& t0 b4 F2 s- K' X
setup-turtles
6 D, a: o4 Y( @ [* {' j3 a setup-plots
3 Q: m8 D+ [2 ~& B+ G update-plots U* X7 ^1 ?2 k: v
end" Z4 l6 O3 ~5 x- R
to setup-patches
9 r4 H/ q- D5 f# H% r ask patches
- R5 o: h& i; |1 m [ set max-grain-here 0
" e. N, e) u$ e: |7 |! t7 | if (random-float 100.0) <= percent-best-land
0 C' r- m6 z) q! @6 ^" B7 j+ t3 r5 f [ set max-grain-here max-grain+ @6 o1 y9 r' l; |3 W* L* s9 n
set grain-here max-grain-here ] ]
" Q, v6 M0 H, C# e/ b' ?. c repeat 5
, f2 S( }$ t, {' S2 p. o [ ask patches with [max-grain-here != 0]' d3 d% W2 E* z' y9 M6 X
[ set grain-here max-grain-here ]8 J: \8 ^' x3 K) k: ~9 r: i
diffuse grain-here 0.5 ]% @& K2 q" A, P( o0 R3 d$ p/ f3 \
repeat 100 j6 |% G+ r `, u5 c
[ diffuse grain-here 0.5]
# m( Z( z. x2 ~ x% h. x ask patches
0 R7 a. |/ `9 i% t [ set grain-here floor grain-here
9 [0 G6 N, @3 t9 o set max-grain-here grain-here
1 x0 z4 o: v3 f# Z- e recolor-patch ]) S8 A4 F% o+ J# ]% `3 S
end
' u1 H+ K5 ?1 h/ ~( hto recolor-patch 0 C/ m7 {1 O$ N! [* Z9 J
set pcolor scale-color sky grain-here 0 max-grain( s6 @+ _8 u' c1 `
end
8 k9 ^" Y- S7 p& w$ \. ]to setup-turtles
. W. ^/ C. \& B8 D$ b set-default-shape turtles "person"
9 k# s. q% l' R' w7 T9 }7 Y crt num-people% H& u) E6 g3 K: k
[ move-to one-of patches 5 ?+ r, o$ v4 \1 D- W# O& D
set size 1.5 6 i7 h) u' `6 l8 A
set-initial-turtle-vars-age
+ F) i M. c/ N$ j8 |6 f% }5 m. S set-initial-turtle-vars-wealth5 z) m' F* C+ t: M
set age random life-expectancy ]
8 H5 A; \. N$ ~ recolor-turtles" N6 q) Q7 d! e# c
end
; _2 |* }' X1 M1 h
/ A' S6 }9 D, D2 f1 {: Fto set-initial-turtle-vars-age
3 c, `9 g5 l" {9 C1 p6 |2 k let max-wealth max [wealth] of turtles3 `' x4 @* ?* M
8 T4 h8 k6 }( s/ T5 h! X
ifelse (wealth <= max-wealth / 3)
, H. v+ {) A7 q$ W7 h! w [ set color red
& A( V! x1 s; [6 U% J set age 0+ ~1 _( U8 G3 U/ i+ {
face one-of neighbors4 * r6 Q' \: `% X/ e( S8 I( Q
set life-expectancy life-expectancy-min +
' q5 u; o7 h' r+ ^$ s' O random life-expectancy-max . j% ~( a+ w) n5 u p* Q1 R
set metabolism random 1 + metabolism-low
( m9 e) G3 g5 B4 d7 Y$ n2 q' }" ` set wealth metabolism + random 30
3 L+ R: {1 l% G# ?/ `) x set vision 1 + random max-vision
& N, C' z0 i3 y4 A8 | set wealth wealth + Wealth-inherited-low ]
. v. _: J! y# S [ ifelse (wealth <= (max-wealth * 2 / 3))
" T. P5 l5 a) N% r2 w7 u [ set color yellow V. L/ v8 \# w" v
set age 0( ]2 S1 J& y" o, q0 E+ }
face one-of neighbors4
! r9 C+ A4 [# t3 g5 W set life-expectancy life-expectancy-min +
$ r2 T9 Y5 G$ W# Q6 x1 f5 M random life-expectancy-max + 11 d' r' t2 E0 j! X& w% ]2 r4 |
set metabolism 1 + random metabolism-mid6 r6 ?5 ^9 f& D
set wealth metabolism + random 30
+ T+ E( W7 ^/ B* `0 [% f/ I' ~ set vision 3 + random max-vision3 a# S: A! t5 G3 T' D: u: V* s
set wealth wealth + Wealth-inherited-mid]
7 C) e5 |. s4 k( K: a) v [ set color green ( E7 _9 Y8 Q, ?# D; c) h' ]
set age 0
7 t G% X+ x& i) A' {3 \/ I$ z+ ~ face one-of neighbors4 ) V$ g1 R; o. G1 U; d
set life-expectancy life-expectancy-min +
; B, y, V, Q9 x, Q" w! W random life-expectancy-max + 21 f: b) r3 e6 ]0 ~
set metabolism 2 + random metabolism-up
; O9 R: ?, [4 ?; P* K8 M set wealth metabolism + random 30 {. b9 M6 _9 P9 ^6 q* Q
set vision 3 + random max-vision
' `2 k- i' D* | F z* V L$ w2 O set wealth wealth + Wealth-inherited-up ] ] , m7 H6 m P/ H0 l
$ `4 }, f; y9 b+ N- M) nend
. b1 x8 r4 K8 T! i/ c5 F7 \to set-initial-turtle-vars-wealth6 B8 H7 F) A% t# d# M* h
let max-wealth max [wealth] of turtles
" E3 `3 O% C, V( K4 f. t- t set age 0
- T7 v6 \ g" |7 E face one-of neighbors4 1 B: x3 @7 v/ H
set life-expectancy life-expectancy-min +
Y1 X* W) D# a! c random life-expectancy-max " }- V' j8 w7 l- }
set metabolism 1 + random metabolism-up
- f* J+ q6 c J" J( Z g. q+ w set wealth metabolism + random 304 S' e5 E# ~. Q: N& s O
set vision 1 + random max-vision 8 `& h& i3 w1 v
end
# Q9 ^2 u: m: g% H- B+ Wto redistribution% J& M1 s' h) i. b* ^+ g9 V
let max-wealth max [wealth] of turtles
" K* T W3 E: ~. [* \" jlet min-wealth min [wealth] of turtles2 J6 T7 F8 \( g7 O4 Z
if (wealth <= max-wealth / 3)
4 b4 s! D( m+ P; F- g1 F) j3 R% u& o [set wealth wealth + Low-income-protection ]* L% |/ I" S, \- y
end2 I, r& c5 N1 N% H7 a, {" H+ x8 s
- \+ K9 |7 R. p0 e
to recolor-turtles* H# P7 w1 Z& K( I3 X* _, {
let max-wealth max [wealth] of turtles
- U0 G. u" R2 D! @ ask turtles
4 X. x" d; H$ O C( _ [ ifelse (wealth <= max-wealth / 3)
6 R, l7 T8 U; Q [ set color red ]0 z/ U/ k" E, z% F1 S1 f
[ ifelse (wealth <= (max-wealth * 2 / 3))% ]- J+ p' [4 Z9 k! r
[ set color yellow ]
% C# l1 `$ K1 F% K) _ [ set color green ] ] ]
) o8 P' g6 L# O' _' A* B$ E! Y ask turtles [ifelse show-wealth?) }# B8 y4 [ c" {" c
[ set label wealth ]/ a2 n3 C9 y" e0 s1 A
[ set label "" ]]
4 z" S4 Y* ^# H; s E5 Y+ Y9 eend
; E; A6 n. ?7 z; Q0 {7 N+ L
5 T1 _% e2 k! Tto go/ u+ k% m' Z/ G O5 e) c' R
ask turtles
9 J, o- ]% z) J- ^: d [ turn-towards-grain ] 1 { r- m6 N; g2 j) b
harvest! b4 J. K" l% V4 ]5 t* r
ask turtles! B6 P$ r+ j: i2 q! ]
[ move-eat-age-die ]& y |& H! c$ t
recolor-turtles- l) {7 p7 ~( l; l V% M" o0 O
if ticks mod grain-growth-interval = 0$ K: y) c8 p( w4 }2 a, v
[ ask patches [ grow-grain ] ]
% ? ~$ A6 P2 u* t5 B
5 A$ q$ z( p% d7 Q if ticks mod 11 = 0
e* y8 k$ P. |- ^, b) h2 g [ask turtles
& _5 K C% }' ~: m7 J! H [ redistribution ]]
2 D3 a [, u ~5 K7 k M if ticks mod 5 = 0
% X, a- O' |7 | [ask turtles
3 n: e& c2 s$ w [ visions ]], M' {6 @" `, Q, W$ M
tick# k/ w+ a( N [
update-plots
, A4 l' D) V7 g$ x- }0 Rend" ]3 W2 }% W' ]( {
to visions
: [( K! ?6 X7 W9 W8 U _, ` set vision vision + 1
S) E) v' L4 C% s+ s! {' Gend
* O9 h, q9 D8 Y y: R$ Y# k4 i7 A& X3 h& {* s0 p, U& [
3 @0 \& h$ M4 z8 F5 }% Y6 ?6 M i P7 C$ [. M8 l3 B X- ^2 k" d# |
to turn-towards-grain & M8 x) \2 y& |. a9 U
set heading 03 H, i- u8 t, |5 z+ o1 p0 A
let best-direction 0! T. S4 c: A7 R, L8 f) I
let best-amount grain-ahead
8 G8 x ^) {6 N: W, g h; q- a' h F set heading 90
/ z) j8 Y" ?$ y" Y! \4 C if (grain-ahead > best-amount)
- s+ u3 y2 S# f& |& Y- e. U [ set best-direction 90
' t% k7 d1 Q2 k% p! Q set best-amount grain-ahead ]4 V' w3 J Q* S( B: \2 }
set heading 180
6 a( X( Q' S5 A1 e& U4 n& z% o if (grain-ahead > best-amount)
5 x8 o; H; r& q* z. d9 e4 v [ set best-direction 180
4 b! R6 r/ Y% w, c- m( K9 \! z! A set best-amount grain-ahead ]
, j' [& D" L/ i8 b1 O# D V set heading 270
9 B8 S( G: O1 [$ u0 b1 U; N if (grain-ahead > best-amount)+ F6 g$ D* V9 T' y$ i% I
[ set best-direction 270
9 |( T, }6 @2 k! a' C- W set best-amount grain-ahead ]
' ]" P+ S7 i+ K. N9 u) N set heading best-direction7 E n2 m9 H, L
end1 U8 i0 l* N7 @% \+ X+ B' F0 k
6 d* _0 J3 S' _, X* T
% M" h$ i& L1 j' R; d- N" K- Qto-report grain-ahead
$ Z* J5 ]4 O; ]: V* k let total 0 Q) J9 m+ L8 b* `4 m4 j
let how-far 17 Z+ m& u1 N& ^2 l3 Z( H
repeat vision
# d7 s; K; [9 ]% A1 k# M. _. ] [ set total total + [grain-here] of patch-ahead how-far
# @; i% r; i1 D& \ set how-far how-far + 1 ]
5 ^' H5 `/ {5 K" l; O2 s2 \2 W report total! ^" U# G3 y+ S9 E5 R$ H
end+ L- @/ M0 V$ W( Y- T0 E, o
?$ Q/ S* ^2 w P- F8 m; T' u, M
to grow-grain $ [: j0 `( a! J+ _" o
if (grain-here < max-grain-here)4 e/ b5 N% m8 J/ |% l% V: n2 z
[ set grain-here grain-here + num-grain-grown
( l) |1 l7 V& A6 C0 r% k% C if (grain-here > max-grain-here) / O7 z( M& e* n, ~6 J
[ set grain-here max-grain-here ]7 C! R% v o* G* F1 O% b+ k& \
recolor-patch ]
) P. s8 B' \- b( Mend2 m7 W1 O- ^/ N4 M+ }! F" W: R
to harvest1 Q4 W) i( p+ ]5 [( i
ask turtles
# t( n1 k, ` \0 x& f& t+ } [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
6 l: g( c; ], |2 ]8 R4 T% N ask turtles
0 X v7 J$ Z( i. T7 c [ set grain-here 0! U/ H+ j8 _; X0 |2 n7 ^
recolor-patch ]
" K5 c! Q9 V w% ]) S' g
% L9 W0 L: L9 d. \* Eend
& M- o: X9 L9 @
4 [% R4 f" Q; I a cto move-eat-age-die
; C/ x, x# V$ |& P5 ^1 o' m fd 1: W# I( ? ~& }& B) }
set wealth (wealth - metabolism)
. g& k- r* p$ _+ ]' U set age (age + 1)& T0 E: V7 t7 |8 y! j9 U
if (age >= life-expectancy)+ y" |6 H+ u% V
[ set-initial-turtle-vars-age ]
5 {# Z$ c# W. K; @ if (wealth < 0)& `1 ?9 a9 I3 O9 u+ X3 |/ H$ R! l, _* Y
[ set-initial-turtle-vars-wealth ]
; l. P2 U3 @1 j/ W! O* r ' B( h1 S, {) Q/ x4 x5 r4 {
end) p( K! ]4 l" [) \+ _' p; | V. e
0 m5 L. D& ]- E" m2 T2 z/ U( w; C; R. u$ F. i; G
to setup-plots2 b7 p: ~: g. `3 X7 o! G' \
set-current-plot "Class Plot". F3 w4 h5 K3 L! ?* f6 O' T6 r
set-plot-y-range 0 num-people
) ?" T! E2 y5 P! w7 w set-current-plot "Class Histogram"" S9 P6 Y- a# b. E
set-plot-y-range 0 num-people
1 }) `5 y& I- f+ i' x" Rend
. E/ l( e( L* H K( x; P6 Q2 \" }8 v4 ^8 J1 N: S2 K6 @ K
to update-plots! M7 [/ h9 m( r3 V) ]5 A
update-class-plot
, y4 n; A. b6 [: `9 Z update-class-histogram
' q) ^1 `4 u6 A- x [ update-lorenz-and-gini-plots4 z9 x$ ~" @2 D& z0 P
end4 i" m* k1 h: \ i
! q( ]/ F& {; U! I& J
to update-class-plot
4 Q6 h& B% M$ S" F4 X set-current-plot "Class Plot"! I" S4 `+ S. ~4 v
set-current-plot-pen "low"
7 f4 @) i* f9 E& z+ U plot count turtles with [color = red]
! F: `) `; b6 L set-current-plot-pen "mid"
8 I8 b5 M7 b1 V2 ~ plot count turtles with [color = yellow]
# z& l6 F) J* Y; i set-current-plot-pen "up"6 O( A8 D& S0 z6 b1 x
plot count turtles with [color = green]1 i, P& B5 Y2 s5 h! t9 w" x: F
end
- G+ L4 j0 D5 S+ @ b1 _
! E& j3 N- [3 d+ c# yto update-class-histogram
9 x0 h @3 U: \ set-current-plot "Class Histogram"
5 }( H( ~9 I0 ^8 W! P% S% q plot-pen-reset
2 t" [0 g' d9 f7 ]& A4 F" q/ Z set-plot-pen-color red
. G2 z0 T+ @) Z plot count turtles with [color = red]9 M" t# p- ^ h0 N5 w' @
set-plot-pen-color yellow9 i5 `" f7 y0 H' H! ~) \
plot count turtles with [color = yellow]
+ r2 i$ z" z( q# B2 [+ K set-plot-pen-color green% }* G& @# r) m S: s/ u/ J5 v3 F
plot count turtles with [color = green]6 y/ S, ^) {! A, p7 X9 r
end
8 _0 y \3 `' V( _* J8 e0 Fto update-lorenz-and-gini-plots' o1 W. H2 o7 q2 D: I
set-current-plot "Lorenz Curve"
; ?* M) s1 R0 X8 X/ g; n clear-plot' _. n# L- [) {
7 T/ G; V' }6 ]: _
set-current-plot-pen "equal"
, g: R) e. r; ~# _$ Q plot 0
, }! s; a, Q" S" d8 m9 Q3 j plot 100! m1 u7 f# i+ I* v: h3 h
9 M/ l4 I4 k e3 j2 q% g7 ~ set-current-plot-pen "lorenz"
% H3 p% t: M% t set-plot-pen-interval 100 / num-people
7 ]: e) z( g7 g7 @' j' W plot 0; l$ I7 p+ [& J6 L; K5 {" g
% ?" b1 q7 ]4 p let sorted-wealths sort [wealth] of turtles( O& ~" G. p8 t& j5 w2 G0 P! ^
let total-wealth sum sorted-wealths7 E; |$ K( ~( {+ | C, ^
let wealth-sum-so-far 0
5 [$ m- t2 H# \/ v let index 0% D* q: S4 k% t$ x5 u- F( P8 F2 P
let gini-index-reserve 0
! E* D5 s( {+ ~' Z7 x% F( i5 ?* m, _3 |6 F1 C' I, v
repeat num-people [
: ?. Q& ?; v1 J4 l; f# N' g, E set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)& B* I* M) H5 @) J9 ^& {
plot (wealth-sum-so-far / total-wealth) * 100) G7 {, [7 ~- T: M2 [7 W4 |& Q, d
set index (index + 1)6 O7 }# R- l, A2 ^7 F. @9 p# x4 M4 K
set gini-index-reserve. n+ V' k% k9 a4 Q. x
gini-index-reserve +3 g/ E" G. u$ G8 O& E- A9 O1 L
(index / num-people) -" n4 O7 P+ Y" g m* n2 x
(wealth-sum-so-far / total-wealth)7 w |- u; {1 _/ I$ _- W: s
]5 X' t. y! I& c N4 _3 Q
+ n4 z- G0 u% {' {( B set-current-plot "Gini-Index v. Time"2 x& R7 h/ T, L- ?
plot (gini-index-reserve / num-people) / area-of-equality-triangle
- D# Z& M! e* X; f# I& pend6 |/ s7 _- ^2 M+ D- k
to-report area-of-equality-triangle F" O6 E8 E' x
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)% G, O% ^- W3 L) e
end |