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0 z. o/ L1 v2 |# `+ z4 V1 g4 |0 s
globals1 N0 I) i0 v. P* V# a' i; u/ j$ ]
[
- J3 [' I {$ x7 p0 z8 g4 u max-grain 2 |4 M3 S; ?' T: {4 q. N- [
* E, \9 q8 C( H]) r9 U s: d" Y8 n. k% F# D5 Y( c
' J; \% @ k; Y, y1 Z2 C3 E. ~patches-own
% z8 u8 w- Y( X[
; w, K* b+ f$ J grain-here - ^0 H8 d! E& u. i9 V
max-grain-here ; \/ }/ b, m8 C: }
]& _6 b& t2 H, C
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turtles-own6 G" k9 @2 _( x
[6 w, e3 w/ q6 E, K
age
! H8 P0 J. R4 V" b' l/ ^ wealth % p8 T; i2 j5 A, Z
life-expectancy " m! k$ ~7 p, E- n2 [
metabolism . s7 Y" k: ^4 Q, ?0 q& `0 y
vision
. j1 C* G) t. v( A( ^ inherited
* @+ g( |; ^9 k]
& h! n+ f* s3 i" Q, n: H3 ^" R; ^$ L/ E, ^- H1 m5 S3 Q# S% M4 L, D7 ?4 D9 b
$ @$ J2 N8 w( w9 X) o
to setup( _9 r: n- m7 P& Q1 g% V( T
ca% w; S4 T1 u* y' U; P1 h
set max-grain 50
$ q5 x3 m# `5 y setup-patches6 r& r( k4 u2 E2 x: R& Y5 z
setup-turtles
& K9 F# G2 U0 c! g! u$ e setup-plots
) d) O) k+ l1 ^ update-plots2 f# m: D1 h6 z. e t! o
end6 t; \# A* W5 G% k7 V
to setup-patches/ R5 Z, f3 p0 r; y) I. q
ask patches
9 y, T: a- p+ x; i [ set max-grain-here 0
! y0 ~" L6 W7 q1 F/ J& E T if (random-float 100.0) <= percent-best-land
$ c, X. z6 R& d3 F. | [ set max-grain-here max-grain3 S. J* d$ K; ?* U( [
set grain-here max-grain-here ] ]& ?: E" M: ]9 F3 }
repeat 5( s9 Z& y/ T Y4 J' m& F- C( f
[ ask patches with [max-grain-here != 0] ~7 A$ i% j- `2 p' a
[ set grain-here max-grain-here ]
2 h. E& y' {) V9 _* ] diffuse grain-here 0.5 ]' r( Y2 p: Z3 |. H- e) O) |) o6 q
repeat 108 N+ }4 ]& J9 U
[ diffuse grain-here 0.5] " Q0 ]. l3 h, @
ask patches* g$ q1 k6 d( j' s3 w# D
[ set grain-here floor grain-here 1 y/ [+ \& \9 t' T$ [; T$ }, U
set max-grain-here grain-here 1 Z: r% |, R3 d; }
recolor-patch ]. c/ E: D6 q- e9 _$ L Y! T
end1 L; Z3 j7 K! J( Y1 a C9 O
to recolor-patch & V4 _+ K3 b! K2 R
set pcolor scale-color sky grain-here 0 max-grain
) d4 O$ b" `2 L# Fend
4 k- E f9 O8 `& m* _' k3 o/ rto setup-turtles! @: w- l# Z9 }% O7 k, ]
set-default-shape turtles "person"* P" ]9 p6 b" O% r
crt num-people0 ?- K* M5 `" p) H0 e; K
[ move-to one-of patches 9 p4 ]8 N9 J9 A3 [
set size 1.5
6 W4 x5 G; s/ O9 j4 {( f1 C set-initial-turtle-vars-age
8 t! b5 V1 k& _6 A, A0 y: t set-initial-turtle-vars-wealth5 m6 q4 l k, `( n
set age random life-expectancy ]
; ^$ b' T. r2 K3 h2 B7 k. l& O recolor-turtles
; |; ~- X+ g: \; E0 Y0 m( a3 u3 G$ mend
3 t; d3 E8 ^6 X5 N
4 W7 ?" d3 u) D ] X- Lto set-initial-turtle-vars-age
- {& d) g& _3 } let max-wealth max [wealth] of turtles
& O9 V! q2 k% |9 j J: @ 2 T* D( Z$ S5 R( L1 a$ h. a
ifelse (wealth <= max-wealth / 3)
8 V4 N+ S0 L9 y( ?/ U& T8 O5 O [ set color red
! o: J8 W+ ^- H* \# K0 _' d! o set age 0& W: M7 a4 X2 G5 K; Z1 V$ x
face one-of neighbors4
`: n! V0 q O) D# [3 u) Z. g% H set life-expectancy life-expectancy-min +
. T& R# R1 D- K: v random life-expectancy-max : u( e: c2 Q" W& s9 r
set metabolism random 1 + metabolism-low
0 R: L8 {) d; Z set wealth metabolism + random 30
+ y3 O! F( c! b6 y8 I" j set vision 1 + random max-vision! O; |5 d1 B$ K8 B
set wealth wealth + Wealth-inherited-low ]! q! y/ z2 O* ]" D8 a9 O4 } }" y
[ ifelse (wealth <= (max-wealth * 2 / 3))
& w- W" ?/ }2 [4 R7 ?; G0 t$ x [ set color yellow
" L# ]* d6 ^! K$ l {6 M set age 0
; I7 T% y/ t9 @1 ]4 ?" I face one-of neighbors4 : L2 U' I! a/ C X
set life-expectancy life-expectancy-min +, r1 f; {4 s3 |& a/ _9 V7 ^% w
random life-expectancy-max + 1
+ w; l L- ]6 ]! ~5 L0 m+ H, S' n set metabolism 1 + random metabolism-mid3 G( M z- f5 X& D& U; a+ y8 v* K4 I
set wealth metabolism + random 30) |8 a0 J5 E( B4 }
set vision 3 + random max-vision% p% m# N' s7 y& p
set wealth wealth + Wealth-inherited-mid]& f0 j6 b- r6 U1 `8 a" u
[ set color green
& x- o% m& u1 b4 _1 h- u% i set age 0- Q+ k+ h$ a2 g3 Z
face one-of neighbors4 # z: f) V6 @ e# v) e8 T) X: o& l
set life-expectancy life-expectancy-min +( F4 ?3 ?2 e2 b j( |8 ?) Z- G
random life-expectancy-max + 2
K' f8 }" M; e) `9 E6 u3 f set metabolism 2 + random metabolism-up! A( E }7 a! r5 c7 {; W8 M5 A
set wealth metabolism + random 30
' M' ?7 |) N7 X set vision 3 + random max-vision
+ M7 O) \9 ~$ a/ ^9 }) Q- Y! Y$ N set wealth wealth + Wealth-inherited-up ] ]
$ D9 \) a7 H4 @+ N. f 0 H6 i! F7 ]. u
end
. k$ C% @6 k+ g. N1 Mto set-initial-turtle-vars-wealth
; P0 `5 D H3 g5 E( z let max-wealth max [wealth] of turtles
7 _0 q# C6 `3 O8 Z9 _ set age 04 D3 f( Q% O% k! G( K2 F
face one-of neighbors4 ' E" g7 ~: p9 V4 J: R
set life-expectancy life-expectancy-min +. S& U3 {# k6 ~9 J* ?
random life-expectancy-max ' [2 `' U4 s6 M- T( e% p
set metabolism 1 + random metabolism-up8 m" b f+ m( e& R
set wealth metabolism + random 30
; ^4 ?+ o( w& L4 E. D. h2 N H set vision 1 + random max-vision
" J' M7 h2 l' ?+ V4 H' j- [- O$ wend, q' |% A, n4 f X* A' Q) D- N
to redistribution
% C2 A6 e" W2 t' F! k8 `let max-wealth max [wealth] of turtles# j3 L4 L3 t" B, P, T1 {% K$ }
let min-wealth min [wealth] of turtles' S0 M' Q: |! g+ W- ~
if (wealth <= max-wealth / 3)7 \+ f. Y. F8 k
[set wealth wealth + Low-income-protection ]& u( ~9 ]. a7 E, v1 V' ]
end
9 O5 x8 N; a7 J( C+ m0 K 0 j3 r, Y6 A+ l! l
to recolor-turtles3 c T* [# q1 Q
let max-wealth max [wealth] of turtles
, s4 i" \, K; F- b! W ask turtles
2 z1 H ]2 p7 T9 R( @; [' ]* d [ ifelse (wealth <= max-wealth / 3)
$ [# G/ z' _. K1 K! O0 t [ set color red ]0 f; _' P/ R5 k+ @% z5 p
[ ifelse (wealth <= (max-wealth * 2 / 3))
! \6 [& A6 |4 e3 z [ set color yellow ]
3 p1 W/ W. Y& O0 B4 P9 S [ set color green ] ] ]
) P: m L8 J! Z3 ?9 v ask turtles [ifelse show-wealth?
$ R7 `" x& E9 M+ Q0 [ [ set label wealth ]
; w; S g. ]( f0 P2 q# u2 }$ t. G [ set label "" ]]0 {2 e3 P4 X$ v* D
end& y/ r2 p8 U+ V& c, F5 i
( z/ ?/ I* n# p- f/ v
to go
$ d9 \; h3 J( U0 } ask turtles/ m- l9 Q9 m9 C/ G# d% C8 @
[ turn-towards-grain ] 4 u6 {. T1 G3 W7 X! d; {
harvest
* e/ S/ j+ ?' d! J- B3 p9 a7 g. V ask turtles
; n/ X6 i/ v5 E9 u [ move-eat-age-die ] E2 v! h: D5 D
recolor-turtles% x% w$ s. @" @1 s
if ticks mod grain-growth-interval = 0
$ B! r$ P; b+ C% H$ g [ ask patches [ grow-grain ] ]
7 ~1 i' f1 a6 K
: x" q" g& x+ P) `* d, \4 p if ticks mod 11 = 0
) [- I. h4 Q& ~$ E" ^( [ [ask turtles# s& p# J- U7 m4 P0 |8 L b
[ redistribution ]]. m9 X k8 n) M" ^
if ticks mod 5 = 0. X1 [: d/ a$ c- r0 s
[ask turtles9 E% S. a$ U9 s/ {- i' T
[ visions ]]
. Q. r( R1 F! [8 y: A( z. M tick
5 Y' [; Q8 R }- o4 Y0 C8 C update-plots$ W, J6 z2 F9 M( l1 q* e1 y
end
" h0 |5 u s. w+ K3 s) oto visions
4 {* a( }5 P+ j/ { a1 R% } set vision vision + 1 & ]( J* Y, @4 a' \! A a0 A7 e
end
2 q9 a5 o& y" y* G7 [1 n; g* S+ r5 e3 S. |
. D2 [9 F, [" w% ]! b
U9 i2 y# ?6 e- P% m7 {) Pto turn-towards-grain
( X2 w; M$ ?1 `! |+ \: q7 i set heading 0- Q: z7 I: [; O& G" J: h
let best-direction 04 v% ~) W5 H, o
let best-amount grain-ahead
* S$ I: r$ \# H! @" z set heading 90# J- p3 L& ?* `$ K0 W2 c2 r* p* G1 s
if (grain-ahead > best-amount)
7 s& v8 L6 [" K! Z [ set best-direction 90# N2 @" l, |! B8 Y
set best-amount grain-ahead ]
* N+ ~8 t# B2 w. K- \! K' U5 A- U set heading 180: L D9 t6 o) T- S6 Q( N2 Y1 F, V
if (grain-ahead > best-amount)
8 X, O' E8 {$ K6 @& A [1 b" y: n0 r* D [ set best-direction 180: O- S+ P4 ], V U k4 N# u+ r: U0 _
set best-amount grain-ahead ]
& V" }# ^ F6 I! [0 i set heading 270 P* G5 U/ f( R v
if (grain-ahead > best-amount)1 q+ O3 ^1 y) n$ R2 |0 \
[ set best-direction 2701 E" B0 k/ V# V% a
set best-amount grain-ahead ]% E5 K/ r2 `. H
set heading best-direction
- s; C" \& a ?" z: S3 B0 }: iend: E8 I$ R6 Z( V, X) s) o) o
; j# ~) \8 y& N. F: Y, u/ \
X$ N- j* B( E5 Fto-report grain-ahead
; E$ D3 c7 b) o L; P let total 0/ \# [7 b% e; j7 { C3 v+ K! T
let how-far 18 z+ x) ~1 e6 N" M
repeat vision5 m, Q' j. A0 X/ R, C" x: o; u: l& D
[ set total total + [grain-here] of patch-ahead how-far& N+ t+ Q& F2 ?$ D: N- c
set how-far how-far + 1 ]
: X. k3 e/ x( U) P+ _3 g b report total+ V+ a7 K0 l, r! N R1 q
end
6 L% Z" Z6 t$ M8 u2 U; u
# k( E; v- V6 \3 C7 Bto grow-grain . s, h; o# X+ t! Y5 u: t. J. s4 t
if (grain-here < max-grain-here)' R# }$ g/ [# `2 A
[ set grain-here grain-here + num-grain-grown
" l" j$ D& ~- X% Q2 \* \8 q9 k if (grain-here > max-grain-here)
( o1 c, ~% H" m, C, p2 _2 q8 M [ set grain-here max-grain-here ], Q6 p% {8 ~% `
recolor-patch ]
+ d" O0 V- o4 j1 ^ i$ H1 Rend
. g- }3 Z- _/ z) uto harvest9 j* b8 Z- y b3 u
ask turtles
& K3 K/ V9 n {9 O- K9 u* c [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
) E. ]6 D5 |3 c+ I ask turtles/ V. j& J. e: }* F" I. Y, Z
[ set grain-here 0
0 M1 [( Z' W( H recolor-patch ]
- v8 R" n: ?/ E- e# p5 g6 x$ D8 e ( j. H& }9 o- |$ q7 B4 V$ Y7 w
end
2 c3 l" s8 T" ]- S V- M6 w" y
" u7 I2 {3 @+ {6 E" Pto move-eat-age-die
5 @0 a! K( }" \2 J fd 1
7 u3 ~8 K, U4 A2 @6 r8 U4 b set wealth (wealth - metabolism)2 u9 O8 o) u# n! ~ {, g& x& x
set age (age + 1)9 _- D# W' K% D
if (age >= life-expectancy)* K! _/ I: z: R
[ set-initial-turtle-vars-age ]+ {% e/ V8 }. O, t' v. b
if (wealth < 0)4 L5 g1 r. T% _' K8 y
[ set-initial-turtle-vars-wealth ]
( E/ j+ h3 ^' C! M) f
. K- o: O. p+ K, n" }end
) ]0 G8 `. {0 y8 N1 q, Q- h
0 D4 F( Y( D& g( A& j/ I; P/ \4 s2 Z' {$ `9 q
to setup-plots0 t. z9 c: u9 y4 G; ?3 P) E, s
set-current-plot "Class Plot") c) {% h2 b0 K f
set-plot-y-range 0 num-people
6 [& R) W5 _" l$ p }$ P set-current-plot "Class Histogram"
3 y- }5 V1 S6 z1 l, @ set-plot-y-range 0 num-people
: |, ~5 Y/ `( n8 }% R2 Kend: R. _5 V6 e8 Z; E( g/ d5 h
/ V! r: C" F1 T/ M+ b' W3 @7 lto update-plots( g9 O2 `1 w/ p9 H6 C1 p3 ?9 J+ h
update-class-plot! Z! ^. @/ X {
update-class-histogram ^5 C% Z, J4 K/ {& y ^" a9 r% A5 @2 |
update-lorenz-and-gini-plots" C: I9 K* `" c
end# g8 [7 ]# `1 O% L0 q* l" B$ z
1 ]. P; _5 w2 \( J3 l# xto update-class-plot
5 ^* H v) {" g: j set-current-plot "Class Plot"$ x- T1 V; v9 O5 U4 e/ R
set-current-plot-pen "low"
+ M" _* j& Q F9 q4 Y plot count turtles with [color = red]
# A: c/ _! F: {% c, o! g8 j set-current-plot-pen "mid"! {- G' `9 u$ s/ V$ L+ V! j- F6 T
plot count turtles with [color = yellow]* r' x k8 V/ ^9 q2 \" l
set-current-plot-pen "up"
9 k9 n4 V6 q5 ?: [( [ plot count turtles with [color = green]9 Z. K) s% {4 t8 i1 J8 n/ \ o( D
end3 P/ z5 K; {) s
6 S& _( {% s; C, R* `
to update-class-histogram
' y3 X, K) a, b1 [+ { set-current-plot "Class Histogram"
( t8 _ E" {* c9 \5 v plot-pen-reset
1 F* ]! g% w, R }7 R; W$ G; ]' u set-plot-pen-color red% N4 C; C" |! V
plot count turtles with [color = red]7 q% ]) _4 \6 K/ ^' K: ?% |
set-plot-pen-color yellow+ l0 o: T- s8 y1 x- C7 ^! ~
plot count turtles with [color = yellow]
# e4 y& s4 R) K$ y; {+ s) D set-plot-pen-color green
" ?2 j0 Q8 P2 |$ z$ E/ T plot count turtles with [color = green]7 f ~9 @. Z% X3 Y5 Y7 B
end
4 }/ C% Y) _! Mto update-lorenz-and-gini-plots
2 a R- Z' u$ N) f set-current-plot "Lorenz Curve": ^: S& Y+ r- ^1 w
clear-plot
8 q, B8 ~5 ^ s! h7 _5 M% d9 C- X" D& D7 \$ s( u
set-current-plot-pen "equal"
% q R/ n5 g* h J/ x: F' j plot 0
! T4 a1 p! @* P6 `& M" V8 u, ? plot 1007 K2 M4 J- G! n/ O; W' u+ a
5 Y U5 W) \$ D0 n+ H( c
set-current-plot-pen "lorenz"
2 v6 y$ u9 A/ U- H set-plot-pen-interval 100 / num-people% R* F7 d \, S L; [. u
plot 0
; A- M x( L8 E: ]/ o1 y+ T8 R2 k7 N; x
let sorted-wealths sort [wealth] of turtles& W; G# X! i0 i4 f
let total-wealth sum sorted-wealths0 w ?$ o5 o9 C! K
let wealth-sum-so-far 0
& J. F5 e( H. N. y3 M let index 08 g$ q/ F+ b1 _8 w( P J: ~
let gini-index-reserve 0
( R1 ^9 n8 m1 _" [0 w# I) Z$ N G- B2 I
repeat num-people [
t6 m* Q' L+ D set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)# V. C0 g5 \6 M4 e6 l% z7 d+ k
plot (wealth-sum-so-far / total-wealth) * 100
5 W, O0 E) r/ Y1 A7 r8 c) w$ M set index (index + 1)4 B. p' e+ u" [) M
set gini-index-reserve
8 d- N1 ~% d0 ]9 x) d% h gini-index-reserve +1 G! _7 y' p& ]# s' B
(index / num-people) -: U/ M8 l! P: W9 n6 d
(wealth-sum-so-far / total-wealth)
' x, r% ~8 A2 b. g4 C3 l* | ]3 u2 K c, a2 j; k% v
$ [# c4 g( B( a, F/ p9 K% p set-current-plot "Gini-Index v. Time"
/ c- s/ O% u; |# v plot (gini-index-reserve / num-people) / area-of-equality-triangle
5 d# I W& B! n% O7 Lend
' k0 G( A2 I" T, x1 Hto-report area-of-equality-triangle
2 S6 z. M- F) |$ L0 I: S report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
. M* m' p4 ~, K6 q7 Lend |