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Mathematical Modeling Mathematical Modeling

Mathematical Modeling - PowerPoint Presentation

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Mathematical Modeling - PPT Presentation

Carsten Schürmann DemTech April 8 2015 IEEESA VSSC16226 Objective Implementation Administrative Processes Software Legislation Law Logical Framework Data Computation Logic Properties ID: 483345

ballots logic logical framework logic ballots framework logical hopeful uncounted count case logics presentation ballot declarative candidate system properties

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Slide1

Mathematical Modeling

Carsten Schürmann

DemTech

April 8, 2015

IEEE-SA VSSC-1622.6Slide2

Objective

Implementation

Administrative Processes

Software

Legislation

Law

Logical Framework

Data

Computation

Logic

Properties

ProofsSlide3

1. Discourse

Voting Protocol

Cryptography

(Privacy, Security)

Statistics (Audits)Logic (Distribution, Implementation)Social Choice Algorithms Complexity

ImpossibilityUtilitySlide4

2.

Style

Algorithmic

A

lgorithm + control flowJustify the adherence with “specification”DeclarativeDescribe the algorithm, no control flowJustify the adherence with “specification”

AbstractDescribe the “specification”Slide5

3.

Audience

The Public

Assumptions of common knowledge

Levels of abstractionExpertsCompleteness (no choice left to imagination)Soundness (must make sense)Courts

VerifiabilityDispute resolutionSlide6

Logical Framework ToolBox

Logical Framework

Data

: Votes, Ballots, Totals

Computation

: AlgorithmsSlide7

Pictoral Presentation

“A picture says more than 100 words”

Examples: Category Theory, Geometry, TrigonometrySlide8

Declarative (Algebraic) Presentation

Constructive Logics:

“If there is a solution then there is a program that actually computes it!”

Let

P=(

x

P,yP

) and Q =(xQ,y

Q)Define R = P + Q

where R = (xR,yR)

Case 1:

P

Q

and

–P

Q

x

R

= s

2

x

P

x

Q

y

R

= –

y

P

+ s(

x

P

x

Q

)

s = (

y

P

y

Q

)/(

x

P

x

Q

)

Case 2:

-

P = Q

P + Q = ∞

Case 3:

P

=

Q

P+ Q = 2P Slide9

Dataflow Presentation

s = (

y

P

– y

Q)/(xP – x

Q)xR

= s2 – x

P – xQ y

R

= –

y

P

+ s(

x

P

x

Q

)

R = (

x

R

,

yR)

P = Q

-P = Q

R = (2xR, 2yR)

R

= ∞

P=(

x

P

,y

P)

Q =(

x

Q

,y

Q

)Slide10

Formal Presentation

Logics

Intuitionistic Logic

Linear Logic

Temporal Logic

Dynamic system Model CheckerType theories

Active area of researchCoq, Agda, TwelfTool support essential“A formalization of Elliptic Curves” in CoqSlide11

Logic ToolBox

Logic

Properties

: Requirements, Specifications

Proofs

: Arguments, EquivalencesSlide12

Logics

For all points P + Q it holds:

P + Q = Q + P

And in the Coq system:

First-order logic

KeY

system

Higher-order logicsTemporal LogicModel CheckerType theoriesActive area of researchCoq, Agda

, TwelfSlide13

Case Study

First-Past the Post

Logical Framework: Linear Logic

“The Logic of Food” * -o

Logic: First-order LogicSlide14

Objective

Implementation

Administrative Processes

Software

Legislation

Tally all ballots for each hopeful candidate.

Logical Framework

Data

ComputationSlide15

Declarative Statement

If you

count ballots

find an

uncounted ballot

for Cwhere C

is still in the racethen increase C’s tally and continue counting

count-ballots (U + 1) H

*uncounted-ballot C

*hopeful C N -o (hopeful

C

(

N + 1

)

*

count-ballots

U

H

)

Number uncounted ballots:

U

Number hopefuls:

H

Name of a candidate: C

Number of ballots in a tally:

N

Propositions:

count

-ballots

U

H uncounted-ballot

C hopeful C

NSlide16

Objective

Implementation

Administrative Processes

Software

Legislation

Tally all ballots for each hopeful candidate.

Logical Framework

Data

Computation

LogicPropertiesProofsSlide17

Abstract Specification:

Each Vote is Counted OnceSlide18

Conclusion

Narrowing the gap between law and

maths

Laws easier to interpret, implement

CompletenessSoundnessAnalysis becomes easierLong term benefits