Why is there uncertainty in combinatorial proofs?

In summary, the conversation discusses the issue of uncertainty in solving combinatorial problems and the lack of formal proofs in the field. The speaker also mentions that they have observed even experienced students and teachers making mistakes in combinatorial solutions. They ask for recommendations on the most rigorous treatment of enumerative combinatorics. The responder notes that this uncertainty is also present in other fields, such as when doing long symbolic manipulations or considering numerous cases, and asks about the speaker's interest in combinatorial problems.
  • #1
s.hamid.ef
7
0
There's something I can not understand about proofs in combinatorics. Whenever I solve a counting problem, there's a non-negligible amount of uncertainty about the solution which I really don't feel when I solve problems in other fields, say in analysis or abstract algebra. It happens too often that someone sees my solution and tells me I've counted more or fewer than the correct answer. And I've observed this happens even to more experienced students and even teachers. But every time we come to a general agreement after refining the solution.
What's wrong with me? Or does it have anything to do with how it's presented? I've never seen an axiomatic treatment of this field, like say, abstract algebra. Of course all the books I've seen start with the two counting principles, but they seem like too informal to use in rigorous proofs.


Thanks in advance.
 
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  • #2
You should supply some sort example of what you are concerned about.
 
  • #3
Hi Mathman,
I'm not concerned about any particular examples, and now I'm realizing it's not as common an issue as I thought. I guess I need to gain more experience in the field before I can compare it to other fields.
Anyways, what's the most rigorous treatment of enumerative combinatorics you ( and others!) know?
 
  • #4
s.hamid.ef said:
Hi Mathman,
I'm not concerned about any particular examples, and now I'm realizing it's not as common an issue as I thought. I guess I need to gain more experience in the field before I can compare it to other fields.
Anyways, what's the most rigorous treatment of enumerative combinatorics you ( and others!) know?
I have no answer for your question.
 
  • #5
s.hamid.ef said:
There's something I can not understand about proofs in combinatorics. Whenever I solve a counting problem, there's a non-negligible amount of uncertainty about the solution which I really don't feel when I solve problems in other fields, say in analysis or abstract algebra.

I share your feeling. I also note that in threads about complicated combinatorial problems we often see fairly skilled people make "small" mistakes in the answers they propose and get corrrected by others. Often it is a technicality about how the English statement of the problem is to be translated into precise requirements. In the field of combinatorics, what we see on math forums are usually the solutions to problems, not formal proofs. I haven't read enough formal proofs of combinatorial results to form an opinion about the formal proofs.

However, there is a similar uncertainty when solving problems that involve doing long symbolic manipulations by hand, or problems that involve considering a large number of different cases. Do you enjoy combinatorial problems? I've never been interested in the kind that just count the number of ways. I do have an interest in algorithms that actually generate a list of all the ways.
 

FAQ: Why is there uncertainty in combinatorial proofs?

What is combinatorics and why is it important in proofs?

Combinatorics is a branch of mathematics that deals with the study of counting and arranging objects. It is important in proofs because it provides a systematic way of organizing and analyzing the possibilities of a given problem, making it easier to prove or disprove statements.

2. What are the basic principles and techniques used in combinatorial proofs?

Some of the basic principles and techniques used in combinatorial proofs include the fundamental counting principle, permutations and combinations, and the pigeonhole principle. Other techniques such as induction, bijections, and double counting may also be used.

3. How do you know when to use a combinatorial proof?

A combinatorial proof is typically used when a problem involves counting or arranging objects, or when the statement to be proven can be represented in terms of combinations or permutations. It is also often used when a problem involves a finite set of objects or cases.

4. Are there any common mistakes to avoid in combinatorial proofs?

One common mistake to avoid in combinatorial proofs is overcounting or undercounting the possibilities. It is important to carefully consider all cases and make sure that each possibility is only counted once. Another mistake is making incorrect assumptions or generalizations without proper justification.

5. Can combinatorial proofs be used in other areas of science?

Yes, combinatorial proofs can be applied in various areas of science such as computer science, physics, and biology. In computer science, combinatorics is used in algorithms and data structures. In physics, it is used in statistical mechanics to study the behavior of large systems. In biology, it is used in genetics and evolutionary biology to model and analyze biological processes.

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