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
/ R1 U- K' z5 V4 h* Y# jglobals
5 Y6 b1 [9 \6 o: s. H7 a0 t8 V! u[
0 }/ r# B! j1 s/ ?! D max-grain $ C2 ~+ X% M, p; N
7 q' a- C1 F9 ]) O0 Y]
. i- W, c0 J) r# I6 |0 A3 F9 I, S: {, _" h% h
patches-own' E( q- F8 h3 }+ ~! s. v
[/ @1 J" S: ]3 }/ S1 U9 {; w, |
grain-here
( ?* P- a5 t. r" d+ A% d max-grain-here
3 q4 @0 }# K% s+ T3 K! F2 A$ E]
1 b$ \& p/ D8 p; z$ r+ N" e+ H0 T0 n5 O" ~$ b
turtles-own
+ c5 e' X' H7 m" t8 p[$ u0 w. b6 l0 `* Z K
age / ^0 l* _4 w* u0 _6 J
wealth 0 T7 {/ @9 E5 G1 k* {# y7 O' [% c
life-expectancy , P) g& p7 P0 V9 T5 q
metabolism ) G; h \: C8 e+ C$ | K
vision" D+ o; V% |" Z5 ?, h/ H/ S
inherited
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9 O5 m6 m" s& Z* i4 r6 `% S1 _$ x% O
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, x/ T7 G7 t5 ^0 Q) uto setup7 S; B" g# J- I. W( }+ J
ca6 [7 K0 L* o: M. j" ?* {
set max-grain 50
$ f6 r- k" ?' P% p setup-patches
) m$ a8 |' E3 o$ X setup-turtles
, e' R8 |0 N" h4 q J) H: R setup-plots
3 g7 v/ }: N) |# V) v. F5 i) k update-plots
; X. E$ V0 V+ d1 k6 h0 Q6 pend
4 b* C" R' T- p) dto setup-patches8 l: J) I- d" g* U
ask patches
" Q% J0 S2 ~' K5 I [ set max-grain-here 04 A; m0 p9 j; h
if (random-float 100.0) <= percent-best-land7 ^% Z; `; v3 t- f$ I0 R3 @
[ set max-grain-here max-grain
; M. t/ B" U7 K set grain-here max-grain-here ] ], z0 {. }, O6 z. T
repeat 5- R! w! F/ A# E
[ ask patches with [max-grain-here != 0]
- v W& I1 j0 u [ set grain-here max-grain-here ]2 G7 ~, j' P8 |& _: A; n+ Y+ W
diffuse grain-here 0.5 ]6 r, a( |/ i; Y4 w$ F
repeat 106 H& M6 M7 ^/ ]! b+ s
[ diffuse grain-here 0.5]
9 V4 p$ K, D2 y' w* ^6 w5 b1 L' ~ ask patches
2 T; a. O% `! o9 u' h ? W6 V [ set grain-here floor grain-here ; M2 C9 l8 P6 O" A) d' W
set max-grain-here grain-here
. E- ^& _* L7 q- _; V+ }' O9 l$ G6 H recolor-patch ]" b& U3 I7 l- J! L4 k! N
end- ~0 d) h! r0 X
to recolor-patch
, u: \2 T( @3 G set pcolor scale-color sky grain-here 0 max-grain
0 d( D1 r5 x1 e ?8 ?end
1 S+ z. g6 p" n" y- v( m5 d- Pto setup-turtles
* ?' {0 K( T" L6 M# N ^ set-default-shape turtles "person"
! ]% x! K$ }( c' z" D8 U crt num-people
g' D) H" \, O% v) j/ p3 | [ move-to one-of patches & a5 p$ H x3 {% I: Q1 S4 _' a& j
set size 1.5 # M5 [) T' R8 U7 ]( s9 {
set-initial-turtle-vars-age {6 O4 V/ W, T2 S/ X7 f" R
set-initial-turtle-vars-wealth! ?! i" T7 N: _; v% {
set age random life-expectancy ]' _' S. T0 Z7 d, @3 [7 N
recolor-turtles
; X4 _0 J( J% C } n+ Cend% A7 Z& n1 p3 O5 J
1 Z2 a) U: d$ C( y7 {% B
to set-initial-turtle-vars-age6 w) @8 V9 {4 F. W. S: H
let max-wealth max [wealth] of turtles
8 e/ @2 |. H& Y) U( F
! J2 H* H1 o! R h4 B ifelse (wealth <= max-wealth / 3), X8 Y$ C7 t; h; t. L! D d
[ set color red * p) j8 \% M3 P) k
set age 06 b; x. {0 }" ^) k# N: t
face one-of neighbors4
+ F' {2 P- {! @1 |* J set life-expectancy life-expectancy-min +
3 ~' A' x! w9 s' _) t! P" B! b. M random life-expectancy-max 2 P! \: A& R; j# Y7 Q
set metabolism random 1 + metabolism-low# X3 |! D {. o/ e4 m: j
set wealth metabolism + random 30
4 v( j9 C$ O+ [, g+ A$ m set vision 1 + random max-vision3 N! X M ~. {/ i4 q5 Z, F8 X: g
set wealth wealth + Wealth-inherited-low ]
. |, y8 h, p; h) I" R0 B [ ifelse (wealth <= (max-wealth * 2 / 3))
+ u0 p6 I2 T" X [ set color yellow N- P& @, |8 K' z& r" \) v- K( T
set age 0
6 x. r0 y3 r# N( D2 r) N face one-of neighbors4
' W* e& U8 C$ ~) z, I& e. i8 K+ m3 R, G set life-expectancy life-expectancy-min +
& j/ @' j5 ~' `& f5 m7 K random life-expectancy-max + 1
7 E' Y/ |! L! _4 j7 ]( ? set metabolism 1 + random metabolism-mid
- [( e- \2 a2 {8 _7 T/ l set wealth metabolism + random 30
6 b( s2 p7 F. a: P6 ]' S set vision 3 + random max-vision
& z: I3 Z/ I( L( A; c" K& y* x set wealth wealth + Wealth-inherited-mid]$ U* s0 F: ]/ P; [5 P8 i
[ set color green # ^$ u6 W+ M5 o9 ]
set age 0
j+ m" u$ z! T4 G5 }3 A8 q2 ? face one-of neighbors4
* s" V6 ?. Z+ z! u7 g* G set life-expectancy life-expectancy-min +
- I7 Z3 L7 b) Y2 _ random life-expectancy-max + 2; }) x/ R- P( U8 Y! C& w
set metabolism 2 + random metabolism-up3 O# K! q: U2 u" }% F
set wealth metabolism + random 30$ n9 ?3 O% g2 J( a: M, m
set vision 3 + random max-vision5 N% Z- n5 s# k- H
set wealth wealth + Wealth-inherited-up ] ]
- m7 ~4 V* ^1 a8 e . R0 ?. X& x* q! I5 M7 E
end
' N5 ?0 g& Q. m$ o3 U+ Y' Q/ cto set-initial-turtle-vars-wealth; r2 v1 Y/ |# V% H1 H" n
let max-wealth max [wealth] of turtles
9 l) y8 I* P! u set age 0
7 W! `& E8 K9 _% e$ A L& ?! k# U face one-of neighbors4 # d/ Q h$ w/ q: e
set life-expectancy life-expectancy-min +" N& _+ b) @8 L9 Z/ O* a. `
random life-expectancy-max
& n$ D- x& |! g& l( x7 p. X7 e set metabolism 1 + random metabolism-up- Z1 L7 p4 N7 o$ k/ Q, E! w
set wealth metabolism + random 30
6 T) _5 t; {; N, m set vision 1 + random max-vision 2 d4 B8 e/ ]4 C
end
( Z) @. a0 z) c" Q4 m- Bto redistribution
# v4 j: U- f) Q. o7 Jlet max-wealth max [wealth] of turtles# }. O& j* ^1 Q3 B/ Y/ O9 R
let min-wealth min [wealth] of turtles
' y8 Y! z1 k$ e4 n! w# A- b6 Oif (wealth <= max-wealth / 3)
. c$ x3 p1 s4 ] [set wealth wealth + Low-income-protection ]
7 ?8 u" b% A6 |: Z2 V& rend
5 ?- B8 Q: T# \" F1 Y" Q* Y 3 |! M. |1 R$ t: R( x7 l1 e5 ~
to recolor-turtles( l' W0 y1 A& c8 T& W4 l: p4 G9 M
let max-wealth max [wealth] of turtles2 T& \5 p+ B) M4 T0 I6 d
ask turtles/ h+ Z1 q& h4 B. k' l
[ ifelse (wealth <= max-wealth / 3)
7 @8 y# F" d, J8 _3 u [ set color red ]. j' p0 j5 k+ L
[ ifelse (wealth <= (max-wealth * 2 / 3))
4 S) ?7 O2 z; k" { [ set color yellow ]
5 |/ d% v. a4 A; e: B* y8 h [ set color green ] ] ]# B( v" i- X4 K" W
ask turtles [ifelse show-wealth?
$ ]. y% |/ W" A+ a' T& V [ set label wealth ]% P; x% v9 F$ u; a& w
[ set label "" ]]
! l* s1 K) I* q- J, Cend
: Z5 r! y6 y+ r- `, d& l
; \3 ?4 C( e: n# @to go
9 v2 q H2 t e) k" ^: O ask turtles8 B. ]5 ~/ |0 ?$ L& w. V
[ turn-towards-grain ]
. H* s. j4 s- t harvest
5 b4 \' m; |1 M0 z$ Z/ `! @ ask turtles
1 [+ k5 S' Y m8 x [ move-eat-age-die ]
1 U' h! C4 U" B6 r+ S0 d recolor-turtles
9 ], W& ]1 y1 A. E if ticks mod grain-growth-interval = 08 s, P4 i; y9 I% ?0 S. c
[ ask patches [ grow-grain ] ]
( z/ `# j8 L" Z" U; p% I, q$ S3 v' n g) b$ b/ a4 | k6 V
if ticks mod 11 = 00 z3 g% t6 n9 ]$ q+ u: z- l9 x
[ask turtles8 v0 w7 K7 l: d* u t! P7 w
[ redistribution ]]8 D/ f* S' j5 i- B! }& T, x
if ticks mod 5 = 0/ y# T. y2 ?0 X
[ask turtles& P1 | i: q6 o5 B# C/ U' y/ L
[ visions ]]! I, G5 ?. r, R* R
tick* C7 o/ c, n1 D( E4 C0 u6 F3 R c( S
update-plots
+ k1 S4 e3 w' Q/ Y U3 zend$ ?' U& N, h2 U t. l
to visions* L) ?0 O' ^. \3 s) T' \ W- q
set vision vision + 1 / \. S. G6 L4 g
end" Y' n0 `/ {9 M. ^* f$ m# l. ~9 C
( V8 D, d) Z/ i- b9 I9 [
1 e$ k; _& i, q' Y/ O
6 L1 N% m" Y% E7 pto turn-towards-grain
% j4 N" ?. b+ P* }% t set heading 0
; Q* z; O( P$ A8 W6 ?- H) k let best-direction 04 V! d8 C u: U
let best-amount grain-ahead% R# E; g% u6 _# O( `" {; g& Y) v$ N3 K
set heading 901 A1 H1 P! g" s5 k. {2 k1 f, ~
if (grain-ahead > best-amount)
9 {; G( `( G1 i1 S' j/ O [ set best-direction 90( h, s/ K+ N x r: x' D/ ]
set best-amount grain-ahead ]
+ ^" K* L" ~' ^: R set heading 1802 B1 X+ F/ J) i( j
if (grain-ahead > best-amount)7 L P& Q2 y. J. i: M% S
[ set best-direction 1806 e/ L" g ^4 L- i$ l" c
set best-amount grain-ahead ]) _, Y( V. ]& f% D; M- F
set heading 270$ I/ D3 I i) a" Q; E
if (grain-ahead > best-amount)
4 X+ q1 \* ~: E6 P& {/ @$ [) C [ set best-direction 270
7 ?8 O0 B- v7 K; L9 Q! U+ e set best-amount grain-ahead ]. [8 S. i3 m2 a6 D; e: s
set heading best-direction( I' `2 v [# ~* j+ h
end0 D9 g g8 f8 l, p; Y# x) d) O3 X
3 a/ a9 T* ^# d, J# `7 y/ s& ?
2 e3 |& }! B1 Y) w& ]to-report grain-ahead 6 y* v$ @2 f) P$ m0 l
let total 07 \! D8 H7 n& `* W
let how-far 1# l) H! q4 z* F, T! @) U& r2 ?
repeat vision- b x" R7 w) T( Y: O
[ set total total + [grain-here] of patch-ahead how-far* ~5 w% T7 U1 p( i
set how-far how-far + 1 ]
9 {3 V- e |/ U( D Q, B" u report total4 ~; a2 n: V2 u P
end
2 |: |3 N/ n7 G; u' L9 I1 E; D9 [$ r3 Z) B/ s8 w8 C/ A
to grow-grain
9 a0 U& p. u6 i if (grain-here < max-grain-here)
: {" Z/ ]# J4 s0 Z" Y [ set grain-here grain-here + num-grain-grown
# ^, s( b; {2 P N" ?5 k if (grain-here > max-grain-here) ( _4 v {: R- B! h' i
[ set grain-here max-grain-here ]4 B" Q; {( D- V {
recolor-patch ]0 s+ s, Z2 C) @, @5 l$ l
end6 n! |2 u# `3 a1 @' G$ V
to harvest- \3 t4 p( j) U
ask turtles( u9 n) U0 k& n& O% \8 c
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]: |1 p* W- v8 P1 `( `( J0 @* A
ask turtles
- o/ W: R" d, H" r M# F1 R [ set grain-here 02 Y" Y# [' ]* x6 U0 ^5 O
recolor-patch ]
/ T; @8 ]; Z4 M( p6 z 8 q, z2 ~" ~- A8 U
end$ t1 x, |' H& s. v
: `1 } ?2 _3 |# @' u, N
to move-eat-age-die
" Q. [9 W: o2 U% } fd 1
( v" Q9 ]# w7 H3 G) e set wealth (wealth - metabolism)
0 P" w& W) O0 M. S3 N set age (age + 1)
1 O8 I# i, ^0 t. n/ Y" J$ n6 g if (age >= life-expectancy)+ R% q7 N2 Z7 ~) T. S8 B, w+ R
[ set-initial-turtle-vars-age ]0 j8 u- E9 _- G: o8 X
if (wealth < 0)
2 J8 ?2 L2 B) e# N [ set-initial-turtle-vars-wealth ]; e5 c# F$ y% C4 h3 W
: j( u* f% i# R* m- e
end) E. M! X1 Z9 m4 U* ?) \4 K& n
3 ^2 x+ ^9 r- b# P) e: W4 a7 o$ ]8 T$ r) b8 d2 I$ s- i, e
to setup-plots) q! b- D4 o' N6 q* d
set-current-plot "Class Plot"
. T) A, }3 a; k/ |6 [ set-plot-y-range 0 num-people
: r( T0 l7 O5 a" r set-current-plot "Class Histogram"
2 I n: ^3 f( H5 s. @ o- U set-plot-y-range 0 num-people
2 @+ n# d/ |7 n) `7 p4 v aend& Z' F8 p" s" b) g+ T' w! q* P
4 G% p: r7 \6 q2 L# s' T) V; w0 S- X
to update-plots
6 L0 f F- [; n0 v update-class-plot
( {, O8 g! p# C. @$ \6 S6 h update-class-histogram
+ n4 N) o; H6 F* z% n update-lorenz-and-gini-plots
" X8 I" R* X* {8 s `) s) `end
$ m6 z! s2 O: o% U1 u- b- h$ v
: O! c6 O0 m% @' _: ^1 g( s3 ^6 gto update-class-plot
; Z: Y; b' B2 N+ H: D set-current-plot "Class Plot"
8 r, v; [% h9 c0 f) L/ t set-current-plot-pen "low"$ L* b3 ~. d5 S; v, |" r* ?( W& P3 ~
plot count turtles with [color = red]. u8 l% S+ _& o" P$ M$ o# }) _9 t0 O
set-current-plot-pen "mid"
* M0 {9 B# |) S& ~1 V: b) e. U plot count turtles with [color = yellow]" v9 d) ^% |8 W3 F6 R- o
set-current-plot-pen "up"
" ~, m9 x6 h. g7 q plot count turtles with [color = green]
7 b0 e9 ?& _+ ]; r! Aend7 w2 e9 _& t x+ n* R! g$ L
! K+ ?7 Q% {; |9 d2 R) D& G
to update-class-histogram
V& Y- [2 D, o: Y set-current-plot "Class Histogram"
+ \ n, F& f/ B plot-pen-reset
. y, z2 F; Y6 @( v" r/ y set-plot-pen-color red {/ k. M& l6 Z1 ^ ~% U
plot count turtles with [color = red]
9 y R/ A! P) @- E* [" D- M% o. {% ` set-plot-pen-color yellow
: [- S5 L( e5 r* }& N1 L plot count turtles with [color = yellow]' k! D& p1 [7 I% L
set-plot-pen-color green1 D4 h2 ?: {+ o$ Q0 o
plot count turtles with [color = green]
- s9 Z6 r% \7 m" s$ q# H0 O. }end( w0 f; h9 v! q2 W# S' O8 X
to update-lorenz-and-gini-plots
, b* x$ x. r `# ^ set-current-plot "Lorenz Curve"; A: Z1 y3 j1 |: M
clear-plot
8 E* j/ e* h! ^4 [* _& ^) m
g2 Z) E! X9 h/ Z& s& \ set-current-plot-pen "equal"
4 j1 ^- o9 w! V) f3 z1 Z6 Y plot 0
& z5 ]7 W o1 q# `4 k1 M9 k3 y plot 100
* Y' S" n: v, d F j- R1 S$ N' ^4 a8 F! n0 T* u: e
set-current-plot-pen "lorenz"
. L$ C3 X" e0 A( S+ C1 R9 @6 ?* { set-plot-pen-interval 100 / num-people
3 J" m* X! K8 l3 L2 R4 z5 d plot 0
0 I8 s6 V# U. }2 X% w1 k
1 X+ q" w$ F) v. R! Y+ N4 { let sorted-wealths sort [wealth] of turtles% e8 T! R2 C. s, d% e+ b
let total-wealth sum sorted-wealths$ b1 [6 u# A& C- z/ j# }
let wealth-sum-so-far 0
! i4 d' D8 \; O8 a let index 0
* p9 t5 Z% ]! `2 Q, q4 ? let gini-index-reserve 0- l! Z: `2 ~7 W) Z4 N8 u3 j
& F) _, W6 Y/ q/ A repeat num-people [* p" q0 F( y2 W
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
3 ^( O7 E, f1 P% G9 g. _5 m plot (wealth-sum-so-far / total-wealth) * 100
, ` d7 Y* [1 m! [/ \* E set index (index + 1)
2 }9 y/ T# t* s0 B5 {- ]& g set gini-index-reserve+ \. F# f# |8 _% k
gini-index-reserve +
9 t6 J- E* f% i' {# u% H (index / num-people) -) v; d7 S+ l3 b
(wealth-sum-so-far / total-wealth)
0 `4 h! r8 ]) a! [* s! \- W3 _ ]
) M1 n C( i( X3 }
, ]3 E' P& U( j- C, |1 V set-current-plot "Gini-Index v. Time"
' m E J: W6 [! j2 C. L# T3 G plot (gini-index-reserve / num-people) / area-of-equality-triangle
! _" d1 d! v7 I# Y; Send) ~/ L& a$ n: `# Z' s9 G6 w
to-report area-of-equality-triangle, e! W% {& r( N1 }1 _" v1 R8 d1 ~7 k
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)9 h! N4 I5 Y. M
end |