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X-Machines for Agent-Based Modeling: FLAME Perspectives
The tendency to defect is the dominating move for the players. But when
players jointly defect the payoff returned is less than the payoff returned with
mutual cooperation. Playing the game once, clearly the players would think
of defecting, but playing it with many trials, the players learn that they have
a higher probability of getting a high payoff if they choose to cooperate, eventually trusting the other player to cooperate.
Researchers have used the iterated prisoner’s dilemma game to draw important conclusions on behavior of group selection or mutual altruism in real
individuals. The gaining of trust among individuals when coming together in
groups is often viewed as an evolutionary process which allows evolution of
cooperative behaviors. Politics exhibits a PD scenario, illustrating when the
country has to make decisions in spending money on its military expansion or
reducing weapons. Advertising in economics is viewed as an example of a PD
scenario, where firms are competing against each other for sales. They have to
decide whether they need to advertise or not depending on whether the other
firm has advertised. Their decisions and the times at which they make them
would affect their sales.
Miller [132] used automaton to represent a strategy in a prisoner’s dilemma
game. A player can make only two moves: either to cooperate or defect. A
strategy, however, is a complete plan of the number of times to cooperate or
defect depending on what the other player played. This can be represented as
a sequence of states to determine the next move for each player. For instance,
some of the strategies can be as follows:
Always cooperate. Always cooperate no matter what the other player plays
(Figure 6.23(a)).
Always defect. Always defect no matter what the other player plays, cooperates or defects (Figure 6.23(b)).
Tit for tat. Cooperate on the first move. Then mimic whatever the other
player plays (Figure 6.23(c)).
Figure 6.23 depicts examples of automaton being used to represent the
prisoner dilemma strategies. Table 6.7 explains how two players playing an all
defecting strategy against a tit-for-tat strategy progress.
The players have no knowledge of what other players might be playing at
time t = 0. After the players have made their move, they know what the last
played strategy was. When an all defecting strategy plays against a tit-for-tat
strategy, it starts with the first player playing a defect and the second player
cooperating. As a result, the first player benefits getting a better payoff and
Player 2 suffers. But after this time step, Player 2 starts to mimic Player 1’s
last move. Since Player 1 defected in the last time step, it now plays a defect.
Player 1 is playing a strategy to defect. Each of these moves returns certain
payoffs to the players as shown.
Axelrod [14] organized a prisoner’s dilemma tournament where he invited
X-Machines for Agent-Based Modeling: FLAME Perspectives
The tendency to defect is the dominating move for the players. But when
players jointly defect the payoff returned is less than the payoff returned with
mutual cooperation. Playing the game once, clearly the players would think
of defecting, but playing it with many trials, the players learn that they have
a higher probability of getting a high payoff if they choose to cooperate, eventually trusting the other player to cooperate.
Researchers have used the iterated prisoner’s dilemma game to draw important conclusions on behavior of group selection or mutual altruism in real
individuals. The gaining of trust among individuals when coming together in
groups is often viewed as an evolutionary process which allows evolution of
cooperative behaviors. Politics exhibits a PD scenario, illustrating when the
country has to make decisions in spending money on its military expansion or
reducing weapons. Advertising in economics is viewed as an example of a PD
scenario, where firms are competing against each other for sales. They have to
decide whether they need to advertise or not depending on whether the other
firm has advertised. Their decisions and the times at which they make them
would affect their sales.
Miller [132] used automaton to represent a strategy in a prisoner’s dilemma
game. A player can make only two moves: either to cooperate or defect. A
strategy, however, is a complete plan of the number of times to cooperate or
defect depending on what the other player played. This can be represented as
a sequence of states to determine the next move for each player. For instance,
some of the strategies can be as follows:
Always cooperate. Always cooperate no matter what the other player plays
(Figure 6.23(a)).
Always defect. Always defect no matter what the other player plays, cooperates or defects (Figure 6.23(b)).
Tit for tat. Cooperate on the first move. Then mimic whatever the other
player plays (Figure 6.23(c)).
Figure 6.23 depicts examples of automaton being used to represent the
prisoner dilemma strategies. Table 6.7 explains how two players playing an all
defecting strategy against a tit-for-tat strategy progress.
The players have no knowledge of what other players might be playing at
time t = 0. After the players have made their move, they know what the last
played strategy was. When an all defecting strategy plays against a tit-for-tat
strategy, it starts with the first player playing a defect and the second player
cooperating. As a result, the first player benefits getting a better payoff and
Player 2 suffers. But after this time step, Player 2 starts to mimic Player 1’s
last move. Since Player 1 defected in the last time step, it now plays a defect.
Player 1 is playing a strategy to defect. Each of these moves returns certain
payoffs to the players as shown.
Axelrod [14] organized a prisoner’s dilemma tournament where he invited