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1. Bayesian games with intentions

   https://doi.org/10.1016/j.geb.2020.06.003  

   Bjorndahl, Adam ; Halpern, Joseph Y. ; Pass, Rafael ( September 2020 , Games and Economic Behavior)

   null (Ed.)
2. Games With Tolerant Players

   https://doi.org/10.4204/EPTCS.251.18  

   Ghosh, Arpita ; Halpern, Joseph Y. ( July 2017 , Electronic Proceedings in Theoretical Computer Science)
3. Games with filters I

   https://doi.org/10.1142/S021906132450003X  

   Foreman, Matthew ; Magidor, Menachem ; Zeman, Martin ( August 2023 , Journal of Mathematical Logic)

   Chong, Chita ; Feng, Qi ; Slaman, Theodore_A ; Woodin, W_Hugh (Ed.)

   This paper has two parts. The first is concerned with a variant of a family of games introduced by Holy and Schlicht, that we call Welch games. Player II having a winning strategy in the Welch game of length [Formula: see text] on [Formula: see text] is equivalent to weak compactness. Winning the game of length [Formula: see text] is equivalent to [Formula: see text] being measurable. We show that for games of intermediate length [Formula: see text], II winning implies the existence of precipitous ideals with [Formula: see text]-closed, [Formula: see text]-dense trees.

   The second part shows the first is not vacuous. For each [Formula: see text] between [Formula: see text] and [Formula: see text], it gives a model where II wins the games of length [Formula: see text], but not [Formula: see text]. The technique also gives models where for all [Formula: see text] there are [Formula: see text]-complete, normal, [Formula: see text]-distributive ideals having dense sets that are [Formula: see text]-closed, but not [Formula: see text]-closed.

    

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4. Building Simple Games With BRIDGES

   https://doi.org/10.1145/3287324.3293758  

   Burlinson, David ; Saule, Erik ; Subramanian, Kalpathi ( March 2019 , Proceedings of the 50th ACM Technical Symposium on Computer Science Education)

   Many newcomers to programming and computational thinking have been brought up on interactive, gamified learning environments. Introductory computer science courses at the university level need to dig deeper into these topics, but must do so with similarly engaging technologies and projects. To address this need, we have built a framework for a grid-based game API with event-based blocking and continuous non-blocking interfaces. The framework abstracts away much of the complexity of inputs and rendering and exposes a simple game grid similar to a 2D array indexed by rows and columns. As such, our project helps reinforce basic computing concepts (arrays, loops, OOP, recursion) with a customizable and engaging game interface. We have discussed the valuable influence of visual representations of student's data structures using BRIDGES in previous publications, and believe our game API can provide significance and intrigue for students in introductory courses and beyond. Our Bridges Games App website (http://bridges-games.herokuapp.com/) presents descriptions and instructions. 

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5. Multi-scale games: Representing and solving games on networks with group structure

   Jin, Kun ; Vorobeychik, Yevgeniy ; Liu, Mingyan ( January 2021 , Proceedings of the AAAI Conference on Artificial Intelligence)

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   Network games provide a natural machinery to compactly represent strategic interactions among agents whose payoffs exhibit sparsity in their dependence on the actions of others. Besides encoding interaction sparsity, however, real networks often exhibit a multi-scale structure, in which agents can be grouped into communities, those communities further grouped, and so on, and where interactions among such groups may also exhibit sparsity. We present a general model of multi-scale network games that encodes such multi-level structure. We then develop several algorithmic approaches that leverage this multi-scale structure, and derive sufficient conditions for convergence of these to a Nash equilibrium. Our numerical experiments demonstrate that the proposed approaches enable orders of magnitude improvements in scalability when computing Nash equilibria in such games. For example, we can solve previously intractable instances involving up to 1 million agents in under 15 minutes. 

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