Maria Cristina Peixoto Matos

Game Representation - Code Form

When we analyze a game we want a full representation, i.e., we want to be able to look at a game and perceive all of its details. If it allows us to visualize the respective solution all the better. This aim was the reason for researching a new game representation which is described in this paper. The code form of a game consists mainly in a table containing all of the information with no suppression or “adulteration” with regards to the game. Initially presented at Fifth Spanish Meeting on Game Theory & European Voting Games (Seville 2002), based on examples, code form is put forth in this paper thoroughly. We begin by presenting code form, exemplifying it with four games. We finish proving the existence of Nash Equilibrium in code form games.

Let the games begin and go on

Real life is a bigger game in which what a player does early on can affect what others choose to do later on. In particular, we can strive to explain how cooperative behaviour can be established as a result of rational behaviour. When engaged in a repeated situation, players must consider not only their short-term gains but also their long-term payoffs. The general idea of repeated games is that players may be able to deter another player from exploiting his short-term advantage by threatening a punishment that reduces his long-term payoff. The aim of the paper that supports this abstract is to present and discuss dynamic game theory. There are three basic kinds of reasons, which are not mutually exclusive, to study what happens in repeated games. First, it provides a pleasant and a very interesting theory and it has the advantage of making us become more humble in our predictions. Second, many of the most interesting economic interactions repeated often can incorporate a phenomenon which we believe are important but which are not captured when we restrict our attention to static games. Finally, economics, and equilibrium-based theories more generally, do best when analysing routinised interactions.