An interesting take on Pascal's Wager.
I think Homer may just be on to something here.
= new reply since forum marked as read
Biblical admonitions against gambling:
"Deception:
Legal gambling operations are steeped in deceit. Lotteries that conceal or misstate the odds, casinos without clocks or windows to hide the passage of time, slot machines programmed for "near misses," and "riverboat" casinos that cannot sail are but a few examples. Scripture, on the other hand, detests deceitful conduct (Psalm 5:6: "You destroy those who tell lies; bloodthirsty and deceitful men the Lord abhors."
. Indeed, Jesus describes Himself as the embodiment of truth (John 14:6) and Satan as "the father of lies" (John 8:44).
See also Psalms 26:4, 55:23, 101
; Proverbs 14:8, 12:20, 24:28; Romans 1:29.
Avoiding temptation:
Gambling establishments are often host to other corrupting vices, including prostitution and drunkenness. Christians are urged to avoid such environments (1 Thessalonians 5:22: "Avoid every kind of evil." . In 1 Corinthians 15:33, Paul writes, "Do not be misled: 'Bad company corrupts good character.'" Other Scriptures warn believers to flee temptation (1 Corinthians 6:18, 2 Timothy 2:22).
Lack of trust in God:
The Bible teaches that Christians are to look to God as their provider, and that we are to be content with the material blessings we receive from His hand. To engage in gambling indicates both a lack of trust in and dissatisfaction with God's provision.
See, for instance, Matthew 6:25-34; Philippians 4:11-12, 4:19; 1 Timothy 6:6; Hebrews 13:5."
Read more: http://www.beliefnet.com/Faiths/Christianity/2003/05/Gambling-And-The-Bible.aspx#ixzz1j0wNbxcL
Or if we want to avoid the loaded word, what "if the answer to Einstein's question "is universe a benevolent place?" is yes, then what? or if it is not, then...? What if my answer, being part of the universe, affects the more general answer, then... ? etc.
And if we reduce these questions to the logic circuits of a Turing machine, we already know that they reduce to what is called the halting problem, which has been proven undecidable:
"In computability theory, the halting problem can be stated as follows: Given a description of a computer program, decide whether the program finishes running or continues to run forever. This is equivalent to the problem of deciding, given a program and an input, whether the program will eventually halt when run with that input, or will run forever.
Alan Turing proved in 1936 that a general algorithm to solve the halting problem for all possible program-input pairs cannot exist. A key part of the proof was a mathematical definition of a computer and program, what became known as a Turing machine; the halting problem is undecidable over Turing machines. It is one of the first examples of a decision problem."
"Importance and consequences
The halting problem is historically important because it was one of the first problems to be proved undecidable. (Turing's proof went to press in May 1936, whereas Alonzo Church's proof of the undecidability of a problem in the lambda calculus had already been published in April 1936.) Subsequently, many other undecidable problems have been described; the typical method of proving a problem to be undecidable is with the technique of reduction. To do this, it is sufficient to show that if a solution to the new problem were found, it could be used to decide an undecidable problem by transforming instances of the undecidable problem into instances of the new problem. Since we already know that no method can decide the old problem, no method can decide the new problem either. Often the new problem is reduced to solving the halting problem.
For example, one such consequence of the halting problem's undecidability is that there cannot be a general algorithm that decides whether a given statement about natural numbers is true or not. The reason for this is that the proposition stating that a certain algorithm will halt given a certain input can be converted into an equivalent statement about natural numbers. If we had an algorithm that could solve every statement about natural numbers, it could certainly solve this one; but that would determine whether the original program halts, which is impossible, since the halting problem is undecidable.
Rice's theorem generalizes the theorem that the halting problem is unsolvable. It states that any non-trivial property of the partial function that is implemented by a program is undecidable. (A partial function is a function which may not always produce a result, and so is used to model programs, which can either produce results or fail to halt.) For example, the property "halt for the input 0" is undecidable. Note that this theorem holds only for properties of the partial function implemented by the program; Rice's Theorem does not apply to properties of the program itself. For example, "halt on input 0 within 100 steps" is not a property of the partial function that is implemented by the program—it is a property of the program implementing the partial function and is very much decidable.
Gregory Chaitin has defined a halting probability, represented by the symbol Ω, a type of real number that informally is said to represent the probability that a randomly produced program halts. These numbers have the same Turing degree as the halting problem. It is a normal and transcendental number which can be defined but cannot be completely computed. This means one can prove that there is no algorithm which produces the digits of Ω, although its first few digits can be calculated in simple cases.
While Turing's proof shows that there can be no general method or algorithm to determine whether algorithms halt, individual instances of that problem may very well be susceptible to attack. Given a specific algorithm, one can often show that it must halt for any input, and in fact computer scientists often do just that as part of a correctness proof. But each proof has to be developed specifically for the algorithm at hand; there is no mechanical, general way to determine whether algorithms on a Turing machine halt. However, there are some heuristics that can be used in an automated fashion to attempt to construct a proof, which succeed frequently on typical programs. This field of research is known as automated termination analysis.
Since the negative answer to the halting problem shows that there are problems that cannot be solved by a Turing machine, the Church–Turing thesis limits what can be accomplished by any machine that implements effective methods. However, not all machines conceivable to human imagination are subject to the Church–Turing thesis (e.g. oracle machines are not). It is an open question whether there can be actual deterministic physical processes that, in the long run, elude simulation by a Turing machine, and in particular whether any such hypothetical process could usefully be harnessed in the form of a calculating machine (a hypercomputer) that could solve the halting problem for a Turing machine amongst other things. It is also an open question whether any such unknown physical processes are involved in the working of the human brain, and whether humans can solve the halting problem.[2]"
http://en.wikipedia.org/wiki/Halting_problem
With benevolent interpretation and respect to Pascal's mathematical and logical philosophical abilities, his theological wager can be seen as a precursor of the halting problem. Or in more simple terms, taking into consideration that if universe treats you the way you treat universe, then it's better to treat universe as a benevolent place. 