WHEN RULE-BASED MODELS NEED TO COUNT Pierre Boutillier - Ioana - PowerPoint PPT Presentation

K S a i p pa m WHEN RULE-BASED MODELS NEED TO COUNT Pierre Boutillier - Ioana Cristescu - Walter Fontana http://kappalanguage.org 1

KAPPA MIXTURE y y P EGFR EGF EGFR l c r c r y P EGFR EGF EGF y c r l l EGFR y EGF c r EGFR EGF l P l c r y EGF EGFR EGF l y EGF l c r EGFR l c r 2

A KAPPA MODEL P y y EGF @ k EGFR EGFR EGF l l r r EGF EGF l EGFR EGFR l @ k’ c r EGFR c r EGFR c r c r … 3

PATTERNS VS SPECIES P y y EGF @ k EGFR EGFR EGF l l c r c r y EGF y EGF l EGFR EGFR y l y @ k’ c r EGFR c r EGFR c r c r … 4

P y y EGF @ k EGFR EGFR EGF l l c r c r y EGF l EGFR y y B C c r EGF EGFR EGFR y l c r c r EGF EGFR l c r y A EGF EGFR l c r EGF P P l y y E D EGFR EGFR y y c r c r EGF EGF EGFR EGFR l l c r c r 5

EGF EGF l EGFR EGFR l @ k’ c r EGFR c r EGFR c r c r EGF EGF l l EGFR EGFR c r EGFR c r EGFR c r c r

DISTINCT SITES 7

CASE STUDY 8

COUNTERS • Declaration: C(p: 0 += 8) • Equality test: C(p: 1) • Inequality test: C(p:> 2) • Increment/Decrement: C(p += -1) 9

COUNTERS MACHINERY n n n n succ succ succ A c succ succ A c p p p p p Incr succ A c succ A c Decr p p n succ p 10

EFFICIENCY 10^5 events simulation KaSim 3 counters KaSim 3 no counters 200.0 200.0 200.0 200.0 KaSim 4 counters KaSim 4 no counters 50.0 50.0 50.0 50.0 ● ● 20.0 20.0 20.0 20.0 ● time 10.0 10.0 10.0 10.0 ● ● ● 5.0 5.0 5.0 5.0 ● ● ● ● ● ● ● ● ● 2.0 2.0 2.0 2.0 ● 1.0 1.0 1.0 1.0 ● 0.5 0.5 0.5 0.5 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8 8 8 8 9 9 9 9 10 10 10 10 11 11 11 11 12 12 12 12 nb phos site 11

THOUGHTS ON TRIVIALITY • a posteriori triviality is not a priory triviality • an easy encoding is not an easy language extension 12