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
; u7 I; t# O3 Q4 I5 Q; R# Kglobals
) \( \1 Q4 {7 B2 @2 v- A) t/ Y; [- I[3 S5 t0 z. J5 p# h
max-grain 8 J" f0 R) f9 P* t, A8 s, R# l
/ y4 o# p( \- \9 M
]- T' `$ g, K4 V X, A0 R
( Z. G8 ~& I% D- l: xpatches-own j u9 |' M( p0 W/ I
[
K! P! \ Z9 T- _3 ? grain-here - k8 X3 W# B0 j7 ^
max-grain-here ! f7 P9 ]2 }* {+ h6 L+ ^+ `3 B: j
]% E7 m' B8 H+ O. s$ ^0 A$ t
* [/ e! n, N9 V1 t# U3 I* [turtles-own
8 k* U: P6 H8 C9 z5 d9 s" M[' h& i( D8 a3 J) ` M- O2 P, s
age - p* f: I6 P U$ `
wealth
0 F' Y: Q: g2 g3 i+ S life-expectancy
( j1 @: w! n3 e) ` metabolism # Y5 ^; W. N, f' A: v) D. {8 G
vision" ~0 S$ s5 e8 F2 p$ y9 j' u D- x
inherited
* K3 z+ {* A5 e0 I' |8 u]" z3 _+ y& w1 S6 d
S3 p, ?/ a; P. p6 B2 j6 i9 i: b- p+ Z2 U+ `
to setup* U' I5 i D! B: G
ca5 w5 @+ S0 c) a0 t* d
set max-grain 50
5 @6 D8 K& ]5 L/ b setup-patches
6 g0 L8 q. P! G# T# z setup-turtles+ j8 b0 w! S( M
setup-plots
7 Z# w( ~6 ~9 N1 a' D3 I update-plots
4 j6 R9 n/ U i1 T6 kend8 ~" M4 o- h# C! ^; r
to setup-patches5 X" v" Z' K+ I( s* z+ M8 [& H
ask patches
4 Z5 l" \9 {" I( ~0 Z [ set max-grain-here 0
+ x! A& |3 @% R- X2 a if (random-float 100.0) <= percent-best-land$ s1 \, g" {/ R# Q5 o( ~
[ set max-grain-here max-grain
) R1 w+ E8 [9 |* \" s1 Y% W set grain-here max-grain-here ] ]$ T! k( x/ |- G1 `: H& O) ]
repeat 5
% Y1 Q3 t9 L5 ~: m* }+ n [ ask patches with [max-grain-here != 0]
; i/ i$ V. h; O) c' \ [ set grain-here max-grain-here ]9 K, |6 K- n8 G$ ^
diffuse grain-here 0.5 ]0 l9 n( C$ p8 v2 d) B2 d1 T
repeat 10+ [3 |, |4 r, N8 E: [% j! [9 ?. `
[ diffuse grain-here 0.5] 6 ^% w% n+ G! J$ d0 d6 N* M
ask patches) d3 y. i) u- C: r: c& X. ~
[ set grain-here floor grain-here 3 u1 n( P$ g% l, E5 t9 ~4 a, ?
set max-grain-here grain-here
0 v" c# z, {6 I, J6 E% J3 r6 n0 Z recolor-patch ]& {( G0 f8 z+ q2 m% Y
end$ _% b8 r' _3 t
to recolor-patch . a" d' ?$ a5 J6 P4 ?6 F. x
set pcolor scale-color sky grain-here 0 max-grain
. F; }6 V: ]' d1 Yend
) R; A6 I8 a$ b; h) ~) lto setup-turtles
/ }6 O: l- A) a2 @) a set-default-shape turtles "person", L% f) E' A' ^9 r C5 R8 k7 P* f
crt num-people1 e5 m3 z4 k9 Y/ E
[ move-to one-of patches & f0 l. l& l/ }+ v+ @( E) @3 o
set size 1.5
1 b8 h" g6 O' L& g set-initial-turtle-vars-age
5 r6 g& D5 C( ~# l9 B set-initial-turtle-vars-wealth
; c0 E) q# l% s( K5 W set age random life-expectancy ]
+ z1 w! J+ ~1 V, H7 I recolor-turtles
- u7 T3 p+ R( Y& r' Uend: i5 w1 K" Z5 k' O
+ d. `5 l* f4 K% B: K1 c7 V dto set-initial-turtle-vars-age+ z3 W( g5 U% d7 _$ i* e* c( J( @
let max-wealth max [wealth] of turtles! R; V- B" I4 t1 P: t0 ]' L1 F
+ f% `4 ^' C% J4 G# `- w ifelse (wealth <= max-wealth / 3)2 `8 d) c2 V( t5 K' a P
[ set color red
0 [3 k; D) b7 K set age 0
. B3 N7 @" h" A* K$ a7 \& q9 @% |2 x. I face one-of neighbors4
$ _$ S$ A3 J* i2 `( ] set life-expectancy life-expectancy-min +& `! a3 }4 g7 [: E# D' ?: Q
random life-expectancy-max
' C$ j9 d7 O3 `* W+ y! W, Y T set metabolism random 1 + metabolism-low
2 o8 K( Q7 B% w* c8 }9 u/ ^ set wealth metabolism + random 305 k9 A# G- a5 D4 [. E1 \# z2 @
set vision 1 + random max-vision
* K% k/ H; r' Y7 Z3 V( Q5 s/ } set wealth wealth + Wealth-inherited-low ]
% j) x) I1 I. ]9 ]( Q3 J [ ifelse (wealth <= (max-wealth * 2 / 3))
+ z" T7 e) Z1 x& D( T5 ?, { [ set color yellow ) C2 H# T" f4 x; |/ L
set age 0
, S* C$ g3 Q5 G5 F/ s1 B6 ^" A6 ~ face one-of neighbors4
' A) |- Q2 ~ c set life-expectancy life-expectancy-min +
3 ?. L2 m) C( C random life-expectancy-max + 1
1 D0 M% r) n6 p4 \) `% I6 o set metabolism 1 + random metabolism-mid, S% B$ z" X8 e; s$ g# d
set wealth metabolism + random 30
; w. a# q# {+ l ?+ G set vision 3 + random max-vision( U" }8 w. i+ \
set wealth wealth + Wealth-inherited-mid]4 F- x! r* [! f. R' a
[ set color green # Y; C0 |0 Q- s) V8 d* l8 u" M
set age 06 T8 v# ~: C- w5 b. m* h/ ]
face one-of neighbors4 ' `) L, ^: S; D: _
set life-expectancy life-expectancy-min +3 ^$ E1 e- l' f. Y R: v2 q& h5 d
random life-expectancy-max + 2
) C. D' y2 l0 \7 E' ?4 ] set metabolism 2 + random metabolism-up4 V+ n# y9 z t$ m8 @8 l, ]
set wealth metabolism + random 30
/ O e: f" d/ d( H S" ?+ H R8 S set vision 3 + random max-vision. ^ y* q: P/ ?5 j. Z/ g
set wealth wealth + Wealth-inherited-up ] ] & }8 ?+ x8 [4 H4 G1 H! a( b
6 Y# f. S/ W$ O2 U4 R
end4 [% @; G/ N+ C! i. F! I
to set-initial-turtle-vars-wealth, b, h8 u/ Z* Z% d
let max-wealth max [wealth] of turtles' a3 j+ k! U, B
set age 0. f( Q, @7 w: z; ]
face one-of neighbors4
+ B4 q, q4 O: r4 U set life-expectancy life-expectancy-min +& L( E: M# D% |( o" |* K
random life-expectancy-max ' X1 N; [# w; C0 Z0 `
set metabolism 1 + random metabolism-up' o5 T/ Q$ l1 v8 Q
set wealth metabolism + random 30% v s6 a% F: E
set vision 1 + random max-vision : g. r& t" E0 V! O+ V
end
& L: y4 g9 h6 z/ t9 S& y% Z7 T+ Sto redistribution. K9 c1 V/ a# _1 L8 F6 r' D2 c
let max-wealth max [wealth] of turtles: b1 f7 p3 d* N9 X& _% Q' x
let min-wealth min [wealth] of turtles9 [- N" Z8 W1 q- @: u, v+ F' ^
if (wealth <= max-wealth / 3)
1 q, M; r* Q0 C [set wealth wealth + Low-income-protection ]
5 ?) Z' \8 J. v" |end
. }6 q) b8 \5 _ Y0 P 5 P& `5 `( ]2 t1 K$ z2 A s; A( M
to recolor-turtles {! m4 D. P. `* C. s; S5 r4 k) Y/ d
let max-wealth max [wealth] of turtles2 m# ~" y8 ]% M' ^' L
ask turtles
/ E3 i X) R q3 h+ \ [ ifelse (wealth <= max-wealth / 3)& H3 l6 V( c K' d' X
[ set color red ]
) V; L0 d$ {; p3 d% B [ ifelse (wealth <= (max-wealth * 2 / 3))
! J# ?/ g2 I/ q- t# _7 \' A& u [ set color yellow ]2 t* I/ p, Q- Y- Z$ c
[ set color green ] ] ]
* K9 b7 S" C3 J' ?$ x) W ask turtles [ifelse show-wealth?
! W. L7 z2 k" M; @2 L [ set label wealth ], k: ]& ^4 o' }6 B: G1 K0 g
[ set label "" ]]
1 [7 @1 R; j& v, Bend
4 b/ D2 |" H @+ }% w$ O, T9 n1 ]% R; S/ `) ?% G; G; _8 t- S
to go3 G; H8 `- u- k& I5 y) V+ a
ask turtles) |7 R2 V. ]2 @. b* a, ?: [
[ turn-towards-grain ]
- V# h, ?. u; A1 D& ]2 Q9 J harvest
E, k: n3 q% d+ T ask turtles
- `" ? X6 i4 v0 R [ move-eat-age-die ]
; B* _, S n7 k recolor-turtles
/ p, M& W# R1 ?6 K if ticks mod grain-growth-interval = 0" b- Z0 ^( q3 ?
[ ask patches [ grow-grain ] ]
& b) T( I3 d/ ^: X9 C4 W
4 m8 t$ n2 d( S if ticks mod 11 = 03 o: r E1 J6 S1 ~; d; Q* m
[ask turtles5 D- Y8 O4 Z8 M$ K) _# B
[ redistribution ]]
( D2 T; f4 Z2 m$ d3 c* G w. X if ticks mod 5 = 0
, v& E* @0 E# t& j7 T- z$ d [ask turtles7 d: T3 g. ?/ L
[ visions ]]
, N1 J- h, H( X7 p tick( H" `4 x: a$ G. k: @; ~9 {
update-plots
8 `+ \; `7 N7 ~6 P/ n. K4 cend
; |: g( n- }1 _( [) k8 K* ^ @to visions
1 J, \9 q; F4 p* c9 D set vision vision + 1
& Z. f1 j7 t& n9 Q3 Qend& k8 ?9 m D% s5 i
7 {# z6 k# ^+ h7 {/ y" Y3 n! N* M2 P( j
4 J1 s5 U7 F4 U6 m
to turn-towards-grain
( _" ~( l+ E l6 m- ]6 V1 h set heading 0& {3 r2 q1 g$ }7 B# Q+ `
let best-direction 0+ q; L6 }# W+ D
let best-amount grain-ahead
: u) T/ S0 z. k) Y! R set heading 90; |* C% K& l4 j' [4 A
if (grain-ahead > best-amount); b8 _" O4 I4 g8 e+ e
[ set best-direction 90
L, q+ }5 Y( v( N0 \. ]/ x/ t set best-amount grain-ahead ]
" {- L5 r+ p' P& o set heading 180
) L3 i# l" L! b1 z f" v! w if (grain-ahead > best-amount)) X! ]$ E A+ \% e+ F/ a
[ set best-direction 180 }3 l; k2 r2 ^* F
set best-amount grain-ahead ]
& q# S" u5 V" h0 U. L set heading 270- [2 f$ V& c2 s9 y- J4 h
if (grain-ahead > best-amount)
# F' H. ~1 Q1 W [ set best-direction 270
# U( J* Z) `7 X& O5 H; w# b set best-amount grain-ahead ]
2 ]! [+ J4 a% U6 w2 u set heading best-direction
8 U- \4 n4 L$ k5 g2 O; zend H3 |: q$ @" j, p( D) b
1 w& o c; E0 \5 p( z+ h( n D6 i* Z. N* b
to-report grain-ahead
; R; r5 l3 V& K4 s' g* j let total 0
& c& r& o# g6 A8 Z3 l: W let how-far 1
q' e+ f) i6 {/ Y$ q repeat vision# t! }# S/ Y+ W2 w/ f
[ set total total + [grain-here] of patch-ahead how-far0 U' w* h; `0 I% ?- @4 p( H# K
set how-far how-far + 1 ]3 y, L# W) J8 i E1 u
report total' e2 v+ A ?, _, [0 h& A
end
) [" c6 Q; v, ^ m6 M% v
?' ]+ q; ~( n6 T, h* Q" p7 vto grow-grain 3 f$ n! D/ g# [% F4 w1 ^1 m9 B
if (grain-here < max-grain-here)- V# D9 w! R7 J0 A$ S, _) j2 v
[ set grain-here grain-here + num-grain-grown9 H( _7 v2 Y2 h5 E
if (grain-here > max-grain-here)
9 L9 q# f6 q0 o% O7 W2 B3 G8 X [ set grain-here max-grain-here ]
5 b; c. V; C. r& Y4 Z! z7 n recolor-patch ]
" C# J, X; Y: \) Q- E" C9 oend
% X6 \( R$ e4 l3 S" ?) C3 rto harvest8 P1 z) n5 x# q) M( ~
ask turtles
j+ Q. t# z( E6 m1 _ [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]4 f! y9 n) O0 P9 K Y
ask turtles( s* k1 D0 e; f
[ set grain-here 02 V2 z0 o2 ?! J& G" Z& N3 q; E
recolor-patch ]- i+ U/ w# R3 K! T
/ T% M0 N3 a0 ^0 r/ Q8 i; j2 I9 Send
% i- e) c' ]0 y7 i9 u+ s8 I2 b+ b0 p6 [ ?' z' }; f
to move-eat-age-die
% c8 a% v% e/ a. y$ Q fd 1
% U( ~6 f$ _4 F" v4 m set wealth (wealth - metabolism)9 u) |( n2 r4 \
set age (age + 1)
8 p& G1 v1 D' q' F! f9 K# H& p if (age >= life-expectancy)
1 A- ]+ M `& q# t5 }" L [ set-initial-turtle-vars-age ]7 U) I; c }- w% S' U+ m2 {7 }
if (wealth < 0)" ~( w) I1 X* t. o+ {4 X9 R
[ set-initial-turtle-vars-wealth ]
6 y0 _" Y4 K0 u V) c4 n, V" k ! @ O( O- j) `: H" x e
end
3 N% \ t7 L8 Q* m. ]: s" L( j
# r- Q0 Z" w9 c3 W
* t0 ^0 |/ ~# Kto setup-plots' i. l6 i) t2 f. j$ I4 s" r* q
set-current-plot "Class Plot"3 R, O6 b5 G& a
set-plot-y-range 0 num-people+ ]1 v1 ?8 g- `' \2 H& r( b/ o( L
set-current-plot "Class Histogram"
% ^; \. g' K$ p$ h0 ~ set-plot-y-range 0 num-people
/ H8 f* O5 y$ E. tend% W2 j6 u9 v9 ?! `! m8 \
/ Z. w; `2 T f" Uto update-plots) V. K) i% [9 J0 V5 N8 t" u+ T( o
update-class-plot
# D+ x) t% k& S$ d" e$ d2 W7 ? update-class-histogram# h/ R' V! B. |( y( ]
update-lorenz-and-gini-plots3 j& w4 _7 D( p* a- E6 U
end
* C% m% J3 J7 z; A- O
6 ^: X7 k) f0 m! h. a" Ato update-class-plot. F* r* b& M% J5 S( c: }
set-current-plot "Class Plot"- W3 }3 |# d6 n D) \/ e9 l
set-current-plot-pen "low"
7 i) E9 T5 U N( s; a% _) O8 ^ plot count turtles with [color = red]
8 N# s( R4 J' z# F1 Q, M set-current-plot-pen "mid"$ l0 J6 Q, r3 V# y. `
plot count turtles with [color = yellow]
* I) w: a! n+ |1 ^, G set-current-plot-pen "up"( g9 h3 O8 c; u% s
plot count turtles with [color = green]! m3 C6 r& Y* H& ]% @4 ^ d
end- g: ?# ^1 m0 D; S
* @! i4 h. j" X3 w3 l5 V7 o6 |9 q
to update-class-histogram
. X$ x0 G$ n$ Z _ o set-current-plot "Class Histogram"
" C) J* [, H! x$ ?: h plot-pen-reset
& ~- V$ H0 D# Q `+ P set-plot-pen-color red
3 H# y2 I/ M5 B# P5 m& n) T o! t. [6 p x plot count turtles with [color = red]- \$ U% }* }7 ~
set-plot-pen-color yellow3 b$ N( H( G0 `# b' H% I2 r
plot count turtles with [color = yellow] \8 [" z1 z2 _/ y
set-plot-pen-color green! k1 l. B$ T& A' a2 c2 o6 e
plot count turtles with [color = green]
3 }6 \- y6 C3 v/ A! Pend
+ w# y2 i7 G$ B5 R% v: Z7 V* `1 uto update-lorenz-and-gini-plots. L$ D/ H( y6 H8 K( T, W
set-current-plot "Lorenz Curve"
0 i+ e- _# J/ a8 w. u clear-plot: w6 a: v5 D% k! k4 a
9 A1 Y! [; M9 Y: `6 s6 v" A2 [/ Q
set-current-plot-pen "equal"
9 b* q) m0 O5 {1 Z; I. X plot 0* e- D$ n+ a+ v, x8 r2 c4 N
plot 100( ?6 P+ M% T0 M6 _2 Z7 G1 D
+ u. _7 \6 j4 B8 P3 q; i" Q1 e D: P9 h set-current-plot-pen "lorenz"( D" g7 J: o. B* K) q
set-plot-pen-interval 100 / num-people
?& M X0 N2 H5 B4 O, r plot 0' u9 `$ p0 C2 T! Q% i4 {) H! f
% U+ h5 t# P' b let sorted-wealths sort [wealth] of turtles
+ \2 l |" o3 }# s let total-wealth sum sorted-wealths
& `! |+ S, Z( D; L9 S( X2 y let wealth-sum-so-far 0
( ^2 m& h) w3 r: @2 q) z% K4 F let index 0
4 q4 Y7 O4 V6 t0 b) C let gini-index-reserve 0
/ J) J; K- a. ^; o5 i9 Q, E& I
" J# ]2 |* |1 E4 v, H: X repeat num-people [( a7 k7 i- A* z& R+ G
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)5 f& \' Q8 f1 M2 G" B; z" Q) e
plot (wealth-sum-so-far / total-wealth) * 100
/ e$ M3 w, T$ [) p7 Q set index (index + 1). [7 _8 M3 w" X. f' S$ V1 N0 {/ s
set gini-index-reserve
5 C, j7 a5 L* @, M2 [* z- o gini-index-reserve +
( ^, x4 ? u% t (index / num-people) -
1 r. t; s3 ]7 A! s" M/ ` M: j! o (wealth-sum-so-far / total-wealth)' J: ]3 X" @% M4 H$ h
]
D1 f- |: e& t3 g, E9 N) B
. N, B5 S4 Z' q) A# _ set-current-plot "Gini-Index v. Time"% |1 M! M$ e1 O4 s& N: o0 o+ \
plot (gini-index-reserve / num-people) / area-of-equality-triangle2 V6 Q( P' J T' R, C: r
end( i) x0 a, m) Y# ]: B/ q- h! G" R3 n
to-report area-of-equality-triangle! b. Y2 K1 e& Y, _
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
+ x3 B! I* K+ M5 c2 wend |