Walling in Strategy Games via Constraint Optimization

International audienceThis paper presents a constraint optimization approach to walling in real-time strategy (RTS) games. Walling is a specific type of spatial reasoning, typically em-ployed by human expert players and not currently fully exploited in RTS game AI, consisting on finding con-figurations of buildings to completely or partially block paths. Our approach is based on local search, and is specifically designed for the real-time nature of RTS games. We present experiments in the context of the RTS game StarCraft showing promising results

Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy games

Decision-making problems can be modeled as combinatorial optimization problems with Constraint Programming formalisms such as Constrained Optimization Problems. However, few Constraint Programming formalisms can deal with both optimization and uncertainty at the same time, and none of them are convenient to model problems we tackle in this paper. Here, we propose a way to deal with combinatorial optimization problems under uncertainty within the classical Constrained Optimization Problems formalism by injecting the Rank Dependent Utility from decision theory. We also propose a proof of concept of our method to show it is implementable and can solve concrete decision-making problems using a regular constraint solver, and propose a bot that won the partially observable track of the 2018 {\mu}RTS AI competition. Our result shows it is possible to handle uncertainty with regular Constraint Programming solvers, without having to define a new formalism neither to develop dedicated solvers. This brings new perspective to tackle uncertainty in Constraint Programming.Comment: Published at the 2019 IEEE Congress on Evolutionary Computation (CEC'19

Orchestrating corporate social responsibility in the multinational enterprise

Multinational enterprises (MNEs) invest significant resources in corporate social responsibility (CSR), but their attempts to build a global “social brand” may clash with the execution of operational strategies at a subsidiary level. Using a game-theoretic model, this research addresses the complex interplay of different contingencies that shape the coordination and control challenges facing MNEs when they implement global CSR strategies, including brand spillovers, the risk of public scandals caused by irresponsible behavior, the size of the MNE network, as well as the roles played by non-governmental organizations and altruistic managers. Challenging the view of CSR as insurance against lapses of responsible conduct, our model shows that investment in social brands helps avoid irresponsible practices across the MNE network, thereby inducing subsidiaries to “walk the talk”

Problèmes d'optimisation dans les jeux avec GHOST

National audienceCet article présente GHOST, un solveur d'optimisation combinatoire qu'un développeur de jeux de stratégie en temps réel (RTS) peut utiliser comme une boîte noire pour résoudre tout problème modélisé comme un problème de satisfaction/optimisation de contraintes. Nous montrons une manière de modéliser trois diffé-rents problèmes de RTS dans ce formalisme, chacun de ces problèmes appartenant à un niveau d'abstraction spécifique, en utilisant le jeu RTS StarCraft comme environnement de test. Sur chacun de ces trois problèmes, GHOST retourne des solutions de très bonne qualité en l'espace de quelques dizaines de millisecondes

Defending Choke Points in Star Craft: Brood War

Navzdory úsilí v oblasti umělé inteligence pro strategické hry v reálném čase, se počí- tačově řízeným agentům (botům) stále nedaří porazit ani průměrné lidské hráče. Jedním z klíčů k úspěchu v těchto hrách je schopnost využít různé taktické body na mapě, jako jsou ku příkladu chokepoints - úzké průchody spojující otevřené oblasti ve hře. Pomocí genetických algoritmů a simulátoru SparCraft pro hru StarCraft: Brood War, popisujeme metodu generování výhodných rozložení jednotek pro obranu chokepointů. Naše exper- imenty ukazují, že rozložení vytvořené pomocí naší metody mají výrazně lepší výsledky než náhodná rozložení a jsou srovnatelné s rozloženími, která jsou tradičně používána lidskými hráči. Naše metoda může být také použita k vytvoření databáze výhodných rozložení jednotek, jež by mohla být začleněna do stávajících botů pro hru StarCraft: Brood War. 1Despite the effort in the field of artificial intelligence for real time strategy games, computer controlled agents (bots) still struggle even against average human players. One of the keys to success in such games is the ability to take advantage of various tactical points on the map, like chokepoints - narrow passages connecting open areas. With the use of genetic algorithms and SparCraft, a simplified simulator of StarCraft: Brood War, we present a method to generate advantageous unit layouts for defending chokepoints. Our experiments show that layouts produced using our method perform significantly better than random layouts, and are comparable in quality with layouts traditionally employed by human players. Our method may also be used to generate a database of advantageous unit layouts, which could be incorporated into an existing StarCraft: Brood War bot. 1Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Microgrid-Enabled Reactive Power Support to Enhance Grid Economics

Reactive power plays an essential role in voltage control and stability in electric power systems. Various Volt/VAR techniques are utilized in electric power systems to maintain the voltage profile within defined acceptable limits and accordingly provide reliability and stability. Reactive power has been commonly generated through large-scale synchronous generators or distributed capacitor banks to provide proper transmission and distribution level system management, however, reactive power can be further used as an effective means to reduce total system operation cost. In this dissertation, an optimal reactive power model is proposed to determine the optimal nodal reactive powers that result in the lowest total system operation cost. Microgrid is introduced as a source of real and reactive power where its capability curve as a single generator unit is further determined and utilized. An optimization-based method is proposed to determine this capability curve. The results of numerical analyses of this proposal show how the reactive power behaves under gradual changing of real power generation in a microgrid and how these two outputs are correlated. This model is further integrated into an optimal power flow problem to show the potential economic benefits of microgrid-generated reactive power of the larger system. The numerical analyses on standard test systems show the performance of the proposed model and provide insights on the role of microgrid as a source of reactive power in the system