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Lambda calculus cheat sheet
Lambda calculus cheat sheet




lambda calculus cheat sheet

Here, we apply the lambda (λx.x) to the variable y: (λx.x)y What can we do with such a lambda expression? Well we can apply it to another expression (The same way we can apply anonymous functions to an argument in JavaScript). The K combinator which we wrote as x=>y=>x in JavaScript, is written λxy.x. The expression λx.xy is not a combinator, because y is not bound to any parameter, it is free. Thus, the expression λx.x is a combinator because the variable x is bound to the parameter.

Lambda calculus cheat sheet free#

A combinator is a lambda expression (function) with no free variables.We have already discussed combinators in JavaScript, now we can give them a more formal definition: a sequence of nested univariate functions). x y, but they are implicitly curried (e.g. Lambda functions can have multiple parameters in the parameter list, e.g.: λxy.Thus, λx.x is semantically equivalent (or alpha equivalent) to λy.y or any other possible renaming of the variable. The names of variables bound to parameters in a lambda expression are only meaningful within the context of that expression.See the discussion of Church Encodings, below, to see how this is done. It’s lambdas all the way down! However, to actually model and perform useful computations we say that certain expressions represent values. The only values that Lambda Calculus variables can take on is other functions (i.e.Note that anonymous functions in languages like JavaScript and Python are also frequently called lambda expressions, or just lambdas. A lambda expression has no name, it is anonymous.Some things to note about such lambda expressions:

lambda calculus cheat sheet

When we discussed combinators in JavaScript, we gave this function a name. Here is a simple Lambda Abstraction of a function:

lambda calculus cheat sheet

It is worth looking at this notation before studying haskell-like languages because it was the inspiration for Haskell syntax. Lambda Calculus expressions are written with a standard system of notation. The operations we can apply to Lambda Calculus expressions to simplify (or reduce) them, or to prove equivalence, can also be applied to pure functions in a programming language that supports higher-order functions. The Lambda Calculus is also important to study as it is the basis of functional programming. It has been proven that, as a model of computation, the Lambda Calculus is just as powerful as Turing Machines, that is, any computation that can be modelled with a Turing Machine can also be modeled with the Lambda Calculus. However, while the Turing Machine is based on a hypothetical physical machine (involving tapes from which instructions are read and written) the Lambda Calculus was conceived as a set of rules and operations for function abstraction and application. You are probably aware of the more famous model for computation developed around the same time by Alan Turing: the Turing Machine.

lambda calculus cheat sheet

The Lambda Calculus is a model of computation developed in the 1930s by the mathematician Alonzo Church. Apply conversion and reduction rules to simplify lambda expressions.Relate the lambda calculus to functional programming.Understand that the lambda calculus provides a complete model of computation.






Lambda calculus cheat sheet