Talk:List of unsolved problems in computer science

message: "A problem in computer science is considered unsolved when an expert in the field (i.e, a computer scientist) considers it unsolved or when several experts in the field disagree about a solution to a problem" seems unnecessary, since most of the problems on the list require exact, non-subjective solutions.  — Preceding unsigned comment added by 177.82.37.234 (talk) 05:20, 15 September 2016 (UTC)
thread_title:  Unnecessary definition 

message: The original speedup section is posted verbatim in this section below my objections.  As stated it appears to confuse the meaning of "speedup" used in the "speedup theorem" (which allows one to achieve a "speedup" by changing the alphabet size -- and potentially causing a combinatorial explosion in the (still finite) number of states in the FSM component of the turing machine) to the notion of "speedup" used by a programmer performing constant-factor optimizations on a fixed-architecture machine.
As stated the problem appears to be fairly close (up to a constant factor) to the problem of finding asymptotic lower bounds to the running time of all correct solutions to a class of problems.  The common way to refer to the class of "asymptotic lower bound" problems is to call it "the field of computational complexity thoery."  It should be noted that the other (two at the current point!) "open problems in computer science" listed on this page are both from the domain of computational complexity theory, although it would be nice (in addition to having a solution to P vs. NP) to have a general mechanism for finding hard lower bounds on classes of problems, which appears to be what the original "speedup" section was asking for ;).
To what degree can one speed up a computation?
;Field : High-performance computing
;Description : Although the speedup theorem from computability theory shows that any computation can be sped up by any desired constant degree, there is no feasible method of gaining such a speedup. It is needed to know what are the techniques and bounds on speedup in various architectures - a single processor, grid, distributed network, etc.
;Importance : The speed of computation is the limit to the problems that we can solve.
;Conjecture : Amdahl's law is a partial answer to the question. —The preceding unsigned comment was added by Mschures (talk • contribs) 05:54, 20 December 2006 (UTC)
thread_title:  Deletion of speedup section 

message: Wouldn't A = B * C be a simple one-way function? Any functions which takes two inputs and produces only one output is impossible to reverse unless one of the input parameters are known.
- Andrew Price
:When people on cryptography say one-way function, it is usually implied that it is possible, although difficult, to invert the function. In fact, if you add the assumption that B and C are prime numbers (so that there is only one solution), the problem you describe is a very likely candidate for a real simple one-way function. It is easy to multiply two large numbers, however it is very difficult to factor a large number into its two primes. There are lots of places to read more on this topic. Meekohi 14:35, 7 August 2006 (UTC)
replies: text: Just last night I read about the use of the logical OR (inclusive) to destroy any chance of reversability. But I can't remember where I read it. I.e. given a state machine with multiple entries into a state, we cannot retrace how the machine came its current state. But where the hell did I read this? I bet it was Minsky (1967).wvbaileyWvbailey 15:20, 31 August 2006 (UTC)
thread_title:  Simple one way function? 

message: This page needs a major rewrite.  The problems seem randomly chosen, and there seem to be few factual errors:
a) "If one-way functions exist then public key cryptography is possible."  This is simply wrong; as far as we know OWFs do not imply public key encryption (they do imply signatures, though).
b) "the speedup theorem from computability theory shows that any computation can be sped up by any desired constant degree".  This is also wrong.  That is not at all what the speedup theorem shows.
:Feel free to make edits; one should be bold here. --Mgreenbe 11:18, 30 January 2006 (UTC)
replies: text: I know i can make edits.  But even if I invest the time to fix the errors here, I still would think that this page should rather be deleted.  A random collection of some open problems is worth less than no collection at all, in my opinion.
I am sorry, but I do not have the time required to make this a good page.[unsigned, undated]
I think this is a fun and useful page, kind of in the spirit of Hilbert's problems. Read the talk page of Turing machine re the problem of what is and is not "computable" by what, i.e. analog vs digital/logistic computation. The page just needs more input.wvbaileyWvbailey 20:33, 16 August 2006 (UTC)
thread_title:  Overall 

message: One would think that "algorithm" is a perfectly-understood word. I too was surprised. Not so: in the same way the Church-Turing thesis is unresolved we see the need for a definition of what an algorithm really truly is/is not. For example see the work of Blass and Gurevich (2003) Algorithms: A Quest for Absolute Defintions (exact reference to be found at algorithm -- can be gotten off the microsoft website). I will add this after a while if no one objects.wvbaileyWvbailey 20:33, 16 August 2006 (UTC)
thread_title:  Add "definition of algorithm" to the list 

message: At one time there were more entries focused on technique and simulation and the practive of computer science.  Now the page has devolved into a mathamatical discussion.  I would much prefer a list like the unresolved problems in physics list.
Ggb667 14:40, 31 August 2006 (UTC)
replies: text: I agree that the list doesn't seem fully representative of known problems in computer science.  I'd recommend the INFOSEC Research Council's Hard Problems list at http://www.infosec-research.org/docs_public/20051130-IRC-HPL-FINAL.pdf for a source of unresolved open problems in the computer security domain. I have to believe there are lists of known problems in other domains, particularly software engineering. --Sgorton 05:12, 5 February 2007 (UTC)

text: Agreed. It paints a depressing picture of the field that these are the only problems significant enough to make it to this list. If this were truly the case, all computer scientists could pool efforts on P=NP, declare computer science solved, and go find something else to do! I'd add some myself, but the problems I'm currently working on are far more esoteric (and far less important) than the ones listed here. Metasquares 18:44, 29 July 2007 (UTC)

text: I would like to suggest bold edits. Any problem whose resolution is a publishable result belongs to this page. If the list becomes to long, we merely create relevant subpages and categorize properly. If only so much work is intended, obviously entries that cover more important, well-known, many et.c. problems are more valuable, i.e. it is more valuable to write an article on BPP=NP? than something less popular such as E=AM?, or even better Deciding relationship between Complexity Classes. C. lorenz (talk) 12:55, 26 January 2008 (UTC)
thread_title:  Need many more entries 

message: I've placed some of the categories - those relating to specific problems - against the section heading rather than at the end of the article which would be in accord with the WP:MOS.  The reason is to make the article easier to maintain.  As problems are added and removed the categories will change and if they're not associated with a particular problem then we'll end up with the article being in inappropriate categories.  Placing the category entries in the corresponding section is the simplest way to do this.  It's not essential, but clean. -- JDX 05:19, 29 September 2006 (UTC)
thread_title:  Style, categories, qualifications 

message: Source:
In the article "Prospects for Mathematical Logic in the Twenty-First Century", Sam Buss suggests a "three-fold view of proof theory" (his Table 1, p. 9) that includes in column 1, "Constructive analysis of second-order and stronger theories", in column 2, "Central problem is P vs. NP and related questions", and in column 3, "Central problem is the "AI" problem of developing "true" artificial intelligence" (Buss, Kechris, Pillay, Shore 2000:4).
: "I wish to avoid philosophical issues about consciousness, self-awareness and what it means to have a soul, etc., and instead seek a purely operational approach to articial intelligence. Thus, I define artificial intelligence as being constructed systems which can reason and interact both syntactically and semantically. To stress the last word in the last sentence, I mean that a true artifical intelligence system should be able to take the meaning of statements into account, or at least act as if it takes the meaning into account." (Buss on p. 4-5)
He goes on to mention the use of neural nets (i.e. analog-like computation that seems to not use logic -- I don't agree with him here: logic is used in the simulations of neural nets -- but that's the point -- this stuff is open). Morever, can I am not sure that Buss can eliminate "consciousness" from the discussion? Or is consciousness a necessary ingredient for an AI? 
Description: 
Mary Shelley's Frankenstein) and some of the stories of Edgar Allen Poe (e.g. The Tell-Tale Heart) opened the question. Since the 1950's the use of the Turing Test has been a measure of success or failure of a purported AI. But is this a fair test? [quote here?] (Turing, Alan, 1950, Computing Machinery and Intelligence, Mind, 59, 433-460. http://www.loebner.net/Prizef/TuringArticle.html 
A problem statement requires both a definition of "intelligence" and a decision as whether it is necessary to, or if so how much to, fold "consciousness" into the debate.
> Philosphers of Mind call an intelligence without a mind is a zombie (cf Dennett, Daniel 1991, Consciousness Explained, Little, Brown and Company, Boston, -1 (pb) ):
: A philospher's zomie, you will recall, is behaviorally indistinguishable from a normal human being, but is not conscious. There is nothing it is like to be a zombie; it just seems that way to observers (including itself, as we saw in the previous chapter). (italics added or emphasis)" (Dennett loc cit:405) 
Can an artificial, mindless zombie be truly an AI? No says Searle:
:"Information processing is typically in the mind of an observer . . . the addition in the calculator is not intrinsic to the circuit, the addition in me is intrinsic to my mental life.... Therefore, we cannot explain the notion of consciouness in terms of information processing and symbol manipulations" (Searle 2002:34). "Nothing is intrinsically computational. computation exists only relative to some agent or observer who imposes a computational interpretation on some phenomenon" (Searle 2002:17).
Yes says Dennett:
:"There is another way to address the possibility of zombies, and in some regards I think it is more satisfying. Are zombies possible? They're not just possible, they're actual. We're all zombies [Footnote 6 warns not to quote out of context here]. Nobody is conscious -- not in the systematically mysterious way that supports such doctrines as epiphenomenalism!"((Dennett 1991:406) 
> Gandy 1980 throws around the word "free will". For him it seems an undefined concept, interpreted by some (Sieg?) to mean something on the order of "Randomness put to work in an effectively-infinite computational evironment" as opposed to "deterministic" or "nondeterministic" both in a finite computational environment (e.g. a computer). 
>Godel's quote: "...the term "finite proceedure" ... is understood to mean "mechanical procedure". concept of a formal system whose essence it is that reasoning is completely replaced by mechanical operations on formulas" ... [but] the reuslts mentioned in this postscript do not establish any bounds for the powers of human reason, but rather for the potentialities of pure formalism in mathematics."(Godel 1964 in Undecidable:72)  
Importance:
> AC (artificial consciousness, an AI with a feeling mind) would no less than an upheavel in human affairs
> AI as helper or scourage or both (robot warriors)
> Philosophy: nature of "man", "man versus machine", how would man's world change with AI's (robots)? Will it be good or an evil act to create a conscious AI? What will it be like to be an AI? (cf Nagel, Thomas 1974, What Is It Like to be a Bat? from Philosophical Review 83:435-50. Reprinted on p. 219ff in Chalmers, David J. 2002, Philosophy of Mind: Classsical and Contemporary Readings, Oxford University Press, New York .)
> Law: If conscious, does the AI have rights? What would be those rights?
Current Conjecture:
An AI is feasible/possible and will appear within this century.
This outline is just throwing down stuff. Suggestions are welcome. wvbaileyWvbailey 16:13, 6 September 2007 (UTC)
replies: text: The central question for computer science is: Can every aspect of intelligence be simulated by a machine? (See the rewrite in progress of philosophy of artificial intelligence) ---- CharlesGillingham 08:59, 10 October 2007 (UTC)
thread_title:  Artificial Intelligence 

message: This is a holding place for the following. The intent is not to push this or any other point of view, but to make the question evident. A number of epistomologic and mathematical issues bubble up from this:
: from https://research.microsoft.com/~gurevich/
:[164] Andreas Blass and Yuri Gurevich
:"Algorithms: A Quest for Absolute Definitions"
:Bulletin of the European Association for Theoretical Computer Science
:Number 81 (October 2003), pages 195-225. 
:Reprinted in Chapter on Logic in Computer Science
:Current Trends in Theoretical Computer Science
:World Scientific, 2004, pages 283-311 
:Reprinted in Church's Thesis After 70 Years
:Ontos Verlag, 2006, 24-57
:See more details here 
::What is an algorithm? The interest in this foundational problem is not only theoretical; applications include specification, validation and verification of software and hardware systems. We describe the quest to understand and define the notion of algorithm. We start with the Church-Turing thesis and contrast Church's and Turing's approaches, and we finish with some recent investigations.
:wvbaileyWvbailey 00:48, 5 September 2007 (UTC)
thread_title:  Algorithm: what is such a beast? 

message: I have removed the above section because the idea that this is a problem appears to be a minority view; the consensus view appears to be that Turing's property is a reasonable formalization of a vague common language idea; as is not uncommon. See logical implication for a similar formalization of the natural language word if.
This may belong under Church-Turing thesis - but not here. Septentrionalis PMAnderson 23:42, 13 September 2009 (UTC)
replies: text: Wrong. You may not agree with it, but your disagreement is not of much interest here. The issue is supported by the references. Bill Wvbailey (talk) 00:29, 14 September 2009 (UTC)
replies: text: Well, I don't agree with it either. It is a minority view. None of the textbooks I have read share this view of the CT thesis. --Robin (talk) 00:35, 14 September 2009 (UTC)

text:  It's an interesting line of research, but few pursue it. I agree with User:Pmanderson and User:RobinK; also User:Miym had a similar opinion. This is indeed a valid topic at the CTT article, but it's not even considered a formalizable problem by most to include it here as an open problem. Pcap ping 02:49, 14 September 2009 (UTC)
replies: text: There seems to be a failure of communication here. Your personal opinions are not of interest. The sourced quotations are the matter of interest. If there's dissent, you need to produce the beef --  a quotation, in print, in a quotation here on this page. Bill Wvbailey (talk) 03:33, 14 September 2009 (UTC)
replies: text:  Requested citations from books:    . Let's put it the other way around too: can you cite a non-WP:PRIMARY source, e.g. a book, saying that formalizing the CTT is feasible or an important open problem? Pcap ping 04:59, 14 September 2009 (UTC)

text:  Besides, Dershowitz and Gurevich claim they have actually proved CTT  from their axioms on page 306, so how can you claim it is still unsolved based on their paper? Pcap ping 05:25, 14 September 2009 (UTC)

text:  I saw nothing in your tertiary references that have anything to do with axiomatizing the notion of computation so the CTT can be proved or disproved. All I saw was a discussion of the thesis. Hell I can come up with dozens of those discussions. You know the strange thing is, this all started with Goedel who suggested it to Church. But anyway, as the statment of the problem actually says (you might want to re-read it), Dershowitz and Gurevich do claim their axiomatization. But this is a primary source, is it not? So it's okay for you to quote from one, and not okay for me? Interesting. I don't understand your aversion to primary sources, especially when bound into reviewed volumes. Quite often they contain secondary source material in the way of comments, and observations, criticism, references etc. You're way off base with regards to their use, and from what I could gather at the chatter, others agree with me. As I'm certain I'm not going to pursuade you, this discussion is closed as far as I'm concerned. I've got better things to do with my time. Wvbailey (talk) 12:37, 14 September 2009 (UTC)
replies: text: Pcap is not alone; caution in using primary sources - especially, as here, on whether they represent a consensus position - is policy. Septentrionalis PMAnderson 16:41, 14 September 2009 (UTC)
replies: text:  Forget about subtle balancing of opinions from different sources. Just using a paper that clearly says that we've solved it to claim that it's an open problem is basically WTF?! to me. Pcap ping 17:31, 14 September 2009 (UTC)
thread_title: Removed

message: Does the scope of this article include recursion theory? I could add a handful of the most important problems from that area, if it is relevant here. — Carl (CBM · talk) 11:04, 14 September 2009 (UTC)
replies: text: This poor article . . . its history shows that the same three problems "Prove or disprove the Church-Turing thesis", "P-NP", and "One way functions", have been there since 25 Oct 2004 (and it wasn't me who put them there -- I started editing in January 2006). And that's it. I remember seeing Go and a few others, but they've been deleted. Probably its scope should be expanded if it is going to survive as an article. Maybe "Unsolved problems in computatibility" or something of that sort. My favorite is the Collatz Conjecture, but can we argue that that is a computer science problem? I would call it a recursion/computability problem, and a gnarly one at that (the last significant result I saw was Liesbeth De Mol's Tag systems and Collatz-like functions but that was from a couple years ago when I was working on it). Bill Wvbailey (talk) 13:14, 14 September 2009 (UTC)
replies: text: Feel free to add open problems related to recursion theory and computability. Collatz conjecture sounds like a good addition to me, especially as we already have a Wikipedia article about it. I don't mind if there is some overlap between this page and Unsolved problems in mathematics. Please don't rename; "Unsolved problems in computability" is much more narrow than "Unsolved problems in computer science", cf. Outline of computer science. — Miym (talk) 13:47, 14 September 2009 (UTC)
replies: text: The Collatz conjecture can be settled by computation only if it is false and the minimal counterexample is not of unreasonable magnitude; even then, its applicability to computer science is unclear.  I would be extremely cautious of adding it here. Septentrionalis PMAnderson 16:45, 14 September 2009 (UTC)
replies: text: A proof would probably not proceed by exhaustive search -- this has been done, with the surprising result that most of the "bad action" is in the lower numbers, e.g. 27, where "3n+1" almost explodes, but doesn't quite -- things get more orderly with larger numbers. (Other coefficients such as 5n+3 are fair game, and some cofficient'assignments cause "explosions", and some lapse into loops. Also negative coefficients are fair game. An absolutely fascinating problem; BTW this is all in the literature).  A proof may follow along the lines of De Mol. To quote her: "a method will be described to reduce the 3n+1-problem to a tag system which is surprisingly small . . . these result will be related to some findings concerning the reducibility of Collatz-like functions to Turing machines studied in the context of the boundaries of solvability in Turing machines." Goedelization such as used by Minsky 1967 text in his proofs is possible, I've worked with counter machines, etc etc. I should think that efforts in this regard could fall into the realm of "theoretical" as opposed to "applied" computer science (De Mol wrote this from "The Centre for Logic and Philosphy of Science" in Gent, Belgium). Bill Wvbailey (talk) 12:47, 15 September 2009 (UTC)
thread_title:  scope 

message: Lets assume, for the purpose of argument, or in order to prove a contradiction that I have reduced a broad category of NP problems to P problems in P time.
and I assert that I have solved it for NP problems.
What should I do?  Have I already done it, here today?  If not why?  Mathiastck (talk) 17:07, 31 January 2010 (UTC)
replies: text: I am not sure quite what you mean. P itself is a broad category of NP problems, and every one of them can be reduced to P in P-time. — Carl (CBM · talk) 23:11, 31 January 2010 (UTC)
replies: text: Yeah I totally don't even know what I was thinking then either.  Nevermind! Mathiastck (talk) 23:14, 11 February 2010 (UTC)
thread_title:  P==NP 

message: I remember seeing a news article recently saying that this problem has been solved and that the result was bad news for computing speed. Is that the case? Abyssal (talk) 02:24, 16 August 2010 (UTC)
replies: text: Take a look at P_versus_NP_problem#Claimed_solutions - looks like it's not solved yet. -pinkgothic (talk) 15:42, 3 September 2010 (UTC)
replies: text:  How about this:? http://kafcsn.org.ua/lang/en-us/anatoly-d-plotnikov-professor-department-computer-systems-and-networks-east-ukrainian-national-university-solved-the-problem-p-vs-np.html ? "See also" User_talk:David_Eppstein#Explanation_Re_edit_to_.22P_vs._NP.22_article and User_talk:Yellowdesk#Explanation_Re_edit_to_.22P_vs._NP.22_article . ...Thank you, --Mike Schwartz (talk) 22:50, 24 September 2012 (UTC)
thread_title: P = NP?

message: Is there any real sense in which the POPLmark challenge is still an "unsolved problem"? If nobody objects, I'm going to delete it.Erniecohen (talk) 03:42, 14 April 2017 (UTC)
thread_title:  removal of POPLmark? 

message: Computers are the devices which manipulate, operate, analyse, and does other tasks at the same time as multitasking, including storing information. But, do we know that the things invented by humans will have definitely some standard errors? And so computers have! How can a computer verify and solve a problem in the same polynomial time? can we solve and verify a problem in the same polynomial time? Bringing a solution and verification to a problem depends on the size of the problem, speed taken by the object(including humans and computers) in the problem, length of the problem, efficiency of the object in the problem, its power usage, its memory usage, number of ways in the problem, external factors like input and output factors and its capacity, often as energy. One should not think that an object can solve and verify a problem at the same polynomial time, because, no object can do anything with 100% efficiency. And so, like us, computers also cannot solve and verify a problem at the same polynomial time due to this. And so, I can say that always P≠NP in this same way.
Note : Since I am young, studying higher secondary second year, please refer this, and if this gives any clue regarding mysteries, try to spread with this and even try to research about this, my dear brothers. For any purposes regarding this, send via email ID as follows : msusendran@gmail.com, email ID of publisher of this topic.2409:4072:6116:6893:4D30:D4F8:E2BE:8B34 (talk) 17:10, 17 July 2018 (UTC)
thread_title:  Computers and Unsolved Problems 

message: This article includes a list of unsolved problems in natural language processing, though the description of these problems is somewhat vague. Is it true that the problems listed in this section are still unsolved? Jarble (talk) 10:48, 29 January 2019 (UTC)
thread_title:  Unsolved NLP problems 

message: The question Can the fast Fourier transform be computed in o(n log n) time? must be a typing error, as the answer is obviously yes.  Presumably the question should instead be Can the fast Fourier transform be computed in faster than o(n log n) time?.  — Preceding unsigned comment added by 165.225.80.233 (talk) 16:44, 19 February 2020 (UTC)
replies: text: Not a typo. Notice that the  is lowercase. This is little o notation. The question Can this problem be solved faster than ? is equivalent to Can this problem be solved in  time? Rzvhkon (talk) 07:51, 23 December 2020 (UTC)
thread_title:  Typing error about fast fourier transform? 

message: Photogrammetry software exists but seems to require alot of compute power or does not update the 3d model in realtime, especially if the 3d objects are moving while new images come in. Augmented reality often only detects position of camera(s) to mount virtual objects into while requiring handheld input devices since the cameras do not detect the Human body precise or fast enough. This may be because more efficient algorithms are not known. 2600:6C5E:1C7F:3889:4887:FFA8:A854:C4CF (talk) 17:23, 12 July 2021 (UTC)
thread_title:  bigO of making a 3d model from multiple 2d pics 

message: Are computer answers acceptable to add if they solve these questions?
For example 
While asking the bot at 
https://huggingface.co/spaces/codellama/codellama-13b-chat
Can integer factorization be done in polynomial time on a classical (non-quantum) computer?
Answer: 
No, integer factorization cannot be done in polynomial time on a classical (non-quantum) computer. This is because the running time of the algorithm increases exponentially with the size of the input, which is a property of the integer factorization problem.
In particular, the integer factorization problem is known to be NP-hard, which means that it is at least as hard as the hardest problems in NP. This means that if a polynomial-time algorithm for integer factorization were discovered, it would immediately solve all problems in NP, which would have profound implications for the field of computer science.
There are several reasons why integer factorization cannot be done in polynomial time on a classical computer. One reason is that the running time of the algorithm increases exponentially with the size of the input. For example, if the input is a number with n digits, the running time of the algorithm will be at least O(2^n), which grows exponentially with the size of the input.
Another reason is that the integer factorization problem is closely related to the hardness of other problems in NP, such as the decision problem for the group of units of a number field. These problems are known to be NP-hard, which means that they are at least as hard as the hardest problems in NP. This means that if a polynomial-time algorithm for integer factorization were discovered, it would immediately solve all problems in NP, which would have profound implications for the field of computer science.
Overall, while it is possible to solve integer factorization problems in practice using algorithms that are not polynomial time, it is not possible to solve them in polynomial time on a classical computer. 31.161.145.232 (talk) 19:44, 5 September 2023 (UTC)
thread_title:  Answers by computer