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
+ B, I% v2 I2 G* Y/ Zglobals h, |3 ]/ I l1 b" t6 m
[
8 d3 }; P* J) a5 C max-grain
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patches-own
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grain-here & m* X1 }; R; H! M7 c
max-grain-here
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# Q$ H$ D) r' s1 j' _; D! pturtles-own& z0 j1 f. {! ]1 f9 B
[
) Y4 E6 c& m3 c) \5 O) c& w$ g1 z age * [. {2 e- `3 b/ e ]1 ?- _( b. d
wealth
1 o0 @' a+ C3 U. s6 L5 k! D life-expectancy
3 c H: t2 \: w metabolism
% K7 C8 H! n$ h: b; Y& D9 _ vision
$ u* g' H. K' U6 B% o3 a8 J( s0 t inherited
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to setup
- L+ ~7 G- h$ U$ u/ U6 \8 s ca
0 T- r( s5 E$ e3 [ B6 G set max-grain 50/ @2 R5 ?% X4 s+ F3 x
setup-patches6 i3 c; s' y1 o* q
setup-turtles0 R* F) Z5 p+ o! t
setup-plots
4 r" x( k& j) s, d0 `% g5 S- r+ ? update-plots. A9 B4 P- p$ m" m) L* ?- r
end
/ e6 ]1 J) c4 b8 D% y dto setup-patches" i6 C& a+ M5 \
ask patches
$ g8 U! a7 D' p C0 F [ set max-grain-here 08 h, ~/ F% w i% E, H7 m
if (random-float 100.0) <= percent-best-land9 a/ T) Q& Z D) q1 B- ~# W. ?
[ set max-grain-here max-grain) r, \# {0 Z9 Q1 M6 n$ N; W
set grain-here max-grain-here ] ]( K( n* \# ^% ]# l5 Y0 y
repeat 5; z. S% ~3 n4 U9 X
[ ask patches with [max-grain-here != 0]
& o! V" F+ d9 N/ w* }) h% I" A2 R [ set grain-here max-grain-here ]* a) v* H* ^4 j {) W8 @% s" z; x
diffuse grain-here 0.5 ]; }8 q3 o5 U& `: I! b1 I/ L
repeat 10
- e* W; M% a- \" A1 m. I [ diffuse grain-here 0.5]
$ W! \3 a. ^' h' l* S, h+ R4 l+ H ask patches* M' ~% x: ]& J1 k# y
[ set grain-here floor grain-here 1 i9 _" d) k9 }+ K
set max-grain-here grain-here , y& U* ~, h/ B! l% [8 O4 C6 F
recolor-patch ]4 F; {2 o* s* a9 g( r, b) B8 B6 B
end
4 r# c1 b) o, ~% U1 F" cto recolor-patch 9 z7 \' h. y2 ^' `3 G$ j/ @" W
set pcolor scale-color sky grain-here 0 max-grain
' a. Z. d. C& [* @4 Hend6 c6 l( @& _! I! r: `+ B
to setup-turtles
1 `6 n1 \; \2 G Z set-default-shape turtles "person"! w3 l$ t! l+ v2 h' G9 Q
crt num-people1 A0 ?; d2 h |7 K- Z' A2 s5 Q% @
[ move-to one-of patches & S% \8 l: R4 B+ O1 F/ E; G! l
set size 1.5 ( a6 {' E9 F1 K. I3 j& c3 G
set-initial-turtle-vars-age
& F4 r l+ @$ `3 [2 t# S set-initial-turtle-vars-wealth1 f; P' j3 H/ z' Z* |
set age random life-expectancy ]% X- V5 p6 o5 r- U
recolor-turtles
8 K' e- @2 o& Z% j/ w. g Y5 ~end
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to set-initial-turtle-vars-age
2 {% U$ ~7 {( y4 `4 Q, k* ? let max-wealth max [wealth] of turtles
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' e, M$ j8 N3 X/ R- P* p ifelse (wealth <= max-wealth / 3)
- |2 ^4 O% S; n/ e1 H4 { [ set color red / F& [5 _8 O6 M3 A* A7 s( `
set age 0
1 F, J4 w' r) T# u face one-of neighbors4 - a. M- d6 n w5 K* D( s" H) @7 i
set life-expectancy life-expectancy-min +# }6 M$ {1 W( }& K" x, _& E; w, |
random life-expectancy-max ! Q, |, A3 Y* q" J2 o8 ~% U; o- m- i, H
set metabolism random 1 + metabolism-low
/ Z. {) V' O; ` set wealth metabolism + random 30
% {, O6 b3 y1 y8 q' t set vision 1 + random max-vision
& J9 Q7 c0 R# P set wealth wealth + Wealth-inherited-low ]4 g* [. a+ u% g4 i" O5 F
[ ifelse (wealth <= (max-wealth * 2 / 3))
+ b7 m- f' l: w [ set color yellow / E( n0 t2 l1 | M, _$ B7 x
set age 00 s7 V, J) k3 Q" T4 B
face one-of neighbors4 - K1 ]3 \: e. N/ I) W1 w
set life-expectancy life-expectancy-min +
7 O v1 v; N4 u$ J random life-expectancy-max + 1
2 y4 v/ y* t ?7 X) Y% C% K) C set metabolism 1 + random metabolism-mid) B0 N8 V" h/ Y' X. H
set wealth metabolism + random 30
& I0 v' F7 o& o# R2 F set vision 3 + random max-vision3 P' K0 P4 g" C9 G+ J. ]5 L
set wealth wealth + Wealth-inherited-mid] ~: H2 X. @9 @. g' Q% j; o# Q+ E
[ set color green % |$ j t& z8 p: S0 Q0 }
set age 0! t2 v0 [2 l# Z8 c0 l( N/ ^ {
face one-of neighbors4 ' D, M- e# H% t. E1 X; v% G8 j
set life-expectancy life-expectancy-min +3 q5 V& T$ I4 h2 G0 E
random life-expectancy-max + 2
" @- v; {6 M0 ]8 M- _/ y set metabolism 2 + random metabolism-up0 e5 T' q( o# H) }7 Y/ n' x
set wealth metabolism + random 30# H' `6 v3 N" ^" {( P! }
set vision 3 + random max-vision( h( C/ P/ N( \2 Q
set wealth wealth + Wealth-inherited-up ] ]
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end& m# A' l$ }& P2 ?3 k; B
to set-initial-turtle-vars-wealth
* T$ h, P9 U: m! d let max-wealth max [wealth] of turtles
* z' C( B6 v+ c$ Q; e set age 0
+ @$ @- E: D9 D8 A( I5 U face one-of neighbors4
% I3 e+ s; o& T, s! z# a, ]+ O+ V set life-expectancy life-expectancy-min +: j! D8 R; D6 h; c) f9 J
random life-expectancy-max # _# Q1 K2 z2 J
set metabolism 1 + random metabolism-up3 \+ M0 e5 E! m% i9 f% T# U7 Q
set wealth metabolism + random 30
7 k; X5 [( A! A6 \# d set vision 1 + random max-vision 1 G- `( [3 A$ G5 T O% M* Z
end
: A) ~: f6 p0 z% b+ F& V3 Lto redistribution
& x) H+ J) _) m1 G) plet max-wealth max [wealth] of turtles- [8 ?0 Z0 ^# _4 L; O
let min-wealth min [wealth] of turtles
$ D( {, o$ E# d# P. M( R' D! l( jif (wealth <= max-wealth / 3)8 x% U( K% y: ~5 i
[set wealth wealth + Low-income-protection ]
# h8 |! B) q& S* ]5 a0 kend
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to recolor-turtles7 X9 |- P3 d& K( S
let max-wealth max [wealth] of turtles
8 `: P# {# U+ I ask turtles
% Q# _/ S8 Y- ~/ D+ o/ m( d. n [ ifelse (wealth <= max-wealth / 3)
9 X3 x7 b3 w! q/ K [ set color red ]
2 p3 {, P5 m2 R. g+ m$ r$ W0 d3 p. P: a& B/ _ [ ifelse (wealth <= (max-wealth * 2 / 3))4 ?: x, w! t- @1 t, q9 I( l% `1 _9 F
[ set color yellow ]
2 M: ^' j* k) p* p# Y4 y [ set color green ] ] ]3 p6 b4 @- P2 y
ask turtles [ifelse show-wealth?; @. R* \# Y7 R( }5 R
[ set label wealth ]
6 C' c) r/ _) R+ v, K; Q [ set label "" ]]
% q W8 A7 b) R# ]9 P+ mend
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, V3 V+ _, _8 C4 X, {$ ito go
2 R* v5 R+ W: i/ W& K% F: b ask turtles
* k1 a/ L) i ~: G [ turn-towards-grain ]
6 P, M: t8 w5 F* Q harvest& P5 G: n! A. J3 |7 ]
ask turtles
, v& ?& z& n6 R1 j3 d `8 K/ G [ move-eat-age-die ]. g8 z% }% L2 V) v W
recolor-turtles
% U% B/ |7 c2 {3 P" ~5 t. Z if ticks mod grain-growth-interval = 03 e6 L" {% D) _. d$ b1 o, \
[ ask patches [ grow-grain ] ]& L8 T# M' \. c" o- G! ~- i% e
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if ticks mod 11 = 02 E9 b$ `; m6 C! w3 i! ^& ]8 k
[ask turtles
& S% O4 d& k2 y! k( P4 `9 J [ redistribution ]]" c5 \1 C2 S- x- v0 i
if ticks mod 5 = 05 D" u5 U9 Q1 V5 d
[ask turtles, [0 H3 i/ m9 N% I& J5 q
[ visions ]]
, Q- F/ C/ G- e$ z8 p tick
% o: `* o7 C* C2 V0 | update-plots
: f1 H! `( h) ?end/ I/ V& V$ {% A6 k: ~& y# M
to visions
& j5 u% T# a& ~7 Y! n8 Z! }2 v u! G set vision vision + 1
, z! d0 E k9 send% t. u1 |- h; h) D5 Q
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n# `- h3 R. ~- \
/ {! Q3 B% i! ~8 [/ s5 c. g+ N+ \to turn-towards-grain . h: A K, ^! O1 H
set heading 08 A* G- u% ~/ s0 N) Z& ?
let best-direction 09 x$ [( J0 g2 I$ w
let best-amount grain-ahead
% k e/ E% N# T) K, @ set heading 90+ I& R- q- q5 f/ U# d0 J% f
if (grain-ahead > best-amount)
" \" J! x7 t" [. C) i9 y [ set best-direction 90
: U/ w* E r/ v& V* | set best-amount grain-ahead ]
: K$ z+ x; ]9 B3 Y( S1 p2 k$ G0 X set heading 180. V" u- K% E3 S5 Z
if (grain-ahead > best-amount)- [6 d. n- N5 @% Z$ Y' J
[ set best-direction 180' `# o1 Z2 H( m
set best-amount grain-ahead ]% c5 A2 \' ^: L$ G/ o
set heading 270; p; d2 j! Q! z7 f# |! v
if (grain-ahead > best-amount)
! N: V' R! m! P) \ [ set best-direction 270
6 J4 f2 f# l( R& w0 @3 b set best-amount grain-ahead ]8 x' h, X$ V8 j& n
set heading best-direction
2 D; A5 k! b- T* Jend* }2 _0 q& b2 Z0 G
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6 j/ J+ H. ]* K/ l; zto-report grain-ahead
7 |# W/ S) W" X* U let total 00 u) Y5 O# f( d6 _
let how-far 14 O( P' b0 k5 n- P
repeat vision: E1 p6 i& v/ |, t c j8 c9 Z& d
[ set total total + [grain-here] of patch-ahead how-far. `* ]# ^; i" \# D; c" j
set how-far how-far + 1 ]7 Z. t' ?0 a! _5 _1 c. K
report total
; w0 l- D2 D9 Gend
% I( X; a5 z9 R7 d0 t
6 f8 v* n; F$ Q% m, _% X! x% sto grow-grain
! C R2 c; q {: w if (grain-here < max-grain-here)( R) s' E7 H9 o9 L/ }
[ set grain-here grain-here + num-grain-grown7 j/ M* W; c: u7 D/ R, j
if (grain-here > max-grain-here) - ~" y: f$ S. H' a
[ set grain-here max-grain-here ]6 [$ n! d7 r* Q9 b$ r2 W D: S4 p
recolor-patch ]$ o5 ]% B4 ]3 i: L. Q( z% T$ o0 I
end
# N+ q* C+ F' K# z! m1 G2 `: Oto harvest' n" K/ \/ w, v; E6 d) f* ^
ask turtles% F7 c- G* T% o, H* X0 f6 o( r
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
1 J: I D* F! E ask turtles
# c+ A3 j& P' A+ w; J' V i [ set grain-here 09 E. v4 n3 y) G- ^
recolor-patch ]2 T8 a: A [- }! y) u
% w i1 j& p# N1 ?
end
2 ~+ Q+ n, y5 ]( X
, j, a. o+ h, Q i4 Z! y4 vto move-eat-age-die
0 i& H" ^, h5 R3 o6 r fd 1
: G5 F5 ^2 K6 q% a set wealth (wealth - metabolism)2 M0 g4 Q1 S) E' F0 J5 s n
set age (age + 1)
' t* ~, P, _3 {* e9 F8 B if (age >= life-expectancy)
O9 }1 L: l3 }& J# Z- w* E [ set-initial-turtle-vars-age ]. ^' N! m: I7 G& k
if (wealth < 0)
: y: y: ?8 n# C$ P, G" C2 v [ set-initial-turtle-vars-wealth ]
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6 B; d' `) ^' `+ Q( Hend
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T4 L8 ~8 K- [* q% l3 ~( Uto setup-plots
G% X: I/ f. U$ h2 k set-current-plot "Class Plot"
s7 t- D) b& M2 P2 G c set-plot-y-range 0 num-people# T% N) G9 [- n/ ]% k. k) Q
set-current-plot "Class Histogram"
+ t9 m! J$ p" g+ O7 q# h# O set-plot-y-range 0 num-people
: _' K! K3 `* K& D/ Vend
% A- o. {! [8 q
2 N# }& p7 g/ E+ {$ u* z% hto update-plots8 ~3 }% A& X& B- \1 [) m* q' F% }9 [
update-class-plot( O" W' |7 _4 E5 F4 `
update-class-histogram
% |1 D& u3 l! D+ @! R% o; K update-lorenz-and-gini-plots4 z4 o- h' D( j0 k
end
- o; {/ Q1 J& c; v6 q+ x+ @ L' k) [# x% T) k. H
to update-class-plot" d1 r7 ?$ y |1 a
set-current-plot "Class Plot"% O2 A+ ^* _: F: x
set-current-plot-pen "low"
; D( m/ C3 ^3 J4 }8 O plot count turtles with [color = red]
3 p. p- v, l* ~ set-current-plot-pen "mid"
( N! M# N. y) e8 U* t plot count turtles with [color = yellow]
% N# c& p( H0 s9 l# P9 G" b set-current-plot-pen "up"
/ {( P: l# _9 H; C( Y$ x plot count turtles with [color = green]
. q {8 D* f) `end% ]" R4 f* f i, c2 O
# b) q& u2 X5 N$ Y
to update-class-histogram& m% E" X" f* D4 s4 @& z
set-current-plot "Class Histogram"1 z$ _. X4 _0 d4 c
plot-pen-reset/ q# w! C- g3 D0 ^0 t+ I& i0 l
set-plot-pen-color red; G. W7 B! t' y0 N! `, ]. |
plot count turtles with [color = red]. f* E8 m# a/ }
set-plot-pen-color yellow3 \9 x# [7 w5 D' i# E
plot count turtles with [color = yellow]9 M- \* d" A% ]; ~5 a. X! L
set-plot-pen-color green
# n2 R: H) G6 ]- S& e plot count turtles with [color = green], }+ x( o6 G9 @3 e" ?
end) B. w& z2 w1 i) P9 i! L
to update-lorenz-and-gini-plots% q" D8 ^5 }" @
set-current-plot "Lorenz Curve"2 k, E$ u4 W# O" S5 p
clear-plot
' H8 p5 R/ w& }% R8 \6 [
! t3 T5 I W( n# h set-current-plot-pen "equal"
' _2 x( r5 A; ^; j0 H2 J( y$ p plot 0
3 l% [ u) f) g5 N2 B8 K! K. Y# q plot 1000 s4 m6 m6 _- Q) x/ `" V
. r5 k# I; `* V1 O0 X& Z0 |1 _
set-current-plot-pen "lorenz"
& t0 i6 ?0 j$ F( V set-plot-pen-interval 100 / num-people
; h i- L) N8 ~8 i6 X! ?9 [9 S7 {1 ]. E plot 0
9 c/ C1 @- a' ], h0 B1 Z2 \" a$ \ x \: |% P, I8 ]) p4 [
let sorted-wealths sort [wealth] of turtles
V1 Q* H3 P8 ^ let total-wealth sum sorted-wealths& x$ e( ^* E8 i [ h) m
let wealth-sum-so-far 0
1 f! B$ u+ D; h, a' Z let index 0
9 K/ Z! t* e1 q* O& ^ let gini-index-reserve 0
! z* d$ V2 s$ R8 x* v) K! t9 d4 B3 K6 o L7 Q# Q
repeat num-people [! U5 Y' `3 U0 y# l
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
3 X" F2 a( H% o# G' y plot (wealth-sum-so-far / total-wealth) * 100
5 A6 d& T/ w3 q set index (index + 1)" s! t) e( j: n9 w" s4 ~
set gini-index-reserve! }: p, l" Z, Z* K Z( i, W0 O
gini-index-reserve +
8 X5 g/ T! ~% ^1 f# T+ }" I/ A# U (index / num-people) -
* |9 o$ d0 T0 O6 `' y; b (wealth-sum-so-far / total-wealth)
0 }+ u5 l( R. o# K9 C/ K ]8 {* k* g* i4 ?( _( }
9 V# T4 ~( T9 d! l+ g
set-current-plot "Gini-Index v. Time"$ X8 F3 G! U9 I3 m. f9 {# `. P
plot (gini-index-reserve / num-people) / area-of-equality-triangle+ ]% g% b, K' u h
end9 p% `% E a4 b# T
to-report area-of-equality-triangle
1 V! v0 l% Z, A o report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
4 u8 k) w1 Z5 n% D" P+ [8 \end |