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The purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.

The approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.

Game theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.

Though games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.

The authors characterize the conditions under which a country may eventually split and when it splits within an infinite horizon multi-stage differential game.

In contrast to the existing literature, the authors do not assume that after splitting, players will adopt Markovian strategies. Instead, the authors assume that while the splitting country plays Markovian, the remaining coalition remains committed to the collective control of pollution and plays open-loop.

Within a full linear-quadratic model, the authors characterize the optimal strategies. The authors later compare with the outcomes of the case where the splitting country and the remaining coalition play both Markovian. The authors highlight several interesting results in terms of the implications for long-term pollution levels and the duration of coalitions under heterogenous strategies as compared to Markovian behavior.

In this paper, the authors have illustrated the richness of the simplications of enlarging the set of strategies in terms of the emergence of coalitions, their duration and the implied welfare levels per player. Varying only three parameters (the technological gap, pollution damage and coalition payoff share distribution across players), the authors have been able to generate, among other findings, quite different rankings of welfare per player depending on whether the remaining coalitions after split play Markovian or stay precommited to the pre-splitting period decisions.

This study attempts to figure out the factors that contributed to deposing certain elected presidents before the end of their constitutional terms, alongside tracing the new political context that prevailed in Latin America since 1978 and its impact on direct political participation and military behavior during presidential crises.

The paper uses the comparative method to investigate the causes of presidential instability in three case studies.

The likelihood of presidential instability increases when a president enacts austerity economic policies that marginalize large sectors of the citizenry, becomes implicated in acts of corruption and develops a hostile relationship with members of the ruling coalition.

This study integrates the social movement theory with analytical perspectives from parliamentary behavior to explain presidential instability. It attempts to investigate the dynamics of interaction between the acts of furious citizens and disloyal legislators through the in-depth analysis of three case studies.

Based on Behavioral Theory of Negotiations (Walton & McKersie, 1965), the purpose of this paper is to discuss the existing gap between negotiation theory and pedagogy and presents an experiential teaching tool that closes this gap. The tool is a ‘serious game’ (Abt, 1975) that reinforces all four core negotiation subprocesses while allowing students to practice their negotiation skills and several critical business competencies in a realistic and improvisational context.

After successfully using NegotioPoly for five years, qualitative and quantitative data were collected in three sections of negotiation classes to assess student learning and behaviors while playing NegotioPoly and to collect student feedback on the effectiveness of NegotioPoly in teaching and reinforcing key negotiation skills.

Findings support that NegotioPoly is highly effective in engaging students in a series of realistic negotiations, joint problem solving and strategic decision-making. Results show that, during the game, students demonstrate their negotiation skills and learnings, and they practice all four negotiation subprocesses of distributive, integrative and intraorganizational bargaining and attitudinal structuring.

NegotioPoly enables students to engage in distributive and integrative bargaining, multiple levels of negotiations and coalitions in quick succession. Students practice organizational politics and adjust their negotiations based on relationships and social realities, as they demonstrate advanced deal-making behaviors and core business competencies of problem solving, decision-making, analytical skills and ability to work with others.

NegotioPoly reinforces core business competencies such as negotiation, problem solving, analytical skills and the ability to work in teams that employers look for and, therefore, is a useful tool for preparing students for the business world.

NegotioPoly is an experiential learning tool that closes the gap between negotiation theory and pedagogy while providing deep learning and realistic practice opportunities for students where they can use their negotiation skills in a gaming environment that uses multi-party and multi-round negotiations.

Japan's decision to release nuclear wastewater into the Pacific Ocean in 2023 has sparked strong opposition at home and abroad. In this study, Graph Model for Conflict Resolution (GMCR) method is adopted to analyze the conflict problem, and reasonable equilibrium solutions are given to solve the conflict event.

In this study, GMCR is adopted to solve the conflict problem. First, identify the key decision-makers (DMs) on the issue of nuclear effluent and the relevant options they might adopt. Second, the options of each DM are arranged and combined to form a set of feasible states. Thirdly, the graph model is constructed according to the change of DM's options, and the relative preference of each DM is determined. Finally, the conflict problem is solved according to the definition of GMCR equilibrium.

Discharging nuclear wastewater into the ocean is not the right choice to solve the problem. Developing more space to store nuclear wastewater is more conducive to the protection of the ocean environment.

It is undesirable for the Japanese government to unilaterally discharge nuclear wastewater into the ocean. Objectively assessing the radioactivity of nuclear wastewater and the cooperation of relevant stakeholders can better solve this conflict.

The problem arising from Japan's releasing plan is complicated because of a lack of information and the existence of multiple stakeholders, while GMCR can help us with a better view of the current circumstance in the conflict.