Ludovic Claude

Gameplay are actions you can take to influence the market. Some people might call these “strategic moves” or “stratagems”. Most of these actions are typical business activities, but some involve deception, misdirection, or even things that might be considered an abuse of power.

Essential concepts:

• Climate

Climatic patterns are rules of the game. These patterns apply across contexts, regardless of user choice.

• Doctrine

• Gameplay

• Inertia

• Pioneers settlers town planners

A Wardley map is a map of the structure of a business or service, mapping the components needed to serve the customer or user. Wardley maps are named after Simon Wardley who claims to have created them in 2005.

Functional programming has its origins in lambda calculus, a formal system developed in the 1930s to investigate computability, the Entscheidungsproblem, function definition, function application, and recursion. Many functional programming languages can be viewed as elaborations on the lambda calculus. Another well-known declarative programming paradigm, logic programming, is based on relations.In contrast, imperative programming changes state with statements in the source code, the simplest example being assignment. Imperative programming has subroutines, but these are not mathematical functions. They can have side effects that may change a program's state, allowing for functions without return values. Because of this, they lack referential transparency, that is, the same language expression can result in different values at different times depending on the state of the executing programFunctional programming languages have largely been emphasized in academia rather than industry settings. However, programming languages that support functional programming have been used in industry, including Common Lisp, Scheme, Clojure, Wolfram Language, Racket, Erlang, OCaml, Haskell, and F#. JavaScript, one of the world's most widely distributed languages, has the properties of a dynamically typed functional language, in addition to imperative and object-oriented paradigms. Functional programming is also key to some languages that have found success in specific domains, like R in statistics, J, K and Q in financial analysis, and XQuery/XSLT for XML. Domain-specific declarative languages like SQL and Lex/Yacc use some elements of functional programming, especially in not supporting mutable values.Programming in a functional style can be accomplished in languages that are not specifically designed for functional programming, such as with Perl, PHP, C++11, and Kotlin. An interesting case is that of ScalaScala - it is frequently written in a functional style, but the presence of side effects and mutable state place it in a grey area between imperative and functional languages.

Essential concepts: pure functions, referential transparency, evaluation by rewriting, pattern matching, polymorphism, composition, effect isolation

In computer science, functional programming is a programming paradigm--a style of building the structure and elements of computer programs--that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is a declarative programming paradigm in that programming is done with expressions or declarations instead of statements. Functional code is idempotent: a function's return value depends only on its arguments, so calling a function with the same value for an argument always produces the same result. This is in contrast to imperative programming where, in addition to a function's arguments, global program state can affect a function's resulting value. Eliminating side effects, that is, changes in state that do not depend on the function inputs, can make understanding a program easier, which is one of the key motivations for the development of functional programming.

Functional programming has its origins in lambda calculus, a formal system developed in the 1930s to investigate computability, the Entscheidungsproblem, function definition, function application, and recursion. Many functional programming languages can be viewed as elaborations on the lambda calculus. Another well-known declarative programming paradigm, logic programming, is based on relations.In contrast, imperative programming changes state with statements in the source code, the simplest example being assignment. Imperative programming has subroutines, but these are not mathematical functions. They can have side effects that may change a program's state, allowing for functions without return values. Because of this, they lack referential transparency, that is, the same language expression can result in different values at different times depending on the state of the executing programFunctional programming languages have largely been emphasized in academia rather than industry settings. However, programming languages that support functional programming have been used in industry, including Common Lisp, Scheme, Clojure, Wolfram Language, Racket, Erlang, OCaml, Haskell, and F#. JavaScript, one of the world's most widely distributed languages, has the properties of a dynamically typed functional language, in addition to imperative and object-oriented paradigms. Functional programming is also key to some languages that have found success in specific domains, like R in statistics, J, K and Q in financial analysis, and XQuery/XSLT for XML. Domain-specific declarative languages like SQL and Lex/Yacc use some elements of functional programming, especially in not supporting mutable values.Programming in a functional style can be accomplished in languages that are not specifically designed for functional programming, such as with Perl, PHP, C++11, and Kotlin. An interesting case is that of Scala - it is frequently written in a functional style, but the presence of side effects and mutable state place it in a grey area between imperative and functional languages.

Functional code tends to be more concise, more predictable, and easier to test than imperative or object oriented code — but if you’re unfamiliar with it and the common patterns associated with it, functional code can also seem a lot more dense, and the related literature can be impenetrable to newcomers.

Composition is the act of combining parts to make a whole, a program can be expressed as functions built on top of other functions representing different levels of abstraction spanning from human to machine. This fits very well with the instinctive way of solving problems for humans expressed by the idea of divide et impera. A complex problem is divided in smaller and simpler problems that are easier to solve so that the global solution is the combination of all the solutions of the smaller problems. Different programming paradigms slice the problems in different ways depending on the tools used to combine the solutions for the subproblems. Composability is more effective when used on pure functions to avoid the problems deriving from hidden side effects.

The fundamental building block of functional programming is the function application to its input values. A function that associates one and only one value to its inputs without any other effects is called a pure function; that is the function only observable effect on the program execution is the computation of the result given the inputs. A function application is basically a table that maps inputs to outputs. The formalisation of this concept is called referential transparency and is a property of expressions in general, not just functions. This means that you can achieve referential transparency with any language and any paradigm. Referential transparent expressions can be evaluated at any time, this allows us to replace symbols with their implementations and the flow of execution is now not relevant anymore enabling parallel evaluation without the problems deriving from race conditions; on top of this previously calculated results can be cached improving performance at the cost of memory. On a human perspective purity is even more valuable because of our limited capacity to reason.

In functional programming functions are first class citizens and as such they have a prominent role to the point that they can be treated as values and passed as arguments to other functions to produce more complex computations. Functions accepting other functions as parameters or returning functions as the result of a computation are called high order functions.

Modular software is well designed software because it is made of independent components that can be replaced or extended without causing ripple effects while cooperating to deliver value. The key benefit of functional programming is the improved modularisation of code built from smaller, testable and reusable components that can be understood independently. The meaning of the whole depends only on the meaning of the components and on the ways you can combine them; this simplifies the reasoning about the software because functions behave like connected black boxes.