Dr. Lance Eliot, AI Insider
[Ed. Note: For reader’s interested in Dr. Eliot’s ongoing business analyses about the advent of self-driving cars, see his online Forbes column: https://forbes.com/sites/lanceeliot/]
They are everywhere.
Seems like whichever direction you want to move or proceed, there is some constraint either blocking your way or at least impeding your progress.
Per Jean-Jacques Rousseau’s famous 1762 book entitled “The Social Contract,” he proclaimed that mankind is born free and yet everywhere mankind is in chains.
Though it might seem gloomy to have constraints, I’d dare say that we probably all welcome the aspect that arbitrarily deciding to murder someone is pretty much a societal constraint that inhibits such behavior.
There are thus some constraints that we like and some that we don’t like.
In the case of our laws, we as a society have gotten together and formed a set of constraints that governs our societal behaviors.
In computer science and AI, we deal with constraints in a multitude of ways.
When you are mathematically calculating something, there are constraints that you might apply to the formulas that you are using.
Optimization is a popular constraint.
You might desire to figure something out and want to do so in an optimal way.
You decide to impose a constraint that means that if you are able to figure out something, the most optimum version is the best.
Hard Versus Soft Constraints
There are so-called “hard” constraints and “soft” constraints.
Some people confuse the word “hard” with the idea that if the problem itself becomes hard that the constraint that caused it is considered a “hard” constraint.
That’s not what is meant though by the proper definition of “hard” and “soft” constraints.
A “hard” constraint is considered a constraint that is inflexible. It is imperative. You cannot try to shake it off. You cannot try to bend it to become…