Information Game With Asymmetric Information

The decisions or strategies one company chooses will likely motivate other competitors to respond. Using the game theory allows a company to assess and understand more about itself and its competitors so that it can adjust and shape the competition to maximize its win probability (Johnson, 2014). Some examples of how A&D companies apply the game theory in their decision making are:

If you constantly split the difference or “straddle the fence,” game playing can result and the outcome could be less than ideal.

The definition strategy function basically means what does being an American do. Being an American allows them to technically do whatever they want since they are free. Being an American allows one to get a job and earn money and have a family and home. It means one can think the way they want to think and act the way they want to act.

True strategy is about placing bets and making hard choices. - Will Evans. Billy had a hard decision to make on whether to bet the Prichard boys. Billy should have taken the bet because he would have put the Prichard boys into their place, prove his dogs are the best, and make his grandpa proud.

Both teams are equally skilled, but they are using different strategies. We can assume that Team A earns 1.4 points on average in this scenario, while Team B earns 1.1 points on average in this scenario. Therefore, given that Team B is waiting until overtime, and Team A is playing to win in regulation, then Team A will earn a payoff of 1.4 points on average, while Team B will earn a payoff of 1.1 points on average. Likewise, given that Team A is waiting until overtime, and Team B is playing to win in regulation, then Team B will earn a payoff of 1.4 points on average, while Team A will earn a payoff of 1.1 points on average. The following matrix summarizes this

Example: Player 1 is the manager at my job, and she doesn’t feel good. She has two moves: either go to work, or take a sick day. If she comes in, she may spread whatever illness she has around. If she doesn’t go to work, she can have the chance to feel better. Player 2 is the boss, and now has two choices: to keep her on staff, or fire her.

The two strategies I played against are to defect or cooperate when playing the Flip-a-coin strategy and the Massive Retaliatory Strike. In both cases when I cooperated one-hundred percent, I had a huge loss to the computer, my score for the flip coin toss was 21 to the computers 86 when I choose just to cooperate. In the massive retaliatory strike when I cooperated all the time my score was 60 and the machine was 60, so in this case, no one won, but we tied or it is a win-win scenario. In the flip-coin toss when I defected, I won, my score was 76 against the computer’s score of 6. When I defected all the time in the massive retaliatory strike, my score was 24 to the computer’s score of 16. When I played the game tit for tat and defected all

Game theory cannot always predict reliable outcomes for real-life situations as it is more an

Nash equilibrium is a solution theory of a non-cooperative game which involves two or more

Game Trees, as mentioned earlier, are very useful in determining what outcomes are most likely to occur, in other words, the most rational and logical decision. For example, Poundstone describes a dilemma between a thief trying to sell a priceless item and a questionable man with few scruples. The scenario is a perfect example of the “Prisoner’s Dilemma” and can be analyzed using a Game Tree. The most logical decision for both parties is to cheat, or choose Traitor. Yet this decision undermines the common good of mutual cooperation which benefits both parties. Logic then is what blocks the best outcome, simply because the most rational decision is to cheat and defect. The trend in such situations, much like a business transaction or in policy

Nash equilibrium can be described as the end of the game sequence. Player gains a posteriori experience during the sequences of the game which in turn help them to form the belief and gain knowledge that lead to the end point, the Nash equilibrium, hence there is no further knowledge that can be gained. In the usual finite set of games the marking of the end point, Nash equilibrium, will allow us to make better or optimal decision. If our decision making process doesn’t satisfy the Nash equilibrium, we must always be able to improve our decision and choice that we made till we hit that equilibrium.

If the Defender knew the Attacker’s utility function uA(a,s,v) and the probabilities pA(S|d,a,v) and pA(V|d), she could predict his decision a*(d) for any d ∈ D by solving backwards the tree in Figure 6, followed by computing his expected utility ψA.

The internet is an integral way of conducting daily business from government agencies to entertainers. Protection of attack, damage, or unauthorized access is necessary with the increase of mobile users, digital applications and data networks. A cyber-security problem can be viewed as a conflict-resolution scenario that typically consists of a security system and at least two decision makers (e.g. attacker and defender) that can each have competing objectives. For instance, the defender may be interested in ensuring that the system performs at or above a certain acceptable level. The attacker’s objective may be to disrupt the system and degrade it. Game theory is a well-established tool that can be used to analyze such problems. In this work, we present a brief survey of how game theory can be used to find appropriate strategies for both the attacker and the administrator (defender). We model the interactions between them as a stochastic game. Various formulations of game theory will be presented to deal with different cyber security situations. We will present mathematical models of security systems to analyze the system’s performance and to predict the likely behavior of key decision makers that influence/control the system.

Abstract— In wireless communication, spectrum resources are utilized by authorities in particular fields. Most of the elements in spectrum are idle. Cognitive radio is a promising technique for allocating the idle spectrum into unlicensed users. Security shortage is a major challenging issue in cognitive radio ad-hoc networks (CRAHNs) that makes performance degradation on spectrum sensing and sharing. A selfish user pre-occupies the accessible bandwidth for their prospect usage and prohibits the progress secondary users whose makes the requirement for spectrum utility. Game theoretic model is proposed to detect the selfish attacker in CRAHNs. Channel state information (CSI) is considered to inform each user’s channel handing information. The two strategy of Nash Equilibrium game model such as pure and mixed strategy for secondary users (SUs) and selfish secondary users (SSUs) are investigated and the selfish attacker is detected. Moreover a novel belief updating system is also proposed to the secondary users for knowing the CSI of the primary user. A simulation result shows that, game theoretic model is achieved to increase the detection rate of selfish attackers.

Game Theory, the analysis of the concepts used in social reasoning when dealing with situations of conflict (Rubinstein, 1991), is one of many methods used to provide rational strategies towards the making of decisions. Game theory provides logical and mathematical models towards decision-making which are applied to real-life situations such as