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
! p/ A v9 P8 D% S4 _: tglobals3 v) Z: N- @2 M: H! ?. C
[
% l4 B4 y+ ?8 J7 Q$ t0 d! O max-grain 1 x X% g* p" e& D# L. B9 Y2 X4 y9 p. V
7 t& _2 M; m3 _; A1 N]. ~! f( X# ]9 I' M& }& Q
' q( i5 n* s6 m! N$ q3 x3 u4 Jpatches-own
& j+ w6 u# I( p3 K' r$ `- j[. j( J, D/ R8 H! ?6 }* j% A
grain-here
, }, b+ g: Q4 `1 |6 t& O max-grain-here ' |* k; u. b, Y( D! U# A. @8 j
]% W' Y9 S% V$ K
: b2 O/ f8 n/ Y; i3 i8 G$ E1 ?, uturtles-own
; p( [! Q5 P. {% B, s: v[# B* J, M' V- N) w& T
age ; I* G% W( @+ m* \* Q4 u
wealth
6 b# ^& V$ ]+ j. l* I life-expectancy ) Z: @, {- F) Z
metabolism
+ T& Z1 j2 n9 R! ? vision
2 Y7 k. l, Z3 r3 \3 k inherited
" ^2 Y6 I0 T: P5 ? r]
4 ]6 l# `6 ]1 l) p9 k- l' o4 R( L. M2 E `
4 l2 Q; J" g% S2 ?to setup
" O5 d( A3 g; ~; R ca* M0 z" A2 L" r5 B8 N d
set max-grain 506 Y6 W8 J2 ?/ y. L
setup-patches* Y. M2 \% G- f% @" `
setup-turtles
. x9 A& J9 L' g2 \6 g9 G2 E& h5 Z setup-plots
9 D% b! U/ B, y4 ]( b update-plots
3 t; b; v! m& n$ P, N/ O* rend0 q- h' ]2 l7 ]4 x! @: K" K7 Y
to setup-patches
9 ]0 N, Q! c* x. r5 [2 U: R2 T. V7 I ask patches: L9 G; q( d {1 Q
[ set max-grain-here 0
% Y& o! r( o" u/ ~) ~6 e% M if (random-float 100.0) <= percent-best-land) G! m" l) ^, g2 p4 |
[ set max-grain-here max-grain# |6 f% p1 e; ^: q, y; _4 W
set grain-here max-grain-here ] ]: E- w+ K8 p+ X1 q0 R$ `
repeat 5$ }6 q" g( {% |, E
[ ask patches with [max-grain-here != 0]
4 F1 F2 n v" V" b u1 l T1 D% d [ set grain-here max-grain-here ]
$ D" ~" Q0 s: M! [' _# v3 [ z diffuse grain-here 0.5 ] h# d- @0 E- S/ H( v) b
repeat 109 n6 S+ }7 j3 C
[ diffuse grain-here 0.5]
2 ?* D7 s; ^1 l; e8 I ask patches
1 Q. N( G1 m6 D, d [ set grain-here floor grain-here
; Q5 g1 `& y( m set max-grain-here grain-here * I4 S: K8 k+ v* E
recolor-patch ]
0 }" B& Z& F& @, A, {, gend. h: N: X7 p% s
to recolor-patch $ u# F0 }, d3 S! w2 M5 N9 O
set pcolor scale-color sky grain-here 0 max-grain! \8 Q Z, B8 F% E
end5 h8 M/ b {2 U1 G
to setup-turtles7 `0 [ f" {0 ]7 B% s* d4 V" H; L; [ d- p
set-default-shape turtles "person"0 o* Z5 O7 F9 \5 ]5 L4 T
crt num-people' D. R& }$ N- {: Q9 I7 k$ ~7 u
[ move-to one-of patches 8 v( H# p1 Y! z, m
set size 1.5 * D e* }+ x! x5 ]/ t, S
set-initial-turtle-vars-age
1 h; V$ d7 A# @9 B8 X) j4 ^) p set-initial-turtle-vars-wealth
; U* \! k: d" i8 | set age random life-expectancy ]
( B& b1 f' U' |/ u2 f" @ recolor-turtles8 Q. a9 {/ [: k. r; R
end% } l/ _; c9 Q. ?, S: S
0 F/ B4 s/ l `2 M! y- G- fto set-initial-turtle-vars-age! j& h/ I" y0 o! W
let max-wealth max [wealth] of turtles
/ P% O, ]+ J9 u8 X% D
- I, t0 a, }. V8 @6 h ifelse (wealth <= max-wealth / 3)
' M0 L. Z& T8 l' _9 ^3 b% f* d% ^ [ set color red ) Q) m* {. E9 ]- A' p
set age 0
. e9 t+ X% m6 R/ M0 _- M face one-of neighbors4 % Z$ G# l6 o8 X1 I
set life-expectancy life-expectancy-min +
1 s& W2 B; a. p, S3 Q random life-expectancy-max ! v+ x3 e! \) Z/ G$ G. e
set metabolism random 1 + metabolism-low# c6 S0 n7 I! W1 i, m, ?: p
set wealth metabolism + random 303 E* n, r4 `; A( j
set vision 1 + random max-vision
' [: e6 ?4 o& Q$ s5 G5 n! f+ A set wealth wealth + Wealth-inherited-low ]& X. x; {* e; R1 V/ w9 G
[ ifelse (wealth <= (max-wealth * 2 / 3))
! m! F- O& ]5 \- j; a [ set color yellow & _! u- C, B4 B* l$ ]/ A
set age 0
! y- l$ M$ ?- G+ w4 P+ I" u face one-of neighbors4
p9 Q% E3 Q' V$ Z: j& @4 N set life-expectancy life-expectancy-min +# I- r7 y) j( B @1 _
random life-expectancy-max + 1
2 w% y3 Y7 O5 L0 g9 V6 ]( J set metabolism 1 + random metabolism-mid3 H. N- O, ]9 g: [
set wealth metabolism + random 301 K3 O O: R7 g
set vision 3 + random max-vision
$ s" t3 V. z1 [3 p1 `$ N% M set wealth wealth + Wealth-inherited-mid]( z1 X8 i+ l! s; Q) d
[ set color green
& k% y6 R; B* S1 m# R3 K0 I1 W set age 0& B4 a, `- C: o' |( B1 {: L
face one-of neighbors4 - E) R6 a, b1 K+ A& |' l
set life-expectancy life-expectancy-min +
( @' F# f2 y! c. [4 E- j; a random life-expectancy-max + 2
3 L3 S3 Q$ y' a set metabolism 2 + random metabolism-up% {( a; X2 [. n& N+ u# ^
set wealth metabolism + random 30
1 X* E2 s. S# }) | set vision 3 + random max-vision
# d) s% Y; K& s; ^, m/ K set wealth wealth + Wealth-inherited-up ] ]
; ~' i6 I$ U U: v3 O
; ?# {! k% {" ]" U2 T, Jend6 i2 z% S& a( O, |
to set-initial-turtle-vars-wealth
. A: s' f, {+ W* g6 I, V let max-wealth max [wealth] of turtles: w$ v! D& v/ z {
set age 0
4 @8 e9 ?0 X. J* m face one-of neighbors4 & S& `1 X, K- M5 Z7 ?3 M: @( Q
set life-expectancy life-expectancy-min +9 M; F5 l4 s" M$ y$ o
random life-expectancy-max 7 p3 m$ W6 L/ w/ Z T) b
set metabolism 1 + random metabolism-up9 f0 ?/ X! t3 I' h2 J% E _4 [: J
set wealth metabolism + random 30) [! j3 c, g- ~0 z
set vision 1 + random max-vision . i" D" L' n# L( `) ?! M; |7 r
end2 t& i. U9 d! o
to redistribution
5 Y5 ?* Y. Y. [& Y- E) |6 n; r ?- wlet max-wealth max [wealth] of turtles
8 V4 k: [0 D/ A$ b; Llet min-wealth min [wealth] of turtles0 C7 [0 m3 Y% m7 [
if (wealth <= max-wealth / 3), i. x: W6 N( B& z+ N" E/ j8 Q ]
[set wealth wealth + Low-income-protection ]
! d( d3 ]& {6 o% g0 S* g$ Hend, k, y# d. R2 g* d. K2 j
3 U; U6 R% o& j& R
to recolor-turtles
* r: q: u0 \% `$ a6 z- h let max-wealth max [wealth] of turtles
7 w- E s5 x. s$ x3 v3 D7 Q+ J ask turtles
. ^( }+ w2 P x' J [ ifelse (wealth <= max-wealth / 3)3 r# E* W3 i- M+ | n1 \
[ set color red ]- @2 d0 w5 i& t4 m& w
[ ifelse (wealth <= (max-wealth * 2 / 3))# a% e: y; I/ m5 x7 u6 T1 G' I [4 o
[ set color yellow ]
+ U, h9 C$ `, _8 J3 Q! ~ [ set color green ] ] ], f+ |+ B c1 A1 U- B( d
ask turtles [ifelse show-wealth?- R' H. k$ J) ]! J+ u
[ set label wealth ]
9 a% ?" y% |) k( {, p: h. Z [ set label "" ]]
) O& c7 _7 u0 B N1 J0 dend% i# I# p! p. g; w
8 \' _- n8 n3 L: x) e
to go
2 ?3 q! B0 \0 H0 v' B2 h ask turtles S1 ]3 |8 \$ l j4 ^' k; Z
[ turn-towards-grain ] ; I$ k5 Y* d S* n1 Z
harvest$ n& C. T8 ]) \1 `
ask turtles
: ]2 {- g1 c6 W. ` [ move-eat-age-die ]
3 q3 ]: p: \% L. { recolor-turtles
" P- W/ G6 V& }) a) s+ A if ticks mod grain-growth-interval = 0
/ j. v- l; o; t8 ^ [ ask patches [ grow-grain ] ]& R; g6 v1 j s" F/ `8 ~
5 C0 @: C* o/ {5 |; l if ticks mod 11 = 0
2 ?9 T: q; @# j3 Q9 w* ?7 a [ask turtles& y1 r1 e ^2 }2 Y8 Y' E. X
[ redistribution ]]
0 w& u$ t+ M6 a7 [" S5 k3 ^ if ticks mod 5 = 0
7 a4 L" E5 \; T( m) u2 S [ask turtles1 U4 o. J/ W. u+ l# ]
[ visions ]]9 I/ N9 v$ V; z/ I ?0 u3 Q9 N
tick
2 r2 v3 n+ g5 F! A+ v/ e W update-plots6 @; \) Y M$ r2 d2 Z
end2 g A# [* k8 R7 O6 f3 a
to visions8 M& e5 S1 c6 T4 Z
set vision vision + 1
# b. [) {# S% _& n Pend0 s; r. u' X- B. x, a3 z7 Q Y: M
9 a! Z ?- F9 }5 G
- M* Y" b9 p6 H* d" Y
/ [, C$ ^! t4 R5 h6 g& u0 Ato turn-towards-grain
' Y. }9 `; S) I! L# r P set heading 0
' Z5 Q! o& y0 R let best-direction 07 C% B! L& E, o7 s+ [$ s" b) k
let best-amount grain-ahead
2 `; I" b9 }& s7 D: x& J0 p set heading 90. U6 g3 A9 F$ o, p
if (grain-ahead > best-amount)
- k* t$ Z5 O% }# a, j: {; N [ set best-direction 90
/ {/ `8 e {5 A7 X! u. e set best-amount grain-ahead ]$ @4 @/ ]2 M( N# m9 o& t/ `
set heading 180
, x# J2 Z* |$ N& h; y% E$ a8 T4 V: l' u if (grain-ahead > best-amount)) \: @9 B1 U' q+ T6 P" i8 e
[ set best-direction 180
2 {- e4 O0 q! @' R set best-amount grain-ahead ]* L# e( D% ^$ p( t
set heading 270
! ]5 q8 _% O6 } n1 M if (grain-ahead > best-amount)
, y( n; A" G* l) n7 E) c O% G$ p) Q [ set best-direction 270
* v1 \" m% l; E! W# k% ~ set best-amount grain-ahead ]% l: o5 @( q) n- j7 e7 {
set heading best-direction7 L/ z/ @$ _! S: _1 w( A& G1 n" i* }
end
: T3 q$ P' [& `
+ V0 p( [/ G$ C5 n7 p; y1 b( J- M
& P- [+ s+ A& `' Vto-report grain-ahead # X6 N2 j2 y+ I2 y/ X5 F4 }% _
let total 0( j7 O, P0 y H; F% j& h" B
let how-far 1
. C, i9 ~5 m; `( o) G0 i! o# `5 J, N& E repeat vision
5 L) Z3 @9 G* m3 `( c6 ^+ E6 n2 N+ H [ set total total + [grain-here] of patch-ahead how-far
1 }, ~$ Z/ b) ], ~& n. m4 Y8 x set how-far how-far + 1 ]; v5 H9 D, s. W" Y
report total2 E4 X5 {1 ?: L3 s' N! R6 b
end# J& j8 ~ a8 c4 i/ Y7 b- K! k
' U6 P9 I5 M4 |# q
to grow-grain $ O# c: [ P& S7 E2 F! N" ]' B4 f
if (grain-here < max-grain-here)9 E6 A5 p, ]- `/ E4 z8 V2 n
[ set grain-here grain-here + num-grain-grown
8 P( }4 e8 \$ p3 [' L+ U. w$ c if (grain-here > max-grain-here)
. ?2 ?7 d+ `* M* N3 J, V8 K' w [ set grain-here max-grain-here ]
: D4 b2 W4 I& U1 j9 m# e# c recolor-patch ]
" K! q, ]% m [end! c2 ]( T6 \0 U4 E9 I
to harvest2 N' [6 _; G+ Q k% O
ask turtles$ _" O+ x) w- ]1 Y; F* |
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
, S5 ~4 t3 Q0 d* x* a4 D( E4 G2 b4 M ask turtles2 H; c! |4 l' G
[ set grain-here 0. X9 f2 {; p0 }. d6 C
recolor-patch ]
( N2 W% C% k7 Z3 b% U
: \2 L5 Z1 Y, _! D; i* jend2 l8 D( i6 D* x
- G3 C/ ^- i9 S/ k8 u8 r, k
to move-eat-age-die - Y. U; R/ [$ ^# D! D1 a
fd 1% c* w% S0 _" R" M# ]
set wealth (wealth - metabolism)- v/ D1 p& P* I/ M- Z$ {
set age (age + 1)
7 I, T8 K; Z' G2 x3 n/ C if (age >= life-expectancy)
6 Z( q- y, H; n. ~5 P) ` [ set-initial-turtle-vars-age ]
% A6 j; T7 |5 t" L3 V if (wealth < 0)
) d* i6 Q- y' U! ]- F: _ C [ set-initial-turtle-vars-wealth ]
, Z$ y: b3 i4 j3 J$ A/ G0 a 7 g2 S1 E$ {' p% H; E9 h& J
end- {9 n0 ]8 p' N: k/ f' [; j& R
5 L+ C" J: p7 l1 L; Q5 |# f2 M
5 {2 ]5 M. V; kto setup-plots+ L9 y v- N7 ^1 K2 X& k
set-current-plot "Class Plot"# Y1 M, |. J7 s5 @4 N7 @" X
set-plot-y-range 0 num-people5 b' i% @. r2 Q: Z% S
set-current-plot "Class Histogram"
3 X( @% B6 ?* C$ R set-plot-y-range 0 num-people2 q9 ]% \; x" z3 p: d2 m# h
end+ m$ k# G) M( _- O. w I
3 R* ~2 j* h4 s
to update-plots
6 Z$ _4 G2 ]% r: s update-class-plot9 @+ j' |; k! _" d! a) S/ a3 y
update-class-histogram! s9 L6 k0 k" @$ }3 B4 X
update-lorenz-and-gini-plots6 v* o# ?: j# l
end
% L+ w5 y) h- B% ^
- T& c& V' v4 P6 L, B3 n0 ]( f0 sto update-class-plot
: h: L4 M3 v0 R& S5 @+ b+ c L set-current-plot "Class Plot"
4 c% i* b( _5 Y/ M7 \2 c set-current-plot-pen "low") f" s( C5 H* h+ I
plot count turtles with [color = red]
1 f: ^- n1 g& K/ S. x; A5 s# t set-current-plot-pen "mid"
4 n7 @0 ]! A) F0 P6 J T! M plot count turtles with [color = yellow]7 `4 e# G* ?- S$ Z
set-current-plot-pen "up"
q2 `+ ^. g4 L0 n5 \- y" D; \& s1 J plot count turtles with [color = green]/ U. B# B! \$ C& f
end7 }% B& O, Y5 A% t- t; w! j. ~
7 C( N3 R5 X, M- ^to update-class-histogram/ J- W, c" H& ~1 F$ @
set-current-plot "Class Histogram"7 [3 u5 s4 p+ n1 \) `# B
plot-pen-reset
8 C6 J$ ?% ^1 F4 H set-plot-pen-color red! k4 T6 D6 Y5 C7 [( L- L9 r
plot count turtles with [color = red]
% [" Z( K. j% h) Q3 |* g3 ? set-plot-pen-color yellow
) w( F/ @2 [; k+ Z5 g; B plot count turtles with [color = yellow]
: I4 P/ o# O ^5 w1 ?& ^2 @6 F$ J set-plot-pen-color green0 Z4 V7 m/ l0 j7 C2 I c1 Y
plot count turtles with [color = green]4 y* i$ u4 _/ p, q% F4 @
end
; ~( z" q3 p; g# jto update-lorenz-and-gini-plots
+ K- T& q9 r5 _ Y' d3 r set-current-plot "Lorenz Curve"
# ?* Y6 ?4 t, g' v7 _5 { clear-plot
/ r, O+ x) L Q0 [6 ]7 `2 o- i# {1 Y( ~' Y) s
set-current-plot-pen "equal"
) b, ]0 W0 e* w/ n, k& V2 G plot 0
0 M; X' D1 |/ ^" Z: H6 { plot 100+ d4 x) x9 V) p# k
. F) e: B- [9 m J, e4 m% P
set-current-plot-pen "lorenz"
6 P3 w( ~! H( H( R* w set-plot-pen-interval 100 / num-people
' ^4 u& ^, c+ n; c; _3 W% {9 {9 P plot 0
5 v1 h* f) H( A
6 E/ B- D. [8 h7 h- C let sorted-wealths sort [wealth] of turtles
% x' X- a2 N$ {4 e let total-wealth sum sorted-wealths+ z$ K! N- k; B& I
let wealth-sum-so-far 05 {+ K w5 r- r1 _7 [- W. Q
let index 0! @6 x$ k' F. g1 c
let gini-index-reserve 0# L: V5 |& X! t% d- w1 O
$ |% \- r5 A, Z4 G+ a repeat num-people [
( ]! J' Y7 @* |5 ]: k8 |5 Y0 F+ A set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
G' S' p. @9 B/ t% w plot (wealth-sum-so-far / total-wealth) * 100
7 \# ?. B, Q; R" j set index (index + 1)
+ G8 ?0 I, i9 Q' R, ~ set gini-index-reserve+ g: C6 Z- }4 ?# Y8 J6 @
gini-index-reserve +& {7 G# Q5 E) {/ q- Z
(index / num-people) -8 B" O5 V7 k; i6 ?$ Z v
(wealth-sum-so-far / total-wealth)
6 m9 i2 B4 @3 L5 `! H: b4 f ]
6 m/ p* M- g2 z4 r1 f
- U0 D+ @; b+ H' F) H& W* K. K set-current-plot "Gini-Index v. Time"/ b% M! U. Y) Z% S. {; m% n
plot (gini-index-reserve / num-people) / area-of-equality-triangle) E; ^: t. J; y+ }3 y% n
end
9 F$ t1 S w Y `& f3 ito-report area-of-equality-triangle
* r# q: J8 S: R O% T report (num-people * (num-people - 1) / 2) / (num-people ^ 2)! a; A. Y- }! g* f& C
end |