University Assignment: Critical Analysis on Game Theory and AI

This report provides a critical analysis of the application of Nash equilibrium and artificial intelligence in game theory. It begins with an introduction outlining the paper's objectives, which include comparing and contrasting Nash equilibrium theory with other research on AI and game theory, elaborating on the impact of Nash equilibrium on AI in game theory, and concluding with an overview of AI's effect on game theory. The discussion section examines Nash's contributions, particularly his equilibrium theory's significance in game development, and how the Nash algorithm is applied in non-constructive fields. The report highlights how AI has improved games through the implementation of Nash's equilibrium and enhanced decision-making processes. It also notes the computational demands of the Nash equilibrium algorithm and the necessity of incorporating Nash's equilibrium in games. The conclusion summarizes the analysis and emphasizes the impact of Nash's equilibrium on enhancing gaming experiences and the role of AI in gaming, particularly in decision-making and strategy handling. The report references several research papers to support its analysis.

Running head: CRITICAL ANALYSIS ON GAME THEORY AND ARTIFICIAL INTELLIGENCE
CRITICAL ANALYSIS
ON
GAME THEORY AND ARTIFICIAL INTELLIGENCE
Name of the Student
Name of the University
Author Note:

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Introduction:
The primary objective of this paper is to discuss about the application of the Nash
Game theory and the application of Artificial Intelligence. In order to effectively summarize
the mentioned topic this paper will effectively compare and contrast the writing on Nash
equilibrium theory with other articles based on the application of Artificial intelligence and
Nash equilibrium theory. Followed by the above discussion it will also elaborate how the
Nash equilibrium theory has affected the application of Artificial intelligence in the field of
game theory. Lastly, this paper will conclude by explaining the impact of Artificial
Intelligence in the field of game theory.
Discussion:
Followed by the above mentioned aspect the impact of Nash’s contribution has been
accounted in several areas. However, according to the Daskalakis et al., (2009) research
paper it has been identified that Trace John Nash has effectively proven that Nash’s
equilibrium is one of the significant as well as common factors in the game development.
Followed by this aspect it has been also noticed that the application of Nash’s algorithm it
based on non-constructive field which is entirely relied on the fixed point of the browser.
Hence, in this paper they have investigated about how the time to compute the Nash
algorithm. Followed by this concern in this paper they have effectively elaborated the aspect
of Nash equilibrium in the field of PPAD however, according to the Quijano et al., (2017) it
has mainly focused on the application of Nash algorithm in the field of artificial intelligence.
However, Parkes et al., (2015) has mentioned that the application of artificial intelligence and
the game theory is interconnected by each other as there is a significant impact of artificial
intelligence is present in the gaming field. Hence, followed by this aspect it has been
observed from the study of Ojo (2018) that due to implementation of the Nash’s equilibrium
algorithm the AI has significantly improved the games which includes the field of Participant

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design, mechanism. Followed by this according to Rabinovich et al., (2015) in the book of
wonderful mind the contribution of Nash’s algorithm is mentioned as it is one of the most
significant aspect of the game theory. The Nash’s equilibrium is nothing but process to
switch the strategy of players. Game theory is nothing but a mathematical concept in which it
determine the strategy of players by analyzing the actions made by that player. Hence,
followed by this aspect Artificial intelligence has significantly improved the actions of the
games by enhancing the decision making process in the gaming industry. While it has been
observed that the application of Nash’s equilibrium has significantly helped to enhance the
application of game theory Chan and Ortiz (2018) has stated that in order to compile the
Nash equilibrium algorithm huge computation capability is needed. Followed by this aspect it
has also proved that however, all most every game required to incorporate the Nash’s
equilibrium algorithm most of the game dies not requited the pure version of the equilibrium
theory as it is very difficult to compile the entire equilibrium code. Hence, the game consist
with minimum one person incorporates the matching strategies with the Nash equilibrium.
Followed by this aspect it has been also observed that in the application of Nash’s
equilibrium every player holds the opportunity to win the game as their desired result is
determined by their strategy thus, Nash’s equilibrium will only prove if and only if the each
and every player present in games knows each one’s gaming strategies (Balliu et al., 2017).
Hence, followed by this aspect it has been observed from the studies that the application of
Nash’s equilibrium has helped the game developer in the field of coordination game,
competitive games as well as in the network games in which it has significantly effected
directed the strategies of the agents present in the game in order to enhance the flexibility of
the game. Followed by this while discussing about the traditional gaming strategies it has
been noticed that in case of two players game there is two significant situation in which if one
player one defects s/he will get the point if and only if the other one is ready to leave the

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game. This is applied for the other member as well (Gaina et al., 2019). However, in the
application of the Nash’s equilibrium it has been noticed that it allows the player to be in
such situation in which both of the player can play their moves without even worrying about
the action of the opponent. Hence, it can be stated that Nash’s equilibrium holds the
capability to reduce the ethical dilemmas of the players (Perez-Liebana et al., 2018).
Considering the above situation it has been noticed that the feature of the artificial
intelligence in the game theory will be applied if and only if the game consist more than one
player as it helps to enhance the decision making capability of the players. As commented by
the Brown et al., (2019) artificial intelligence has improved the field of gamming by
providing more effective decision making process as well as by offering the player more
information about the game. Hence, it can be stated that the application of Nash’s equilibrium
has significantly enhanced the gaming operation as well as the field of Artificial intelligence.
Conclusion:
Followed by the above discussion it can be concluded that this paper has effectively
discussed the research topic as well as it has analyses the mentioned topic related to the
application of Nash’s equilibrium and artificial intelligence by comparing it with the main
research paper. Considering the above aspects it has been observed that the mentioned
algorithm Nash’s equilibrium holds a significant impact on enhancing the gaming
experiences for the user as well as it has effectively discussed about the application of
artificial intelligence in the field of gaming. Followed by this it has been determined that the
aspect of decision making and the strategy handling is one of the major aspect of gaming
which are most of the directed by the application of Nash’s equilibrium. Lastly, it can be
concluded that this paper has successfully analyzed and summarized the application of
Nash’s equilibrium on game theory and on AI as well.

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Reference:
Balliu, A., Flammini, M., Melideo, G. and Olivetti, D., 2017, February. Nash stability in
social distance games. In Thirty-First AAAI Conference on Artificial Intelligence
Brown, N., & Sandholm, T. (2019). Superhuman AI for multiplayer poker. Science,
eaay2400.
Chan, H. and Ortiz, L.E., 2018, July. Learning Game-theoretic Models from Aggregate
Behavioral Data with Applications to Vaccination Rates in Public Health.
In Proceedings of the 17th International Conference on Autonomous Agents and
MultiAgent Systems (pp. 1891-1893). International Foundation for Autonomous
Agents and Multiagent Systems.
Daskalakis, C., Goldberg, P. W., & Papadimitriou, C. H. (2009). The complexity of
computing a Nash equilibrium. SIAM Journal on Computing, 39(1), 195-259.
Gaina, R. D., Lucas, S. M., & Pérez-Liébana, D. (2019, July). Tackling Sparse Rewards in
Real-Time Games with Statistical Forward Planning Methods. In Proceedings of the
AAAI Conference on Artificial Intelligence (Vol. 33, pp. 1691-1698).
Ojo, M., 2018. Beyond Reasoning, Artificial Intelligence and Data Analytics: Gaming
Theories and the Nash Theory of Equilibrium (Presentation Slides). Artificial
Intelligence and Data Analytics: Gaming Theories and the Nash Theory of
Equilibrium (Presentation Slides)(August 6, 2018).
Parkes, D. C., & Wellman, M. P. (2015). Economic reasoning and artificial
intelligence. Science, 349(6245), 267-272.

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Perez-Liebana, D., Liu, J., Khalifa, A., Gaina, R. D., Togelius, J., & Lucas, S. M. (2018).
General video game ai: a multi-track framework for evaluating agents, games and
content generation algorithms. arXiv preprint arXiv:1802.10363.
Quijano, N., Ocampo-Martinez, C., Barreiro-Gomez, J., Obando, G., Pantoja, A., & Mojica-
Nava, E. (2017). The role of population games and evolutionary dynamics in
distributed control systems: The advantages of evolutionary game theory. IEEE
Control Systems Magazine, 37(1), 70-97.
Rabinovich, Z., Obraztsova, S., Lev, O., Markakis, E. and Rosenschein, J.S., 2015, February.
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on Artificial Intelligence.