# Wikipedia for Formal Science

What we are after is a
Wikipedia for Formal Science or formally-specified computations
where the participants claim interpreted predicate logic
sentences (without free variables, a.k.a. **claims**) used to specify
computations as well as theorems that hold in a
formal science.
## Semantic Games

Users can contribute by participating in
semantic games
for claims
where they take **sides** and exchange objects (** examples ** and **counterexamples**).
This way, **without proofs,** they can
objectively defend their own **contributions** and
**dispute** the contributions of others.
Semantic games provide an objective approach to evaluate users
and make it **fun** for users to contribute
to Formal Science and Computations.

Using Hintikka's words: "Semantic games are outdoor games. They are played among the objects
of the language one speaks, and they consist largely of the
choices the two players between different objects"
(page 38 of "The Principles of Mathematics Revisited").

## Modularity

One interpreted predicate logic formula (with
free variables) defines a **lab** (laboratory, corresponding to
a Wikipedia for Computations page) consisting of a **claim family**
and several scholars contributing to the lab.
We use **lab relations** (such as lab reductions)
to solve computational problems using modularity.
## Reflection

We can crowdsource any formally specified component of our system
to improve the system through crowdsourcing
**(crowdsourcing a crowdsourcing platform).**
Ahmed's Thesis Proposal describing the details.

##
Claim Family Examples for the Formal Science Wikipedia

### SaddlePoint

SaddlePoint(c) = ForAll x in [0,1] Exists y in [0,1]: x*y+(1-x)*(1-y*y)>= c.

This claim family SaddlePoint(c) consists of infinitely many claims.

####
Status

Somewhere near c=0.618 is a tipping point.
SaddlePoint(0.618) has been consistently defended by avatar GoodYear.
SaddlePointLab1(0.619) has been consistently refuted by avatar Henry.
### Highest Safe Rung

See http://www.ccs.neu.edu/home/mohsen/for-karl/HSR.ppt
HSRqk(q in Nat, k in Nat where k<=q)=
// note the order: q comes first, k is constrained by q.
Exists n in Nat where n <= 2^q: (HSR(n,k,q) and (ForAll n' > n, n' in Nat: !HSR(n',k,q)).

HSR(n,k,q) there is an experimental plan for a ladder with n rungs, k jars and a maximum of q questions to determine the highest safe rung. (That means the depth of the experimental plan, represented as a tree, is q.)

HSRnk(n,k)= Exists q in Nat < n: (HSR(n,k,q) and (ForAll q' < q, q' in Nat: !HSR(n,k,q'))

### SCG Tournament Design

Design tournaments that find the good semantic game players quickly.
### LocalGlobal

LocalGlobalSat(2,c) : The fraction c of the clauses that can be satisfied in any 2-satisfiable CNF formula.
Reduces to SaddlePoint.

### PartialSat

PartialSat(R,c(R)), R is a set of relations: The fraction c of clauses
can be satisfied in any boolean CSP formula whose clauses have constraints taken from R?
### MinVertexBasis

minVertexBasis(G) : Given a graph G, is there a minimum vertex basis size for G?
### AlgorithmWorstCase

AlgorithmWorstCase(A,n): is there a worst case running time for A on inputs of size n?