Cuckoo is a popular card game, which originated in France during the 15th century and then spread throughout Europe, where it is currently well-known under distinct names and with different variants. Cuckoo is an imperfect information game-of-chance, which makes the research regarding its optimal strategies determination interesting. The rules are simple: each player receives a covered card from the dealer; starting from the player at the dealer's left, each player looks at its own card and decides whether to exchange it with the player to their left, or keep it; the dealer plays at last and, if it decides to exchange card, it draws a random one from the remaining deck; the player(s) with the lowest valued card lose(s) the round. We formulate the gameplay mathematically and provide an analysis of the optimal decision policies. Different card decks can be used for this game, e.g., the standard 52-card deck or the Italian 40-card deck. We generalize the decision model for an arbitrary number decks' cards, suites, and players. Lastly, through numerical simulations, we compare the determined optimal decision strategy against different benchmarks, showing that the strategy outperforms the random and naive policies and approaches the performance of the ideal oracle.
<p>In this paper, we propose a novel control strategy for the optimal scheduling of an energy community constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs), used as temporary storage systems by prosumers, who in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve the energy allocation process. Acting as selfish agents, prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium problem, addressed through the variational inequality theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method, showing sufficient conditions for guaranteeing convergence. The proposed model predictive control approach is validated through numerical simulations under realistic scenarios. </p> <p><br></p> <p>This preprint has been accepted for publication in<em> IEEE Transactions on Control Systems Technology</em>. </p> <p><br></p> <p>This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible </p>
<p>Cuckoo is a popular card game, which originated in France during the 15th century and then spread throughout Europe, where it is currently well-known under distinct names and with different variants. Cuckoo is an imperfect information game-of-chance, which makes the research regarding its optimal strategies determination interesting. The rules are simple: each player receives a covered card from the dealer; starting from the player at the dealer's left, each player looks at its own card and decides whether to exchange it with the player to their left, or keep it; the dealer plays at last and, if it decides to exchange card, it draws a random one from the remaining deck; the player(s) with the lowest valued card lose(s) the round.</p> <p>We formulate the gameplay mathematically and provide an analysis of the optimal decision policies. Different card decks can be used for this game, e.g., the standard 52-card deck or the Italian 40-card deck. We generalize the decision model for an arbitrary number decks' cards, suites, and players. Lastly, through numerical simulations, we compare the determined optimal decision strategy against different benchmarks, showing that the strategy outperforms the random and naive policies and approaches the performance of the ideal oracle.</p> <p><br></p> <p>This preprint has been accepted for publication in<em> IEEE Transactions on Games</em>. </p> <p><br></p> <p><strong>How to cite</strong>: N. Mignoni, R. Carli and M. Dotoli, "Optimal Decision Strategies for the Generalized Cuckoo Card Game," in IEEE Transactions on Games.</p> <p><br></p> <p> <strong>© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.</strong></p>
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