Материал: искусственный интеллект

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all possible maximum expected utilities that the player can achieve by varying the quantum interference term θ in Eq. 20 for a personal strategy of confessing (defecting) or remaining silent (cooperating), respectively. On the left of Fig. 4, it is represented all the values of θ that satisfy the condition that EU [Cooperate] > EU [Def ect], i.e., all the values of the quantum interference parameter θ that will maximise the utility of cooperation rather than defect. One can note that, for experiment of Shafir and Tversky (1992) (as well as in the remaining works of the literature analysed in this work), one can maximise the expected utility of Cooperation when the utilities are negative. This is in accordance with the previous study of Moreira and Wichert (2016) in which the authors found that violations to the Sure Thing Principle imply destructive (or negative) quantum interference e ects. As we will see in the next section, the quantum parameters found that are used to maximise the expected utility of a cooperate action lead to destructive quantum interferences and can exactly explain the probability distributions observed in the experiments.

7.1Results and Discussion

Although there are several quantum parameters that satisfy the relationship that shows that participants can maximise the utility of a cooperate action, only a few parameters are able to accommodate both the paradoxical probability distributions reported in the several works in the literature and to maximise the expected utility of cooperating. The previous work of Moreira and Wichert (2016) shows how the quantum parameters are sensitive to accommodate the violations of the Sure Thing Principle in terms of the probability distributions. The slight variation of the quantum parameter θ in the quantum-like Bayesian network can lead to completely di erent probability distributions which di er from the ones observed in the di erence experimental scenarios reported in the literature. These probability distributions will influence the utilities computed by the expected utility framework.

In Table 2, it is presented the quantum parameters that lead to the quantum interference term that is necessary to fully explain and accommodate the violations to the Sure Thing Principle reported over several works of the literature.

For this reason, we decided to test if the quantum-like parameters used to accommodate the violations to the Sure Thing Principle were su cient and if they could also lead to a maximisation of expected utility of cooperation. We performed simulations of the di erent works in the literature and we concluded that the quantum interference e ects that can accommodate violations to the violations of the Sure Thing Principle in the quantum-like Bayesian network alone, also explain a higher preference of the cooperative action over defect. Table 3 presents the results.

In Table 3, we present the Maximum Expected Utility (MEU) computed for each work in the literature using the classical approach for the player’s di erent strategies: either remain silent (CL silent) or confess the crime (CL confess). The classical MEU shows that the optimal strategy is to conf ess and engage on a def ect strategy independently of what action the opponent chose. Of course

Table 2. Experimental results reported for the Prisoner’s Dilemma game. The entries highlighted correspond to games that are not violating the Sure Thing Principle.

these results go against the experimental works of the literature which say that a significant percentage of individuals, when under uncertainty, the engage more on cooperative strategies.

In opposition, when we use the quantum-like influence diagram, we take advantage of the quantum interference terms that will disturb the probabilistic outcomes of the quantum-like Bayesian networks. Since the utility function depends on the outcomes of the quantum-like Bayesian network, then it is straightforward that quantum interference e ects influence indirectly the outcomes of the MEU allowing us to favour a di erent strategy predicted by the classical MEU.

Table 3. Inferences in the quantum-like influence diagram for di erent works of the literature reporting violations of the Sure Thing Principle in the Prisoner’s Dilemma Game. One can see that the Quantum-Like Influence, presented in Eq. 20 (QL Infl) was changed to favour a Cooperate strategy using the quantum interference e ects of the Quantum-Like Bayesian Network. In the payo s, d corresponds to def ect and c to cooperate. The first payo corresponds to player 1 and the second to player 2.

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It is interesting to notice that indeed the parameters used accommodate the violations of the Sure Thing Principle alone in the quantum-like Bayesian Network could also be used to maximise the utility of a Cooperate action. This was verified in all works of the literature analysed except in Game 6 in the work of Li and Taplin (2002). The reason is that Game 6 is not even reporting a violation to the Sure Thing Principle and could be explained by the classical theory with a minor error percentage. This means that in this experiment, a def ect action was favoured over a cooperate one.

8 Conclusion

In this work, we proposed an extension of the quantum-like Bayesian Network initially proposed by Moreira and Wichert Moreira and Wichert (2014, 2016) into a quantum-like influence diagram. Influence diagrams are designed for knowledge representation. They are a directed acyclic compact graph structure that represents a full probabilistic description of a decision problem by using probabilistic inferences performed in Bayesian networks (Koller and Friedman 2009) together with a fully deterministic utility function. Currently, influence diagrams have a vast amount of applications. They can be used to determine the value of imperfect information on both carcinogenic activity and human exposure (Howard and Matheson 2005), the are used to detect imperfections in manufacturing and they can even be used for team decision analysis (Detwarasiti and Shachter 2005), valuing real options (Lander and Shenoy 2001), etc.

The preliminary results obtained in this study show that the quantum-like Bayesian network can be extended to deal with decision-making scenarios by incorporating the notion of maximum expected utility in influence diagrams. The general idea is to take advantage of the quantum interference terms produced in the quantum-like Bayesian network to influence the probabilities used to compute the expected utility. This way, we are not proposing a new type of expected utility hypothesis. On the contrary, we are keeping it under its classical definition. We are only incorporating it as an extension of a quantum-like probabilistic graphical model where the utility node depends only on the probabilistic inferences of the quantum-like Bayesian network.

This notion of influence diagrams opens several new research paths. One can incorporate di erent utility nodes being influenced by di erent random variables of the quantum-like Bayesian Network. This way one can even explore di erent interference terms a ecting di erent utility nodes, etc. We plan to carry on with this study and further develop these ideas in future research.

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