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1. VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching

   Lin, T.; Aouididi, A.; Chen, Z.; Beyer, J.; Pfister, H.; Wang, J. (January 2023, IEEE transactions on visualization and computer graphics)

   Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily on manual note-taking, due to the lack of automatic data collection and appropriate visualization tools. As a result, there is a gap in effectively analyzing matches and communicating insights among badminton coaches and players. This work proposes an end-to-end immersive match analysis pipeline designed in close collaboration with badminton professionals, including Olympic and national coaches and players. We present VIRD, a VR Bird (i.e., shuttle) immersive analysis tool, that supports interactive badminton game analysis in an immersive environment based on 3D reconstructed game views of the match video. We propose a top-down analytic workflow that allows users to seamlessly move from a high-level match overview to a detailed game view of individual rallies and shots, using situated 3D visualizations and video. We collect 3D spatial and dynamic shot data and player poses with computer vision models and visualize them in VR. Through immersive visualizations, coaches can interactively analyze situated spatial data (player positions, poses, and shot trajectories) with flexible viewpoints while navigating between shots and rallies effectively with embodied interaction. We evaluated the usefulness of VIRD with Olympic and national-level coaches and players in real matches. Results show that immersive analytics supports effective badminton match analysis with reduced context-switching costs and enhances spatial understanding with a high sense of presence. 

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2. On the existence of Nash Equilibrium in games with resource-bounded players

   Halpern, Joseph Y; Pass, Rafael; Reichman, Daniel (September 2019, Proceedings of the 12th International Symposium on A Game Theory (SAGT)})

   We consider computational games, sequences of games G = (G1,G2,...) where, for all n, Gn has the same set of players. Computational games arise in electronic money systems such as Bitcoin, in cryptographic protocols, and in the study of generative adversarial networks in machine learning. Assuming that one-way functions exist, we prove that there is 2-player zero-sum computational game G such that, for all n, the size of the action space in Gn is polynomial in n and the utility function in Gn is computable in time polynomial in n, and yet there is no ε-Nash equilibrium if players are restricted to using strategies computable by polynomial-time Turing machines, where we use a notion of Nash equilibrium that is tailored to computational games. We also show that an ε-Nash equilibrium may not exist if players are constrained to perform at most T computational steps in each of the games in the sequence. On the other hand, we show that if players can use arbitrary Turing machines to compute their strategies, then every computational game has an ε-Nash equilibrium. These results may shed light on competitive settings where the availability of more running time or faster algorithms can lead to a “computational arms race”, precluding the existence of equilibrium. They also point to inherent limitations of concepts such as “best response” and Nash equilibrium in games with resource-bounded players. 

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3. Results of Beer Game Trials Played by Natural Resource Managers Versus Students: Does Age Influence Ordering Decisions?

   https://doi.org/10.3390/systems8040037  

   Turner, Benjamin L.; Goodman, Michael; Machen, Rick; Mathis, Clay; Rhoades, Ryan; Dunn, Barry (December 2020, Systems)

   null (Ed.)

   Systems involving agriculture and natural resources (AGNR) management and representing integrations of biologic, geologic, socio-economic, and climatic characteristics are incredibly complex. AGNR managers purport using a systems-oriented mental model while many observed management and policy strategies remain linear or symptom-driven. To improve AGNR professionals’ systems thinking abilities, two programs, the King Ranch® Institute for Ranch Management at Texas A&M University-Kingsville (KRIRM) and the Honors College at South Dakota State University (SDSUHC), implemented the famous Production Distribution Simulation Game (a.k.a. the Beer Game) into their programs beginning in 2003 and 2011. A Beer Game database consisting of 10 years of trials or over 270 individual players was compared to seminal work in the literature as well as to one another. We found that AGNR managers and students performed worse than players in a seminal Beer Game study. More interestingly, we found that younger players adapted more readily to inventory surpluses by reducing the order rates and effective inventories significantly when compared to older players (p < 0.10 for retailer and distributors, and p < 0.05 for wholesales and factories). We substantiated our results to those in more recent studies of age-related decision-making and in the context of common learning disabilities. Lastly, we discuss some implications of such decision-making on 21st century AGNR problems and encourage AGNR disciplines to better integrate system dynamics-based education and collaboration in order to better prepare for such complex issues. 

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4. Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable

   https://doi.org/10.1609/aaai.v35i6.16668  

   Dehghani, Sina; Saleh, Hamed; Seddighin, Saeed; Teng, Shang-Hua (May 2021, Proceedings of the AAAI Conference on Artificial Intelligence)

   In the classical discrete Colonel Blotto game—introducedby Borel in 1921—two colonels simultaneously distributetheir troops across multiple battlefields. The winner of eachbattlefield is determined by a winner-take-all rule, independentlyof other battlefields. In the original formulation, eachcolonel’s goal is to win as many battlefields as possible. TheBlotto game and its extensions have been used in a widerange of applications from political campaign—exemplifiedby the U.S presidential election—to marketing campaign,from (innovative) technology competition to sports competition.Despite persistent efforts, efficient methods for findingthe optimal strategies in Blotto games have been elusivefor almost a century—due to exponential explosion inthe organic solution space—until Ahmadinejad, Dehghani,Hajiaghayi, Lucier, Mahini, and Seddighin developed thefirst polynomial-time algorithm for this fundamental gametheoreticalproblem in 2016. However, that breakthroughpolynomial-time solution has some structural limitation. Itapplies only to the case where troops are homogeneous withrespect to battlegruounds, as in Borel’s original formulation:For each battleground, the only factor that matters to the winner’spayoff is how many troops as opposed to which sets oftroops are opposing one another in that battleground.In this paper, we consider a more general setting of thetwo-player-multi-battleground game, in which multifacetedresources (troops) may have different contributions to differentbattlegrounds. In the case of U.S presidential campaign,for example, one may interpret this as different typesof resources—human, financial, political—that teams can investin each state. We provide a complexity-theoretical evidencethat, in contrast to Borel’s homogeneous setting, findingoptimal strategies in multifaceted Colonel Blotto gamesis intractable. We complement this complexity result witha polynomial-time algorithm that finds approximately optimalstrategies with provable guarantees. We also study a furthergeneralization when two competitors do not have zerosum/constant-sum payoffs. We show that optimal strategiesin these two-player-multi-battleground games are as hard tocompute and approximate as Nash equilibria in general noncooperative games and economic equilibria in exchange markets. 

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5. Using Physiological Linkage for Patient State Assessment In a Competitive Rehabilitation Game

   https://doi.org/10.1109/ICORR.2019.8779361  

   Darzi, Ali; Novak, Domen (June 2019, Proceedings of the 2019 IEEE International Conference on Rehabilitation Robotics)

   null (Ed.)

   Competitive rehabilitation games can enhance motivation and exercise intensity compared to solo exercise; however, since such games may be played by two people with different abilities, game difficulty must be dynamically adapted to suit both players. State-of-the-art adaptation algorithms are based on players' performance (e.g., score), which may not be representative of the patient's physical and psychological state. Instead, we propose a method that estimates players' states in a competitive game based on the covariation of players' physiological responses. The method was evaluated in 10 unimpaired pairs, who played a competitive game in 6 conditions while 5 physiological responses were measured: respiration, skin conductance, heart rate, and 2 facial electromyograms. Two physiological linkage methods were used to assess the similarity of the players' physiological measurements: coherence of raw measurements and correlation of heart and respiration rates. These linkage features were compared to traditional individual physiological features in classification of players' affects (enjoyment, valence, arousal, perceived difficulty) into 'low' and 'high' classes. Classifiers based on physiological linkage resulted in higher accuracies than those based on individual physiological features, and combining both feature types yielded the highest classification accuracies (75% to 91%). These classifiers will next be used to dynamically adapt game difficulty during rehabilitation. 

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