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
! ]: q/ `7 D& r) A5 n# rglobals
1 o( z% [( P0 w! G8 E[/ Q" v* h6 i5 ~( i; K! `7 j
max-grain * v [+ M# ~; x+ h* v$ z X
% X$ v. k+ h6 A0 v1 ~ ^]* _# D( M6 O( z `/ r
3 C# @, P u( v& N H; s, q7 Ppatches-own
+ j. {3 ^& X4 X0 W( }[
7 o. x' T4 D8 Y/ d0 {! d3 J" y* F grain-here
. p, M/ l* O: z" L' M- l/ B max-grain-here
. i6 I$ l7 d) e) ?" a4 i]
[; u2 J; x3 ?0 h3 e
, S& K1 V9 G }, U9 pturtles-own
4 m( H2 u5 Y; W6 l, n( W, ], I[
6 M* c6 c) A: G1 Q3 p+ Q age ( \, [. {$ U, S* @; S7 Z; W
wealth
2 _) v+ q$ r$ c, f, J8 i life-expectancy
# d- x+ Z( o, j metabolism % ^3 n5 l' G/ i( s; }4 u! a
vision
: y- o! R* _0 `$ X! z' g inherited
0 k/ V! m O( a! s]& K+ j, }0 J' z
+ s7 [$ b8 k; {3 M7 M$ z; `* ^% k. T* C5 V2 T6 c: j
to setup, }: H" V+ ?$ U; @
ca7 Q! P* Y2 z$ R# k' I
set max-grain 50: z# b7 ^* ~6 R- Y% E2 I; v0 ~9 F
setup-patches- X6 `6 I' T' [" i% {- l
setup-turtles0 c* J! ]' |& i: c' y0 U
setup-plots: T2 |: @6 f* I3 ^2 _/ T S5 L
update-plots
3 W( ~* m/ @% i; ~5 I/ Q t" Fend# [1 f, r& G8 x
to setup-patches+ S- G+ x) B5 i
ask patches
- g/ f1 n- ~2 R1 z+ G [ set max-grain-here 0
7 V2 C2 @$ y% }4 B if (random-float 100.0) <= percent-best-land
+ L% I1 F4 V+ H* {6 ? [ set max-grain-here max-grain
, q+ ?& y7 M; C! E) ^: p set grain-here max-grain-here ] ]
% ^+ I$ X" Y- p; K7 M0 v repeat 50 ]' m% L u- G# H0 z
[ ask patches with [max-grain-here != 0]
8 T' G3 V% `: K. H [ set grain-here max-grain-here ]
* E3 b! A7 H+ H6 ^ diffuse grain-here 0.5 ]
- z# \4 N6 c9 s1 c repeat 10! ^8 M" L& q3 U- u, Y7 w( |8 V
[ diffuse grain-here 0.5]
0 G7 m9 A5 z5 L ask patches3 x% z1 G. l! l/ V' ?
[ set grain-here floor grain-here
( G# c; x( [6 Q, k set max-grain-here grain-here 6 H# Y$ |# W" g8 N. d3 [' n8 m
recolor-patch ]. g, [# \+ u6 N; `/ h6 T
end8 r( @& X( N- |- t0 s6 O0 L0 v/ y
to recolor-patch
. ~$ d- ?9 G: L( c$ e8 s# I set pcolor scale-color sky grain-here 0 max-grain* h% e' o2 o: {
end
9 l5 X. B W7 ], r) rto setup-turtles
) y, z: d+ ~7 ?. K& a% b3 a5 ~ set-default-shape turtles "person"2 H+ M9 k% @& S4 J
crt num-people
8 l8 H$ Q* N5 R4 y [ move-to one-of patches
J+ f7 N+ s/ Y8 x8 p set size 1.5
7 b" b9 J5 y% ?9 x: r set-initial-turtle-vars-age8 q2 R1 S) F( v/ ]
set-initial-turtle-vars-wealth6 |/ \8 M D1 A0 u* o& k
set age random life-expectancy ]
5 c1 N8 C! r, c8 _3 I. a% u recolor-turtles
: W5 u5 k2 M5 k0 O( K/ {end" f, c7 \ T1 `% N% C1 \, d. ?
% u, y8 Y2 M: q' D7 |to set-initial-turtle-vars-age
( s& N8 u$ K6 t6 c' n. o- o" } let max-wealth max [wealth] of turtles
. A7 k0 }' L" @! P- a 2 h& o+ Q2 E4 t% s) ^& u5 _+ f
ifelse (wealth <= max-wealth / 3)
; t8 R, ~3 `0 T9 h, Z5 t [ set color red " `5 X9 W7 A$ W7 b7 m }
set age 0
|! s) \, ^; E- L- f# ? face one-of neighbors4 9 c/ o9 Y, D0 U5 j: n* u
set life-expectancy life-expectancy-min +5 t8 {# b3 W, \) N
random life-expectancy-max
4 T% `5 [1 w. [' D+ q, [6 s set metabolism random 1 + metabolism-low
/ I F; t+ D2 A set wealth metabolism + random 30
# |) E; L0 L4 B4 X- R8 z set vision 1 + random max-vision4 J, E" [) w& @* }+ o. h. c- S# {
set wealth wealth + Wealth-inherited-low ]1 S0 J! b4 v3 p' q( a) ^
[ ifelse (wealth <= (max-wealth * 2 / 3))
( `9 J/ M$ {0 ~, F. d0 p7 U' z [ set color yellow + B; O) z7 u; O; b7 x& _. O5 |
set age 0& E/ [1 @2 k# t1 U, u5 c f
face one-of neighbors4 0 S+ K& p2 ~- U% Y7 H2 _
set life-expectancy life-expectancy-min +" }1 v; a2 Z( s; v" b
random life-expectancy-max + 1
/ t; o1 b, S1 u: |: m1 @ set metabolism 1 + random metabolism-mid
2 `8 Z, `) S7 I1 X8 f! `7 H1 V- p set wealth metabolism + random 30
G% g9 |; F) P9 A- R8 G; Z" G; z set vision 3 + random max-vision
% X1 r; q. M( n" C( } set wealth wealth + Wealth-inherited-mid]& ?5 e/ U, _5 G7 Q! [# G
[ set color green & R4 A/ P; y' A3 E/ `
set age 0+ m4 q% d+ K( h( |! }$ d8 |4 H) b
face one-of neighbors4 o3 y# y) F3 u7 {! d& Z* U
set life-expectancy life-expectancy-min +' k! \ ?! v/ M4 [; l
random life-expectancy-max + 21 [2 a% @ l4 `0 h' t
set metabolism 2 + random metabolism-up q' X5 z5 {) G, Y
set wealth metabolism + random 30* [ J( y/ _6 a7 D( I$ `6 U
set vision 3 + random max-vision3 O. o* O4 t: m9 D$ K: ]
set wealth wealth + Wealth-inherited-up ] ]
6 S7 e! g2 O4 L& _ + K3 l' t- j u* U# ]
end) G: V/ _% n! Y
to set-initial-turtle-vars-wealth( P& y6 g; t& Y7 }5 P8 o; O& a, u
let max-wealth max [wealth] of turtles
* Y$ Y. h) O% l8 O4 M# P* s- J set age 04 V h m8 S4 o. w: ^* T! @
face one-of neighbors4
6 t1 ?+ n. k) P6 ` set life-expectancy life-expectancy-min +
$ E. Z2 m% V0 G# j2 K r random life-expectancy-max
9 R( K+ f, Z% T5 b set metabolism 1 + random metabolism-up
* _/ ]( l& c& P2 t2 |, g! n8 X/ M set wealth metabolism + random 30
; z$ O3 D9 t) p3 m( g& F w- w set vision 1 + random max-vision
. s' w$ Z- {. B! A* ?end+ y7 P, e; K1 u3 D
to redistribution3 e, }! S; d1 W
let max-wealth max [wealth] of turtles
. o( D* v( \4 Elet min-wealth min [wealth] of turtles& Q# z# [# `- h% p- N' P9 ]
if (wealth <= max-wealth / 3) _; B+ Q, X+ m1 O; p7 I/ S2 @8 t6 Y
[set wealth wealth + Low-income-protection ]4 Z+ L3 ^2 }1 P
end8 i- J% m1 m. _7 P
* G" a3 p, v- W# s. s8 Lto recolor-turtles
# @3 D2 A3 k2 P; x' _ let max-wealth max [wealth] of turtles
s7 w# E/ i+ T& y \ ask turtles
* E+ I) M0 c7 ~! n, \ [ ifelse (wealth <= max-wealth / 3)
( s' d+ \' \! T R3 ^8 W [ set color red ]8 z3 b+ k9 r7 S. ?
[ ifelse (wealth <= (max-wealth * 2 / 3))
& |! j0 d. S3 \1 _1 D [ set color yellow ]
! |- I& A5 [# n/ P [ set color green ] ] ]
$ I5 k" w2 t# [7 M5 f! ^* {3 X ask turtles [ifelse show-wealth?! |( T1 z5 _, |/ b u
[ set label wealth ]
& ]# i! M4 F3 f% Z! [, d0 s' x [ set label "" ]]
3 }! z/ S6 k) o, f* J: G' Wend
9 o% K. R2 @: G+ w/ x% ^4 z3 a: K0 n; i7 D9 ?, @
to go9 h$ t, e D) D* I
ask turtles- |5 A, S$ l! O: ^! R. S7 u
[ turn-towards-grain ]
" F. `% m$ W! \" j1 | g3 Q harvest/ h6 c" @/ G- x% _9 n
ask turtles
; \1 R; s) A+ I. O9 x5 L0 a [ move-eat-age-die ]
1 O, U" Y5 E" L& { recolor-turtles3 E5 g5 ~" g) U' g: X
if ticks mod grain-growth-interval = 0; C5 k7 M8 q3 a' t* g- s% d
[ ask patches [ grow-grain ] ]3 P% {+ @: x( W9 X5 |$ P
6 _$ o6 U* P7 J, S% C' r6 \3 p
if ticks mod 11 = 0+ _4 n* X. P R/ s- B8 T* x
[ask turtles
+ x) ]- d0 d1 |, v# r& ` [ redistribution ]]
, `+ p# |, U& ~0 ~ j& w if ticks mod 5 = 0( B- {# L& d* u: T. p/ U. s, B* o
[ask turtles
) t& R) @, B) D* T' a [ visions ]]
/ e- i. n. q G2 ^$ R+ ^ tick
+ ]. R6 ^$ J' k, @0 C6 u5 b) w update-plots
- k% o+ V6 U0 s- V- lend
/ {- M7 O$ I }0 Ato visions# k: \. Q" Y% R$ h! V# W
set vision vision + 1 $ o6 `! L$ G2 w+ O
end
+ [3 O+ q4 n4 p9 L; r6 B: p
' N# R" ]! T- Q P5 f5 q9 _% H; Z8 C0 p. G0 Y
+ x9 m% a) i0 C! l3 w" B
to turn-towards-grain
* @: r+ w, U+ r6 `8 l k set heading 0
, W) }1 _5 u+ a$ w0 \ let best-direction 07 r8 R2 t& {. e0 m2 N! ^4 o
let best-amount grain-ahead. H* y) W+ p$ o' c
set heading 90
& @0 d% M- Q( x" s6 X if (grain-ahead > best-amount)
# g x; i! x3 e0 A; V [ set best-direction 90
* M& ^6 c; C! u/ y9 k$ \5 i/ F9 f set best-amount grain-ahead ]
' }) J* T: t- b8 p5 Y* a) u set heading 1807 _+ Y6 k: {/ D! r1 Z& T
if (grain-ahead > best-amount)& B4 a9 ~; J0 _! `) L
[ set best-direction 180
. {: I7 ]) O* w/ f# k, d0 S/ h set best-amount grain-ahead ]
3 T }0 ~1 r7 ]# {; w3 i+ k set heading 270
! G6 b6 m( i) L) b if (grain-ahead > best-amount)
6 I _% r3 x6 \ [ set best-direction 270
) t- j! ]* `* m K set best-amount grain-ahead ]
. B% `& g& a4 V set heading best-direction2 @/ z, [- f7 U3 g
end4 T# t7 T f; B4 o- i1 c
' y- v. ]4 V6 X, H8 U l
( f( Q) Q4 |/ K& b- Xto-report grain-ahead - u- }$ u3 x: N0 U' E: O! b) G
let total 0
' E- `& L4 P: r0 ~- z9 E' j9 I let how-far 1+ ?6 N B$ H% H
repeat vision
8 m9 s' j2 ~: F* s [ set total total + [grain-here] of patch-ahead how-far) a1 t4 M; F$ ~+ W4 b; E# \& t- T
set how-far how-far + 1 ]& ~2 L! b( {* J- e3 m4 \9 E
report total6 B/ R0 y( ?9 Q" L
end
2 J1 ^* c2 \5 J8 v" |5 x, p) A2 k( S$ H) M
to grow-grain 8 b. i+ Y7 w6 d- E, ]$ W
if (grain-here < max-grain-here)
9 S- M3 n* S9 d+ j [ set grain-here grain-here + num-grain-grown1 O' m. o* ]/ M. i/ f; O+ a" f
if (grain-here > max-grain-here) ( I# i9 |3 C+ x
[ set grain-here max-grain-here ]* U- s; N, {0 f- T7 v
recolor-patch ]0 ]# V8 _. B: _6 i; @( J& a U
end
5 K- h |. x: _8 w! dto harvest
# D7 W& k% T! b8 ? ask turtles
7 o$ O0 U- k6 ~ [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]0 p+ \4 X3 L" G7 {
ask turtles
0 R1 a. f2 u( i1 l* Q [ set grain-here 0
( b9 K8 y* L3 D- D+ p9 D6 \/ m recolor-patch ] G: S) o: M; R3 G" K* O
/ y: v( r" p) W# Q8 d( m8 z/ iend. t9 m4 o ?$ K6 `3 Q, `0 x; M
3 @; R% B. f4 H" V
to move-eat-age-die , }, l, J& y" r4 n$ X
fd 1% F# M: |( A( B# ^2 t$ U6 |
set wealth (wealth - metabolism)7 V- q/ X, J4 ?! y. R
set age (age + 1)
% R- D. ]! G( G6 [# ~7 v if (age >= life-expectancy)# R `' E7 R$ M& ^6 _
[ set-initial-turtle-vars-age ]
% L) _$ R5 p/ h3 v) y' h, r if (wealth < 0)
9 U# o7 V3 ^/ H: r [ set-initial-turtle-vars-wealth ]8 _* P4 A$ z( ]; x; }' R; W7 a
1 F4 Y I, a5 }
end
2 S4 ^' f8 d4 r6 ]5 k
, m* D# I7 a6 n, I0 e
; m% T* ?( Z w2 D4 d; s; ]- yto setup-plots y9 E& v" a+ x3 |( U
set-current-plot "Class Plot"
0 J5 ]0 \0 X6 M- t: C: _7 Z set-plot-y-range 0 num-people: C8 Q# a& h& Y# r
set-current-plot "Class Histogram"
$ ]: f7 W9 s; q) e, K4 k( Q set-plot-y-range 0 num-people* i$ r5 |; a2 k1 z; u# ?5 g% }
end
1 t, s' h" G& V4 h$ L2 ?4 v0 s9 C9 A9 H7 U
to update-plots
- j+ W8 h' l3 p3 q update-class-plot
! o; q4 O+ i: i) S; i: [ update-class-histogram
3 B H# W7 ?, X, Q update-lorenz-and-gini-plots/ n1 c/ i Q/ X5 P. w) t- [$ N2 y
end8 M4 y# Y$ }! t$ Q0 T! ?, [ j
! Z' x6 [# j+ Zto update-class-plot5 l6 G9 w- F1 M
set-current-plot "Class Plot"
# D* j3 [6 X. p set-current-plot-pen "low") K4 j2 z# u6 j! ]' y% d
plot count turtles with [color = red]" y: [1 r* H( k2 A4 V, I# q
set-current-plot-pen "mid"/ o0 S, V2 h3 D- r* H$ I L
plot count turtles with [color = yellow]( ~5 h- N# C$ }3 s" [" {. l, W! E
set-current-plot-pen "up"
$ g' {$ M/ K# j. }( l/ B plot count turtles with [color = green]/ C3 D# [; P9 \! q J; k3 T0 W
end
6 P! _ Z7 B- T6 X) c6 ~4 G C7 ]
/ r0 Z( S1 s* c) z. D, @( Y! p9 Xto update-class-histogram0 z& |- T# `7 `6 ?& H- N H9 K. U4 k
set-current-plot "Class Histogram"# u/ D% `& t' L: F4 i
plot-pen-reset) G6 q% P1 b4 t7 {; ^) q; ~
set-plot-pen-color red6 `% U0 u6 x2 ?4 Z- b! Z0 U
plot count turtles with [color = red]
5 G" N2 ^/ i4 D set-plot-pen-color yellow) k0 t; |5 e. o) ]1 g) s
plot count turtles with [color = yellow]/ s7 ?" Y3 b" W6 z5 m! b( a8 L
set-plot-pen-color green
, Q& e6 T) F1 \% `9 L plot count turtles with [color = green], c, W* I7 b3 e' t
end" s' v+ ]/ J% X$ _2 j6 k
to update-lorenz-and-gini-plots/ k- g! b' t7 @: V& _- n8 N
set-current-plot "Lorenz Curve"
; }; C1 ]! q/ M7 V clear-plot% f- V0 }3 d7 z$ t0 W! F. Q
% G2 J# d" _. V
set-current-plot-pen "equal"
& x7 e6 A3 p5 A( c plot 0
1 h/ l" d! y. M4 R plot 100% z# g! g( E) \/ h: C8 w. i
, K7 r* }0 Z6 k- t8 E
set-current-plot-pen "lorenz"# g0 K/ i0 z" d( H; H2 \
set-plot-pen-interval 100 / num-people Q" P8 N6 \0 A" ^
plot 04 y2 x0 K% |! H
: c+ g+ m( u. A/ H let sorted-wealths sort [wealth] of turtles8 v$ S6 k6 j- M5 b8 z' C
let total-wealth sum sorted-wealths
: u: V/ Q- f; r let wealth-sum-so-far 03 Y2 s9 \% V7 L1 w! C3 d# X1 i
let index 00 c: f6 M: y3 H
let gini-index-reserve 0
Z. N6 a \, \2 ]0 J5 i: R M2 {6 r* e/ f% M: ~3 @8 ]
repeat num-people [
) V. r% n, K* x+ r, M3 @+ _) m set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)/ c4 F7 |- U4 s& S8 F4 N
plot (wealth-sum-so-far / total-wealth) * 100' {+ h* t. |0 q4 S. t( a- N9 D4 B
set index (index + 1)
0 ?9 A7 N/ o+ G# c" N5 A set gini-index-reserve! J1 d) j$ H2 {
gini-index-reserve +
* r! g. s# V7 Q. [% a3 h5 q- o* W' o (index / num-people) -! a; w6 O6 W& b" G- o( |3 G3 V
(wealth-sum-so-far / total-wealth)
6 V$ W# |! R/ c( _' N0 `+ C ]# K. e( h9 E# m& y$ E+ q
0 `4 q; [1 r) v3 v
set-current-plot "Gini-Index v. Time"/ O7 D9 ]1 H% @4 N7 S0 V8 V8 r5 j
plot (gini-index-reserve / num-people) / area-of-equality-triangle
" Q: k! O2 U& c: ^end1 t, E) \* d, R
to-report area-of-equality-triangle
4 j* T1 s! z) a* |2 p2 Y" m report (num-people * (num-people - 1) / 2) / (num-people ^ 2). r! {# L! q- Y& h
end |