Networks

Multiplayer gaming creates networks of social interaction. Online multiplayer gaming creates massive networks of social interaction. Throughout all of the interactions that occur among these links, players on both sides of the interaction make choices. The referenced reading talks about one of the major decisions a player makes – whether or not to exploit a glitch, or more generally whether or not to cheat. The reading goes on to explain how this decision is very close to a classic prisoner’s dilemma. If player A cheats and player B does not, player A is hugely rewarded (player A has a competitive advantage). The other way around, player B is hugely rewarded. If neither player cheats, both are somewhat rewarded (fair enjoyable gameplay), and if both cheat, both are punished (unfair assumingly not enjoyable gameplay). The assumption here is that the Nash Equilibrium will cause both players to cheat resulting in a loss for everyone. Fortunately game developers generally try to minimize cheating the best they can, but these situations can be generalized a bit more. What if the act wasn’t cheating, but was playing the game in a way that players generally deemed socially unacceptable. This includes actions like throw spamming in Super Smash Brothers (repeatedly using a somewhat overpowerful move) or camping in a first person shooter (hiding in a single spot and guarding the entrance). Essentially this means that games are difficult to balance, and these types of decisions will exist in many games. Of course, in these types of cases, it isn’t easy to quantify the outcomes. Maybe playing with cheats just seems like a different mode to players. To make the situation more complicated, the players may also value these outcomes differently. Player A might love the mayhem that results when everyone cheats. Player B may hate it.

The article goes on to describe how certain factors can play into the decision making apart from the immediate reward and punishment. It states that players will generally not exploit the game when they think they will be playing the same people in the future or they will be interacting with them outside of the game. Unfortunately these are only guidelines, can anyone say screen watchers (in a local multiplayer game, players sometimes look at other players’ screens to gain information that is meant to be private)? Overall the article gives us a good look of a real life example of the prisoner’s dilemma and how these dilemmas are often more complicated then the generalized cases that we learn. We can analyze the case further, however, to ask how these situations shape the social network itself. We can consider a single closed game where all players are connected to each other. We could imagine these connections are either positive or negative depending on if each player chooses to exploit the game. Some natural situations will probably arise. A group of fair players may gang up to defeat a cheater (creating a situation that’s similar to a positive edge with two negative edges). All the players may play fairly (creating a situation that’s similar to all positive edges). The final most natural state (given by Nash Equilibrium) is where all the players lower themselves to exploiting the game. But what kind of social network does this create? One where all edges are negative? One where the exploitation doesn’t factor into the positive or negative aspect? In a general case, the majority of these people won’t enjoy playing the game where everyone cheats. Consequently, it seems like the case where all edges are in fact negative connections. But this means the Nash Equilibrium is causing a state that leads to an unbalanced network. This is when players realize they have more than two choices and quit the game. This eventually leads to an interesting conclusion. Overtime, all of the online players tend to split up into multiple separate networks. The people who enjoy a fair game play with each other; the people who enjoy cheating play with each other. This is the concept of dedicated servers and lobbies. This is where players who have preferences on types of gameplay can meet with each other and only worry about playing the game in that way. This means players can play without dilemmas. Sounds like the Nash Equilibrium ends in there being no Nash Equilibriums.