We wanted to remind everyone that there are now added bonus goals for total BTC raised. To requote it,
< 400 BTC- 10% on buyback, 15% on dividends
400/+ BTC - 11.5% on buyback, 18% on dividends
500/+ BTC - 13% on buyback, 21% on dividends
600/+ BTC - 15% on buyback, 25% on dividends
Shortly following the initial sale, after we have completed testing with our beta testers, we will be releasing a prototype game which will act as a simple prototype for what we're developing. At the start, we will issue a test currency to make sure if anything goes wrong or works as intended nobody loses any real money while testing this. Perhaps going forward, we can offer testing of various things in the future as a sort of faucet for LIR however this is still currently being discussed.
We think that it's important that our users understand how provably fair games work and what the point of making them provably fair is. A provably fair game means the client (the user) has control over some variable which affects the outcome of their roll. Given this, once the server variable is released at the end of each day a client can go back and verify that the number they rolled was indeed the correct number there by making it provably fair. To ensure the server doesn't cheat by changing it's variable, the server must provide a hashed value of it's hidden variable prior to releasing it. The third variable used is called the nonce which is a value that continuously increments as the user continues to make rolls.
Simply put, there exists some function R such that it produces a real number between 0 and less than 1
In layman terms, there are three variables:
C - Client Seed: which you have control over and can be changed arbitrary
N - Nonce: A number that goes up after each roll
S - Server Seed: A hidden variable held by the server until the end of each day
H(S) - Hashed Server Seed: A hashed version of S so that you can verify that when the server releases S, it is indeed the correct value.
Using the three variables, you generate a number between 0 and 1 (for example: 0.222, 0.442, 0.25, 0.89, 0.9912, etc.)
To then produce a satisfiable result, you can then use following calculation to generate a number between min and less than max
((max-min)*r+min) // where min <= max
Card games (as someone asked) are a little different. Several rolls are actually involved in a card game. What makes a card game provably fair is how the deck is shuffled. The verifiable method for this is checking how the deck was shuffled. One example of a simple algorithm that can be applied here is the Fisher Yates shuffle. Taking our previously defined function R,
i = deck.Count; // usually 52 depending on game
while (i > 1)
{
i--;
r = R(C,S,N++)
j = floor(deck.Count * r)
temp = deck[j]
deck[j] = deck[i]
deck[i] = temp
}
Of course, you then need to define some known hashing function so that you can produce a deck-hash to the client has some reference point of knowing if they were cheated.
Please remember, we are still recruiting beta testers! We've already brought on a few people, however we are still looking for about 5 so reach out to me via
[email protected]Thanks for the trust and investments, we have less then 53 hours left in the sale and we look forward to it completing and moving onto the next stage of this venture.
