The Hard Problem is a term used in computer science to describe the most difficult and complex problems. It is generally considered to be the most difficult class of problems in computing, as a result of their intricate nature and complexity.
The term “Hard Problem” is often credited to the computer scientist Edsger Dijkstra, who is also known for his work on algorithms and data structures. It was introduced in his 1972 paper “On the Role of Scientific Thought in Computer Science”, where he wrote: “The hard problems are the ones that have resisted our best efforts to solve them, and remain so for the indefinite future, rather than those that simply require a great deal of effort.”
Hard problems can become even more difficult and complex due to the emergence of new technologies or because of an unexpected development. For example, it may require merging new technologies or combining information from disparate sources. Depending on the complexity of the problem, the solution may be non-trivial and require significant effort and time from more than one person.
Hard problems are widely researched, and published in diverse fields, including mathematics, engineering, computer science, artificial intelligence, robotics, and cognitive science. Solutions to hard problems are typically high level and often lead to new breakthroughs and innovations.
The hard problems are often studied to find possible solutions that could be applied to other fields or used in new problem-solving approaches. In many disciplines, solving hard problems is the ultimate objective.
