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) Z! f Q) m4 ]1 V
globals( ~0 b5 X: v: [3 v, F5 O1 H5 T8 Z5 N
[
8 l: q- B6 I$ S max-grain
8 p" o; r' y* K" D, g+ J! u9 o9 d
. a, @! I K7 o6 V" m]
2 v8 a5 d& l1 V& O# o @
+ h4 ~7 f" A3 C3 O( e/ gpatches-own
7 j6 }5 ~5 I1 i, R- z% \1 ?% v[7 O5 y C( g; x. H8 Z
grain-here
: i! M' i0 G& j max-grain-here
+ t+ K, z. |, }$ w* K]) k4 N9 C7 X) @5 c/ l
0 o( }7 p6 e( o1 g( Iturtles-own
0 G5 A x' k4 U" P- v [. E[
J0 O! Z# l* X7 Q0 b age
/ ], R$ Z" g; j5 U* @9 k% [ wealth 0 v* [4 ~/ F9 e9 y) W
life-expectancy
2 t& i7 s# S+ L, D metabolism ( M& a6 y1 ^. E% r7 t
vision3 B6 o3 C" a/ k+ t
inherited $ l+ ^0 U7 | B" o2 ?5 v
]
8 t0 h5 m1 j: c+ p" W6 J2 o) |6 `3 T5 p
4 h. l: z! _: v& C2 B2 {* M% V
to setup2 J) H" e& ]0 a: x2 m/ l0 z" t% Y
ca
. B) B% F4 e" h' C6 n& j) u set max-grain 50
, z6 Y, J( V% Z* k2 G4 i setup-patches& G' @3 G& T4 Y( w, v
setup-turtles! N( d8 e! a# `. d5 V+ e$ ^, |
setup-plots: c) Q0 d9 Q* N3 e5 f
update-plots
0 I3 \! v7 K5 N% m' A& H5 A, Fend( s$ y. X( B5 d+ F0 f9 n) D
to setup-patches5 }% e& g# g. Z+ p; n- k
ask patches) ]8 a7 ~9 E( z% _& D
[ set max-grain-here 0
" g' G. A4 i0 \$ } if (random-float 100.0) <= percent-best-land* ]5 _ L1 [& S) ^
[ set max-grain-here max-grain
- @" x; K# l, V set grain-here max-grain-here ] ]
+ m% T# ]6 ^5 o& N8 k repeat 5
3 y2 f# X9 {. O2 Y+ A [ ask patches with [max-grain-here != 0]3 K" X' d g# _* o) J
[ set grain-here max-grain-here ]. t" Y- P4 {+ a3 s9 Z; a+ G
diffuse grain-here 0.5 ]
8 S( `4 H8 L+ A: k5 B7 M. K. `8 ] repeat 10
! `; O, D& \9 @! M- F& h- V [ diffuse grain-here 0.5]
6 R* L) l* X. K4 _ ask patches1 Z8 t' \% V6 N& Y3 Q* N
[ set grain-here floor grain-here 4 n7 t% n4 q( t6 q# g2 T
set max-grain-here grain-here 5 x: {/ e9 m, y ?/ J
recolor-patch ]
9 A1 }% K0 _: |: L4 y( I: Send" Q, W5 k* k; s& n
to recolor-patch
/ g8 }0 ], y( i. a7 M% E set pcolor scale-color sky grain-here 0 max-grain
2 I. b0 x+ y3 hend0 ]7 R# N) W4 b9 k# Y* ^ x# _
to setup-turtles
1 j% ?2 `8 V# r set-default-shape turtles "person"
9 V! z2 W% G9 O$ C crt num-people9 p* i* n9 O( d1 Z1 E$ ?
[ move-to one-of patches & q/ ~& d: s; w) A" \8 x
set size 1.5 & [- u, k4 Q* C8 ^) Y! D
set-initial-turtle-vars-age
* h3 ^2 Y" j, |2 T0 t set-initial-turtle-vars-wealth
3 _% _9 z) e$ ^: P8 _ w% l7 h set age random life-expectancy ]
9 w E5 D1 X: C; B. p recolor-turtles8 b8 G9 Y- o% Q6 `
end4 T# @2 z; o/ N# W' G
0 c" o3 t* P$ e8 `( y7 X6 c) G
to set-initial-turtle-vars-age& P) m, K: ]7 C3 _' o2 T
let max-wealth max [wealth] of turtles, i* R9 E; y$ {
$ \1 ~/ k6 T! W! u" D7 y ifelse (wealth <= max-wealth / 3), B6 @: S) m- R" ]2 k8 F! d) H
[ set color red : T" F, I7 G7 C' @
set age 0
( ~* K4 P* p3 V: o face one-of neighbors4 ' @, n$ V- o" ~& |/ v: \0 l& Z
set life-expectancy life-expectancy-min +& `0 r1 n% ]) \1 u6 E" ^; v, K
random life-expectancy-max
- V6 q5 l- {, b3 B4 c9 a8 } set metabolism random 1 + metabolism-low
, g# d, N+ ~ W, i' D" p7 L set wealth metabolism + random 30
* Z& D' M" F8 ` set vision 1 + random max-vision
& W" K( @6 T, Z, N! u# P set wealth wealth + Wealth-inherited-low ]
, ]& H% T3 b2 j/ \3 U! r [ ifelse (wealth <= (max-wealth * 2 / 3))
# I$ c ~) M/ p [ set color yellow
- b, _& @/ ^6 S set age 05 n9 D. U1 e/ j, K$ m" \
face one-of neighbors4
: u7 I* G' ~4 I; ^8 D# e! Z% ^ set life-expectancy life-expectancy-min +
# m8 J1 c9 k: a5 W( p2 r3 q/ j: p random life-expectancy-max + 1
) M+ ~7 m5 p( a; [ set metabolism 1 + random metabolism-mid
+ a/ d* ^' ~' C% s2 E- ^+ F. a set wealth metabolism + random 30
9 h$ m/ F/ B& t1 |& y/ ] U set vision 3 + random max-vision
- Y4 t+ x7 M* q& M( Y set wealth wealth + Wealth-inherited-mid]
4 ?1 |2 Y, c4 F [ set color green # j/ y4 ^. b8 T
set age 0 t/ [+ |# c: B0 ^' s+ L: s3 \1 F
face one-of neighbors4
. s& s" }1 c6 d! }* r7 j9 N( [" s5 M set life-expectancy life-expectancy-min +
. w% y& Q' R+ S9 s: N random life-expectancy-max + 22 q& f+ \; M$ ~* r3 z- }, V
set metabolism 2 + random metabolism-up
* Y: r' m1 Y- I1 E set wealth metabolism + random 30
: s) y6 r* m: J6 w* W set vision 3 + random max-vision
% {% S0 ?0 C+ R- K8 d set wealth wealth + Wealth-inherited-up ] ] t; O* n' D; U) X' o% Y( d& y
, b: Y$ ^& W: l8 V$ B
end
5 y3 ~: m0 z- D( B9 | tto set-initial-turtle-vars-wealth* ^& Y7 \* A5 ~( V( t+ |
let max-wealth max [wealth] of turtles8 y5 L2 q% }! a2 Z
set age 0" c: W' w. ?* Y, Y# S( ?4 r
face one-of neighbors4 2 Y+ ?6 N* [$ i( @
set life-expectancy life-expectancy-min +; F: M6 i( p, ^6 W" J
random life-expectancy-max # U* @# {1 M4 g. K( N" G- H
set metabolism 1 + random metabolism-up* t9 ^2 m5 I R( P0 y+ b1 Y
set wealth metabolism + random 30
9 z3 ~( O$ s" P$ W- {) F set vision 1 + random max-vision
4 j: [2 `) s9 i5 xend1 f& H5 Q8 P5 F$ m
to redistribution: i C7 i$ S- K" N
let max-wealth max [wealth] of turtles
* ]$ A G$ u/ |let min-wealth min [wealth] of turtles e. L6 l5 [; _1 D! s4 y
if (wealth <= max-wealth / 3) E$ [5 o/ Q$ { m( y, ^
[set wealth wealth + Low-income-protection ]
1 e& C1 R& V8 ]9 ^end; }2 t; X6 A1 l: a5 N# i* W
% A3 @4 Q, V( r$ O- H" W
to recolor-turtles
; B/ D+ {" Q( `; J% G! [ let max-wealth max [wealth] of turtles8 R/ C7 F$ {1 _2 ^
ask turtles& m, a) k7 F3 O- ]$ a
[ ifelse (wealth <= max-wealth / 3)" N5 ~5 v$ @( ]4 N4 r; f; c7 G! w
[ set color red ]+ B9 U, W& J6 f3 H4 R* S
[ ifelse (wealth <= (max-wealth * 2 / 3))
: m6 K! x0 T0 s" v6 V1 s4 O [ set color yellow ] e! T- Z: U; Q" ~" e
[ set color green ] ] ]" } P) O$ U% x
ask turtles [ifelse show-wealth?
# f. W' g7 [" }' ]" J, J [ set label wealth ]5 b6 C! Z2 J. p! M+ E+ g- _
[ set label "" ]]
9 W& R1 b+ y: k2 K3 W1 V/ f9 ]0 Yend
* M3 {4 }+ G" |# ]) E; C( O0 f4 f6 X7 }+ z3 O# W/ c
to go% e& p% {7 `( [ A. x
ask turtles
- l1 Z5 J. v; V' X5 z+ X+ } [ turn-towards-grain ] + A0 a0 V+ U9 ]( V1 s1 ^4 b
harvest
, |' U- x) Y( x% _. ] ask turtles: U; t: L9 U2 d5 p
[ move-eat-age-die ]3 Z6 f+ S. s }' b1 \" i' [$ U
recolor-turtles
# A- z- X9 b X. z+ h! f if ticks mod grain-growth-interval = 0
9 ?% N8 I- J8 w9 w" _% w/ { [ ask patches [ grow-grain ] ]
" e. T) {* c! d/ W1 y
0 g7 Q4 i8 G( w if ticks mod 11 = 0
3 O d4 p) x' O$ S2 A( Z* a: F [ask turtles
' V, Q- ?7 z8 }1 [9 H6 }" R [ redistribution ]]
6 c4 t; o& ?: g& o if ticks mod 5 = 0( s5 H8 p& r0 z+ m! l
[ask turtles6 M' _2 U u' ?& V0 {2 I1 R( m$ ~
[ visions ]]) t) N" l/ [1 k* P# R( @' _7 o0 K
tick
4 R: n" E4 T! R' Q8 m. P% V4 M update-plots
: G6 q* L5 ~- H( F/ @- G4 n. W* mend
, ~$ \9 Z+ ^. F( e8 E. `1 oto visions
- B) O6 u" J- q- d; H1 k& o5 Y5 T5 b+ P0 b set vision vision + 1 " _- X6 _ m* n* {3 X% |! n3 h- O5 w
end
% [1 e5 V/ s7 g! c, Y- W$ o0 R
' R w1 g3 I6 Z% B7 A Z
. U" e3 w* r6 u* P6 W" d0 t0 N- a- _2 O, f" }& N% d( X2 u- i
to turn-towards-grain
$ O6 q- @5 g; Q3 H set heading 0$ s* Z& I; {' s/ Q
let best-direction 0
6 H; H" o- m( n let best-amount grain-ahead' K7 v$ F* ?4 C$ p+ M; w; }
set heading 90
8 D9 A6 h" X0 V5 s @4 S2 x if (grain-ahead > best-amount)
$ z. A+ Q" j2 U/ ` a [ set best-direction 900 x2 Q8 C6 r- J! e V8 ?
set best-amount grain-ahead ]
: k4 G( ^& v0 C% L set heading 180& u+ i$ J% B, e1 u& h- I0 X+ [ U
if (grain-ahead > best-amount)
. c, S: P2 k$ s" N# a/ G [ set best-direction 180. v" v7 {7 V! s `
set best-amount grain-ahead ]
! C. y- e' l1 B7 x8 V set heading 270
3 n. p; l% x2 |3 Z if (grain-ahead > best-amount)$ d9 |2 w6 ?7 e& l
[ set best-direction 270
6 ~# y1 j) T, l1 {$ ` set best-amount grain-ahead ]- c0 U, f, u- `' z3 s% E
set heading best-direction" {5 f1 B4 m: F; ~
end# A5 p' j4 Y/ Y% c
4 f3 m6 q6 y2 {- F8 a( ~1 |/ I* D5 M6 E
to-report grain-ahead
1 {- [3 R- `- g. N( K% | L let total 0/ B' k( c5 h, W2 [! C* n
let how-far 1
7 Y2 ?% `" d2 U( V2 j/ g5 T repeat vision3 `( g! x# c& c j; x( M
[ set total total + [grain-here] of patch-ahead how-far
5 q v/ Z2 s4 |4 `; x% r* n set how-far how-far + 1 ]
; W$ ]# A+ o0 e+ b# [- y report total
0 k- o. G; E$ @) P% Tend
2 y! E) o7 _- r% X5 E( ^) G2 C" @0 V& J' o Q: h! H
to grow-grain
( J( W9 |9 K! y& v( n7 l) ~ if (grain-here < max-grain-here) G+ b+ z! s9 C+ ` c; K* \6 j
[ set grain-here grain-here + num-grain-grown) S# U+ ^/ N/ b+ {0 \
if (grain-here > max-grain-here)
7 U3 N$ X6 k' C [ set grain-here max-grain-here ]3 c$ Q# i* y1 |, N9 l. i6 \2 h8 W: n
recolor-patch ]
- @3 ~2 f4 |9 |5 L% send( k2 \: i" O1 M/ u
to harvest$ T3 D' J. ^. N \$ Q! a( X: z
ask turtles
; M7 ?9 E% L' g* i$ U9 M [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]! ~2 i: V7 P$ r" a% }& d6 x6 [5 `
ask turtles5 n) Z# P) j7 G
[ set grain-here 0. I, i6 l( D% }
recolor-patch ]% r& {. I e; Y _# \
7 q. P, k r! O* s' a
end' }7 {! E/ ?$ u1 [
t0 U0 h" h. k) s2 k1 Vto move-eat-age-die " L) n2 M9 v& Z* I+ ~! N. l3 _
fd 1
! ^ n: ] t# w$ v set wealth (wealth - metabolism) s A( ?7 c6 j, X
set age (age + 1)8 v ]' @3 z% X4 k/ o
if (age >= life-expectancy)8 u. J9 c3 G6 u& f( F3 \ j" z
[ set-initial-turtle-vars-age ]$ s$ H; }. G9 H: B5 j4 K3 m
if (wealth < 0)+ h9 v2 Y1 U" g$ L1 v* X
[ set-initial-turtle-vars-wealth ]
' \/ I1 {7 S- h: X& a0 I ( r4 K; S2 ~; K
end
0 E* t0 c9 k; q7 J
7 E) Z0 b) [ v' X K/ U5 I9 @1 g
3 ^& R2 N" E5 z; v& kto setup-plots# F( W+ E3 ]% o) v! C
set-current-plot "Class Plot"
3 x7 b u7 v, u5 m* X. G3 m+ P9 \( m set-plot-y-range 0 num-people
9 T$ G: m$ M/ S set-current-plot "Class Histogram"
# |2 g5 G' y) o$ C set-plot-y-range 0 num-people
& _7 G, i) o, }$ x6 V) rend
2 @: A1 g* l7 j2 \6 O
4 `" ~6 g" g6 `8 e2 s3 f" [, ~to update-plots3 p C, t7 i, F7 K' i5 P) l
update-class-plot
/ _7 |1 `! m ^2 K8 u" m update-class-histogram4 D: O2 w: h# Z! u+ k# R6 ?
update-lorenz-and-gini-plots; w; R0 l5 ^# |* |
end, M& p- g$ Q6 R/ x
5 W, v( G+ P. U x4 x+ z; hto update-class-plot
1 ?# d! V) ^- i: a set-current-plot "Class Plot"9 m0 M' p1 @8 a+ h" l
set-current-plot-pen "low": b0 o' T8 P2 S! L- j2 P
plot count turtles with [color = red]1 s+ n& q( q6 {. d3 \! U7 Z& O4 V
set-current-plot-pen "mid"
6 d8 v9 F: n/ ^% P) [ plot count turtles with [color = yellow]% |) @6 \! {& D
set-current-plot-pen "up"
- _8 f" W( D0 ?1 X7 P3 _+ y plot count turtles with [color = green]
* i# L% O( A. h3 r0 a d' k: n6 Send
! o# ], k! @# T' c) Z0 D( \8 N1 ^3 P. M( I5 T
to update-class-histogram$ H* t8 X/ Q! G) c. B* _) ]
set-current-plot "Class Histogram"' z7 L* e% O9 o' z. T
plot-pen-reset
( C% @, j x! T4 e8 a set-plot-pen-color red4 l/ I! M( V/ C3 z: e8 K
plot count turtles with [color = red]! g, x' m/ v' k* ^: w9 y
set-plot-pen-color yellow
3 Y1 F9 i* X/ B* o0 P plot count turtles with [color = yellow]
5 v' S+ P& `# @) B, h set-plot-pen-color green3 s& r6 j& S! A
plot count turtles with [color = green]9 T! V; C, k$ J
end: _! O: D$ u4 I- y! b( t- r
to update-lorenz-and-gini-plots
7 M3 n1 f& C1 W6 {3 | set-current-plot "Lorenz Curve"
. O$ N& p2 q$ x; i clear-plot
% Z% o2 I, N' v4 z7 _4 n
" b# t3 g8 q1 O; D" h set-current-plot-pen "equal"
$ U/ X8 G) d1 C; {8 i% O1 T8 }7 j plot 0
% w( `- ]8 Q; r6 x8 s5 ^" B. P plot 100
8 B0 D3 w1 l. ~6 p4 J, a( m+ ~* J* F' m2 {7 r; ?( `/ I* d e% M
set-current-plot-pen "lorenz"3 ]2 R0 D( v" K7 ]/ |" B# q8 u3 D! V
set-plot-pen-interval 100 / num-people
. { X- J9 |, H5 ^9 S5 A* o plot 04 t1 d, o5 W Z9 `' L- n2 c2 m
$ q2 [! F/ _5 y! f0 a& @* f, V
let sorted-wealths sort [wealth] of turtles6 O8 R" _) o* C6 c9 a
let total-wealth sum sorted-wealths
5 p# r$ U" e3 d4 d. z9 t let wealth-sum-so-far 0# Q8 d S8 I0 }# P" D# F. w9 n% B+ O \0 H
let index 0
4 G# l% D7 D P0 G let gini-index-reserve 0
. C5 M4 w" Y, s% R4 k4 `6 B
, C+ A3 q# e/ t8 O* O repeat num-people [
% Y3 r) T9 a% _+ V1 E$ F" h set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)7 f8 s5 q) I( [2 M k( Z( c; ~) ]
plot (wealth-sum-so-far / total-wealth) * 1004 N! u2 E5 b8 M8 u+ `
set index (index + 1) Z, k1 N/ b. I3 P* T* H
set gini-index-reserve
( [( r. c7 R" v R0 f. I% R gini-index-reserve +! X! O+ t1 m& P, c+ ~
(index / num-people) -
. S! q0 n) K6 j& k5 m. p (wealth-sum-so-far / total-wealth): F. r/ Z- `8 w& P. ^& M
]
. c6 B) v. B m F' m! ~: k/ G1 K1 @3 z- I4 F( D3 I6 k2 O) N
set-current-plot "Gini-Index v. Time"
; ~, x# F, l- \1 e plot (gini-index-reserve / num-people) / area-of-equality-triangle! u0 L. P3 |' ~* @. U7 @ `7 N
end
7 o+ ?" J. `2 \. n, m9 E5 Z5 \to-report area-of-equality-triangle% `) f R7 S$ e; W; i1 s
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)
' [/ ]# t3 U7 B0 U- k4 i7 R) H- Qend |