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
: w) s5 B6 m/ i7 X, x2 Y7 dglobals' c1 v; z$ {4 V* W& m2 e6 g$ ~* }+ X
[
4 V9 z; j1 n9 O* y/ n- v2 D5 K max-grain ( o+ A, `* k$ E0 @" h; j! K4 ?( u
5 I: ^$ @6 Z: _; n) U* Z
]
. Z9 w" u, y* q/ u( | j- A
6 S9 h d% N) q' ^: y- D5 _, `patches-own
9 l8 ^! Q0 K A3 a, W[
+ l. w7 ?1 ]/ a* a grain-here : e$ c8 g& c$ F6 j4 `0 R. G2 V% @4 `
max-grain-here
! b9 P& O3 N8 i! u$ H]2 j7 _, s! b" A/ N; x$ d1 L. ?
8 ^# q- ?" U8 x6 Nturtles-own4 {1 ~( A' L4 h, T
[
8 M+ e4 `" A! I* A! a+ j age & R8 F* A! G# u3 `2 `
wealth 7 E% }- m) _' g5 c: u8 ^+ c" `% L' q
life-expectancy & a% z8 l8 C: }% }
metabolism
4 w) i' F5 u; X( d vision5 y; S& G1 l8 i7 f2 A, i" L* t
inherited 7 E+ k* p7 t) j$ B( `
] d. j, e, b6 x6 E
! H/ `2 ]8 N& ]) Q# h% [: W4 l
" K( z4 t& g# y" ~6 n$ @to setup% z6 O4 W; m o7 \6 h
ca+ B8 v% K: R* C' h: \6 T5 P
set max-grain 50& G& A2 B$ {/ _& O
setup-patches4 Z+ U7 B( `1 R) U g2 _& R; b
setup-turtles
; O" l" T. O+ \1 @- N# Q* L* N setup-plots
+ [* I3 {# T- R. H4 ? update-plots
3 ]9 g9 \# D3 \end$ p" L1 g7 d V2 _4 ]
to setup-patches4 p+ Y6 N6 j3 N3 |
ask patches# H: W. N; a6 r+ y7 I
[ set max-grain-here 0
. n* a" X$ [2 a1 u3 n) h7 [ if (random-float 100.0) <= percent-best-land: d8 s7 t0 k7 C, N2 J
[ set max-grain-here max-grain
" P% ]( G# E- ^: [- D- c4 Q set grain-here max-grain-here ] ]
0 ~% }4 Q$ X+ r" H! g3 u& B repeat 5
7 t* |5 h# Z5 E+ J [ ask patches with [max-grain-here != 0]8 ^" u9 m% ?$ h5 O. |) W: [ T- `5 ]
[ set grain-here max-grain-here ]
, m$ J$ |3 h Q0 G2 h diffuse grain-here 0.5 ]9 c% \- k" k4 f$ d, B" \1 B9 N0 e
repeat 10
8 |$ w4 @' |0 Z7 ` [ diffuse grain-here 0.5]
. l m6 x. U2 F, R ask patches; X& x4 \3 y9 E3 t
[ set grain-here floor grain-here 7 C2 i6 r- w$ h& J
set max-grain-here grain-here 4 W3 S9 n- V8 _
recolor-patch ]
, F( k4 g, D4 {0 M7 M6 Eend
( B/ L, Y0 `; eto recolor-patch # b/ Z7 S8 g5 [3 Z: A
set pcolor scale-color sky grain-here 0 max-grain% Z7 ]# m& I5 M! G' f
end4 A' G/ w0 S+ @
to setup-turtles: P5 y' E, j/ j5 r, @7 N4 R' S
set-default-shape turtles "person": X3 e- u' S" m% S
crt num-people N0 N- S) h* i3 |
[ move-to one-of patches 4 K9 j' R! h% B1 C4 x& V
set size 1.5
) O1 E x" X8 E O J0 n5 j set-initial-turtle-vars-age
; R; x( L& Y) v9 X+ m0 A3 Z set-initial-turtle-vars-wealth1 Z/ o0 w P& g# E3 Y; s" B9 E
set age random life-expectancy ]/ z5 M- s' Y2 B4 g5 \
recolor-turtles
4 ^' V' z7 z4 J1 N) ?/ }2 c% Tend
" f0 I4 t2 f: j2 h+ N" v' h
l, F! U& E/ L, eto set-initial-turtle-vars-age
1 y% k/ S0 o2 X$ R- S let max-wealth max [wealth] of turtles
! u6 Y$ Z3 H; n/ y
/ o3 r9 t! L; K0 A3 W) C0 c ifelse (wealth <= max-wealth / 3)' a6 R* Y2 D/ P$ i
[ set color red
* Y1 Y$ W* Z* g8 F7 H set age 0. L: K8 X: X: S0 U9 o& C
face one-of neighbors4
+ h0 n4 I2 d) P% d8 p& L- H9 M set life-expectancy life-expectancy-min +. {: H9 ~+ I: e
random life-expectancy-max $ Z9 `! }: ~, M
set metabolism random 1 + metabolism-low: j1 w' w; r' D
set wealth metabolism + random 30* D( @/ p9 h( ?- o: e( D- J: v
set vision 1 + random max-vision3 z' X: L/ V1 Y. l
set wealth wealth + Wealth-inherited-low ]
9 Q. D" E T5 [% m [ ifelse (wealth <= (max-wealth * 2 / 3))9 b* {+ Y9 u) i. [2 f2 g
[ set color yellow
( Z- |( k5 [$ @" i! l1 e set age 0
. c5 f* U! c) i9 D+ }, y5 p0 J face one-of neighbors4 * T, T3 x1 F: a: V3 \
set life-expectancy life-expectancy-min +
5 J: o3 \6 J, w- r8 } random life-expectancy-max + 1
: C8 l: O; S! k! E set metabolism 1 + random metabolism-mid
5 L+ _: Y: U& J5 }; W: t7 G2 \ set wealth metabolism + random 30
B/ g$ L5 V7 g% G1 k5 B) u set vision 3 + random max-vision. ~4 J( `2 R. ^9 Y i& n
set wealth wealth + Wealth-inherited-mid]( C6 @) T; v1 w( ]
[ set color green ( S8 n7 v7 F; u
set age 0) {3 O% R' f6 X. a& ~, _$ E9 T0 i
face one-of neighbors4
; a, {; c& w" L4 D: j2 M# u set life-expectancy life-expectancy-min +/ F* E) ?9 q3 L1 g7 Q3 |
random life-expectancy-max + 24 p+ w# Q4 O! B1 M6 n
set metabolism 2 + random metabolism-up& b. V" G8 [' m* q( s( f
set wealth metabolism + random 30
: I2 Z5 |4 {. \, E# ?2 }0 j% @ set vision 3 + random max-vision+ y% b$ ?3 j6 I: a q6 G" h
set wealth wealth + Wealth-inherited-up ] ] 1 D7 d3 C6 v1 g8 Q: ]3 [
$ u x; ~2 f" h; W' c9 M! nend
n* a# Q' y* |1 q. f3 Z8 Nto set-initial-turtle-vars-wealth1 o1 U$ p2 E% W: N6 y; T* c, }2 X
let max-wealth max [wealth] of turtles' @7 _+ z7 e+ e4 t! b& ^+ ?2 E
set age 03 e$ O9 j" O* E" l3 {" ~6 |" m
face one-of neighbors4
0 b# k8 [! x- r, v9 {9 p' a set life-expectancy life-expectancy-min +
$ q" @0 N4 ?' `9 S: m( S random life-expectancy-max
3 k2 M W8 L m N0 M" I set metabolism 1 + random metabolism-up# ]0 Q1 V7 d" _; B2 \
set wealth metabolism + random 30
" t X" K8 Q @3 r2 X, Z" ] set vision 1 + random max-vision
8 V4 X3 G4 {) h' f) dend
6 W( h7 z3 s# G! |6 I tto redistribution
6 d0 D/ p9 o' _. G, O, dlet max-wealth max [wealth] of turtles) \7 N* b5 D2 r7 [# Y) D
let min-wealth min [wealth] of turtles
' c$ [- H2 h1 z9 R3 P: Y9 S, cif (wealth <= max-wealth / 3)
9 e9 T0 r- Q0 _' D! L: m1 [* f: H [set wealth wealth + Low-income-protection ]* E; ? ` o3 V' [( `( a
end
7 |2 k6 s6 W6 R
0 R3 F8 C' c' t; |2 s2 nto recolor-turtles
, A5 Z* M* m% x) {1 ~% ~8 j let max-wealth max [wealth] of turtles
, i" q9 U! ^' s, d/ Q" @. ]4 A ask turtles) g% `2 v# L" C; l. T% ]7 ?5 M/ F
[ ifelse (wealth <= max-wealth / 3)
, Q6 E V" o+ R [ set color red ]' p- {% ?& U& ^8 J/ ]0 H
[ ifelse (wealth <= (max-wealth * 2 / 3))
- _3 q$ V( N) ]; L% v4 M1 g0 K- E4 m- E [ set color yellow ]; o0 ~: M& T/ [4 q Q6 a
[ set color green ] ] ]
0 o% N/ @+ Z5 j7 T( H ?- n ask turtles [ifelse show-wealth?6 {+ U' A- H6 e @% e( U
[ set label wealth ]: X: v9 h' A+ ?; ^ _
[ set label "" ]]
$ f; X8 p9 _' P1 [6 I2 `end
, w* v8 q. w# B9 l$ |* ?- ~4 \7 f L U
to go
6 R# V6 e/ E; W% B$ d ask turtles
! D1 _$ n5 M9 W6 p; Q) `" k' ^ [ turn-towards-grain ] + {- U! o4 g# m5 X6 T
harvest9 _8 I' O6 Q! \. e& M: x. J: U
ask turtles) y. C% j- K9 [" u( I5 x2 J8 {
[ move-eat-age-die ]
; @8 S' N5 B+ u- h7 \ recolor-turtles
+ W5 P. g, [/ u7 r if ticks mod grain-growth-interval = 0$ D0 R7 w, y- ?) V
[ ask patches [ grow-grain ] ]7 ? |3 @' m; x
$ b- u; D- W9 K; i if ticks mod 11 = 0
) o( {" G: G( n3 G7 u7 j7 \4 q [ask turtles' C! x1 h3 S2 Z9 V
[ redistribution ]]
& G9 L: _7 p2 k' T3 h if ticks mod 5 = 02 ^% x. x: P! j3 a, g+ n0 r
[ask turtles
5 n7 |5 A2 ]) H; S [ visions ]]# {5 H" Q, ~& S4 K% Z0 E& _& D
tick
. h* \) O! U/ X* V$ H update-plots
" ^) t/ \9 t5 E% ]# d& t- yend6 e) [ u4 x# j) A# X, Q: D4 W* I
to visions9 M6 d8 N. L! I$ i' T) |
set vision vision + 1
: Y/ D: z$ Y+ S- x9 U u! Send
* i9 _: j7 G }3 K+ h" }- w: @/ f
c: I7 a: `: J9 q$ p1 F6 {+ F% b9 u& ^
; @7 F; o1 N2 c- N1 J0 v9 Y3 vto turn-towards-grain
# d9 D+ O* N5 Z+ ?0 @8 G set heading 09 U# s1 {2 k5 Z/ Q; r& c
let best-direction 0% V& ^: v: E7 y1 b/ Z, j( u9 A% W
let best-amount grain-ahead
0 K8 J9 O8 N9 T set heading 90% u( @8 @% S- ^1 k% g- O- k2 z
if (grain-ahead > best-amount)0 m+ L U! u {% }) u
[ set best-direction 90
# v: y( ^: j9 ]2 i- k set best-amount grain-ahead ]8 D$ E+ |2 c; P3 b4 u
set heading 180
7 S/ Q9 Z! o. O: W* Z( ~9 I$ e if (grain-ahead > best-amount). u7 a4 k: u" A- @7 }+ v) }* e
[ set best-direction 180
5 G \3 L" j3 H) L' H set best-amount grain-ahead ]- B6 _8 b! L' J1 }% i! y
set heading 270
( h- X ]' a7 f' z1 l! P if (grain-ahead > best-amount)- k8 o: W/ R7 }/ N. ]/ G% ~
[ set best-direction 270
' F8 N: `) Y* n8 @+ t" O6 v1 l' ] set best-amount grain-ahead ]* s# K7 O) w% w7 ~* D( g
set heading best-direction: N) Y( c. L$ m7 d# |( u( D% M- C
end/ b5 F: C. ^( T6 S; k
* ~7 X% R0 e. v" z% [( N) w3 L
6 z; L3 }# i$ t5 v8 T0 F+ @to-report grain-ahead ' w O- O" _' L
let total 0
$ ^1 A( y0 ~4 K. \ let how-far 1
7 m, S. }% {& X% i7 Q repeat vision
; _1 f8 y+ o$ P. j$ N: b" b [ set total total + [grain-here] of patch-ahead how-far8 d1 h, X. f4 C& s$ m& X
set how-far how-far + 1 ]; g1 R/ Y$ m% |* k
report total5 |0 |0 @7 D1 k {/ e/ c2 G
end+ p' ?; j; |6 R$ v
8 d. S. e: ~6 A6 Z# H( I
to grow-grain
9 l* R6 \5 f6 g4 \, L- K1 l if (grain-here < max-grain-here)6 l) D1 B; G0 @/ s" t
[ set grain-here grain-here + num-grain-grown
8 U3 X. c9 w" E/ {0 h if (grain-here > max-grain-here)
& R% o9 y' R# a" c$ V7 ?# P [ set grain-here max-grain-here ]
3 R9 T/ _) Z. c+ o recolor-patch ]' @; v3 k- u" q( U/ G' |
end
" _: P" s5 f% \/ \$ C% d8 y9 j* hto harvest2 w$ v! s y1 j) h
ask turtles
4 n, N0 R0 S# z5 t: l [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]" U1 `) B4 f7 D; h5 p+ J5 g
ask turtles
0 c3 F1 d: r. b2 h6 ^ [ set grain-here 0
( E! z$ h: D$ H; P recolor-patch ] w9 r8 ^/ L8 f
w5 I+ Z u! [: d/ Send
4 ^+ B7 G; d% Q5 x. d, j9 o& a0 @ M2 V3 B
to move-eat-age-die
6 n& o8 m m; Y) a fd 18 o; Q8 O' L9 Z( M
set wealth (wealth - metabolism)# V2 Y) @' E1 h
set age (age + 1)2 u1 i2 ?8 z7 o1 N
if (age >= life-expectancy)
) N [, k4 L/ K# B0 { [ set-initial-turtle-vars-age ]
! B/ R" l0 R3 G$ w- q8 r$ Q* v if (wealth < 0)" q! Q1 l9 l, t) P9 F
[ set-initial-turtle-vars-wealth ]1 [' b$ E2 Y7 u4 H$ w# n
) m% `( V5 r$ c" I0 w- U4 bend6 I/ ~; ~* N+ t z* l
& I" h- _7 h" }$ w& F7 |2 f9 L% k3 O1 s* j5 ^
to setup-plots, H+ y" ?: o% A0 \9 G, G: D
set-current-plot "Class Plot"" q6 M% j) I" v' y
set-plot-y-range 0 num-people c: O3 Q4 h* E3 {* h
set-current-plot "Class Histogram"
( e6 y8 ^) t P V8 F5 `3 x( @; ~ set-plot-y-range 0 num-people
+ N; P( T$ ~8 ^end% Q. r5 N+ q" K- b
/ }% k5 E! o* M+ a$ }6 Nto update-plots! q8 |( L9 ^* P, c
update-class-plot
% Z3 U9 i+ l; v, H* H- }# r7 P update-class-histogram$ l, L4 e, O5 e6 T$ H
update-lorenz-and-gini-plots
Q$ L& i& @/ X( G: L" ?7 `end4 P: A5 V: }9 u/ {4 u' p
0 m* f; U# y0 [( }( u$ ?. E( t
to update-class-plot% `: ^0 X. {/ W+ g* ~, s9 m" b
set-current-plot "Class Plot"
, O6 @3 E; F1 T set-current-plot-pen "low"
/ m; o; ?* w- i, k% x0 l/ [9 P plot count turtles with [color = red]
) s5 M9 \2 t, a0 O set-current-plot-pen "mid"
& ~' M2 {5 n# J plot count turtles with [color = yellow]
# `/ _5 X: m4 |2 G* P set-current-plot-pen "up"
9 f; Z: L: S: z plot count turtles with [color = green]9 P& U( i; \$ F) f4 D
end
9 x) D/ z* G" \5 I y7 }; L+ Z5 {2 w9 i2 U
to update-class-histogram" t. P# f# x% O
set-current-plot "Class Histogram"
& K- {( c0 G9 x( b l `$ H plot-pen-reset, V: s' q* y8 L' N
set-plot-pen-color red I: O* a, _4 u! R6 l8 x3 i
plot count turtles with [color = red]
9 S! N6 q* p8 U2 C4 T4 C set-plot-pen-color yellow
5 \: ?. A% r, `' {4 N- s( g4 E- E plot count turtles with [color = yellow]
( n5 a5 o% u5 x. d+ i set-plot-pen-color green z/ M, B6 g& i/ D. M2 F+ s
plot count turtles with [color = green]: r. D% q6 N9 A0 @
end
& [, i4 ^+ u q; [+ nto update-lorenz-and-gini-plots. r0 m( a! i" t
set-current-plot "Lorenz Curve"- k# X7 I A! k. v5 G* L
clear-plot0 c8 h* _: t4 }2 [7 C! y
/ u2 `, O! F/ p set-current-plot-pen "equal"
- S1 v% N& k( s5 v6 ^- q4 i plot 0- F+ J% y4 `3 U; u9 n1 E- A
plot 100
3 s; L2 m8 s( G+ M' t$ y7 @5 t5 H0 ~9 X( d2 F H
set-current-plot-pen "lorenz"4 [1 L4 H% w4 H" w& k$ n" \1 n
set-plot-pen-interval 100 / num-people
) d% ]8 y) X0 H2 G* v1 ~: z9 A. a plot 0
) _; s$ \7 ~* d. E0 V4 n
$ ^( w8 v$ | p8 Y2 c- ^: _ let sorted-wealths sort [wealth] of turtles+ H! v& D0 m5 m: w2 R
let total-wealth sum sorted-wealths& a. l- a, z& _" w2 H F4 k2 B
let wealth-sum-so-far 05 V5 b0 g* W6 Y% W' @
let index 0
2 R- ], {6 J- k let gini-index-reserve 0# f/ X; ?/ g( m8 k" v
* |7 d6 N4 D+ z' S" _* Z+ { repeat num-people [) p0 M8 R6 f7 B( n( U3 O- v% E" L
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)$ X# w- V& F1 B8 [. C
plot (wealth-sum-so-far / total-wealth) * 100
2 q) r; A2 n* d- b" b% S set index (index + 1). L/ [3 X0 o" i, d5 P
set gini-index-reserve( g- c1 U) C; S) m
gini-index-reserve +
[' [& e7 o6 h (index / num-people) -
4 }( M! }/ p' M. R (wealth-sum-so-far / total-wealth)
( K7 w( \2 r+ ?- q! f9 I) R8 {. q ]
& ^" Q, z6 L& D7 X
+ k2 r9 j- d/ z7 C$ p" B8 w' X/ y set-current-plot "Gini-Index v. Time"% K* d0 @# \9 M( M3 r3 z+ L# T
plot (gini-index-reserve / num-people) / area-of-equality-triangle
4 E7 D* O; \) d; n& F$ Iend
7 f+ m; _3 X, \/ E4 ?& Ito-report area-of-equality-triangle+ S5 O2 ?; `2 Y" o4 E Y
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)2 C# }, B' B7 K' L/ E# _
end |