Games have been used to evaluate and advance techniques in the eld of Articial Intelligence since before computers were invented. Many of these games have been deterministic perfect information games (e.g. Chess and Checkers). A deterministic game has no chance element and in a perfect information game, all information is visible to all players. However, many real-world scenarios involving competing agents can be more accurately modeled as stochastic (non-deterministic), im- perfect information games, and this dissertation investigates such games. Poker is one such game played by millions of people around the world; it will be used as the testbed of the research presented in this dissertation. For a specic set of games, two-player zero-sum perfect recall games, a recent technique called Counterfactual Regret Minimization (CFR) computes strategies that are provably convergent to an -Nash equilibrium. A Nash equilibrium strategy is very useful in two-player games as it maximizes its utility against a worst-case opponent. However, once we move to multiplayer games, we lose all theoretical guarantees for CFR. Furthermore, we have no theoretical guarantees about the performance of a strategy from a multiplayer Nash equilibrium against two arbitrary op- ponents. Despite the lack of theoretical guarantees, my thesis is that CFR-generated agents may perform well in multiplayer games. I created several 3-player limit Texas Holdem Poker agents and the results of the 2009 Computer Poker Competition demonstrate that these are the strongest 3-player computer Poker agents in the world. I also contend that a good strategy can be obtained by grafting a set of two-player subgame strategies to a 3-player base strategy when one of the players is eliminated.

Denna rapport är av en reflekterande karaktär. Den förmedlar arbetsprocessen och resultatet av ett projekt som gjorts i kursen examensarbete i medier: Dataspelsutveckling vt 2008. Verket som rapporten grundar sig på är en bana gjord för Unreal Tournament 3 (Epic Games, 2007). Banan skall uppnå mina egenstipulerade krav för att en bana skall vara välbalanserad. Texten inleds med en beskrivning av arbetsprocessen och de olika stegen som genomgicks. Den börjar med idén och går vidare i flertalet olika steg till det färdiga resultatet. Därefter visas den färdiga banan upp i form av bilder. Sedan följer en diskussion om resultatet och de problem som uppstod i arbetsprocessen. Slutsatsen är att förutom några få undantag så har min arbetsprocess fungerat bra. Jag anser mig ha skapat en multiplayer-bana som lever upp till mina egenstipulerade krav för en välbalanserad bana.

As mobile devices still have limited battery life, processing power, memory, and display size, they cannot yet execute gaming applications with the same fidelity and quality as their PC counterparts. In response, researchers have recently performed research with the goal of the real-time delivery of game content specifically to fit within mobile devices’ limitations. In this thesis, we present a novel approach to tackling the streaming of objects to mobile devices. Our goal is to reduce the number of objects subject to streaming from the server to the target devices, while not violating the user-defined limitations through an efficient, context-aware 3D object selection and prioritization scheme. We take advantage of the game context to stream only the most relevant objects. Our evaluations have shown that this technique not only leads to better performance in general, but also increases the gameplay experience by helping the player to achieve a higher score.

In this thesis, we study parallelization of multiplayer games using software Transactional Memory (STM) support. We show that STM provides not only ease of programming, but also better scalability than achievable with state-of-the-art lock-based programming for this realistic high impact application. We evaluate and compare two parallel implementations of a simplified version (named SynQuake) of the popular game Quake. While in STM SynQuake support for maintaining consistency of each potentially complex game action is automatic, conservative locking of surrounding objects within a bounding-box for the duration of the game action is inherently needed in lock-based SynQuake. This leads to higher scalability of STM SynQuake versus lock-based SynQuake due to increased false sharing in the latter. Task assignment to threads has a second-order effect on scalability of STM-SynQuake, impacting the application's true sharing patterns. We show that a locality-aware task assignment provides the best trade-off between load balancing and conflict reduction.

In this thesis, we study parallelization of multiplayer games using software Transactional Memory (STM) support. We show that STM provides not only ease of programming, but also better scalability than achievable with state-of-the-art lock-based programming for this realistic high impact application. We evaluate and compare two parallel implementations of a simplified version (named SynQuake) of the popular game Quake. While in STM SynQuake support for maintaining consistency of each potentially complex game action is automatic, conservative locking of surrounding objects within a bounding-box for the duration of the game action is inherently needed in lock-based SynQuake. This leads to higher scalability of STM SynQuake versus lock-based SynQuake due to increased false sharing in the latter. Task assignment to threads has a second-order effect on scalability of STM-SynQuake, impacting the application's true sharing patterns. We show that a locality-aware task assignment provides the best trade-off between load balancing and conflict reduction.

As mobile devices still have limited battery life, processing power, memory, and display size, they cannot yet execute gaming applications with the same fidelity and quality as their PC counterparts. In response, researchers have recently performed research with the goal of the real-time delivery of game content specifically to fit within mobile devices’ limitations. In this thesis, we present a novel approach to tackling the streaming of objects to mobile devices. Our goal is to reduce the number of objects subject to streaming from the server to the target devices, while not violating the user-defined limitations through an efficient, context-aware 3D object selection and prioritization scheme. We take advantage of the game context to stream only the most relevant objects. Our evaluations have shown that this technique not only leads to better performance in general, but also increases the gameplay experience by helping the player to achieve a higher score.

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<p>The focus of this dissertation is on large-scale and long-running networked real-time multiplayer games. In this type of games, each player controls one or many entities, which interact in a shared virtual environment. Three attributes - scalability, security, and fault tolerance - are considered essential for this type of games. The normal approaches for building this type of games, using a client/server or peer-to-peer architecture, fail in achieving all three attributes. We propose a server-network architecture that supports these attributes. In this architecture, a cluster of servers collectively manage the game state and each server manages a separate region of the virtual environment. We discuss how the architecture can be extended using proxies, and we compare it to other similar architectures. Further, we investigate how a distributed database management system can support the proposed architecture. Since efficiency is very important in this type of games, some properties of traditional database systems must be relaxed. We also show how methods for increasing scalability, such as interest management and dead reckoning, can be implemented in a database system. Finally, we suggest how the proposed architecture can be validated using a simulation of a large-scale game.</p>

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As mobile devices still have limited battery life, processing power, memory, and display size, they cannot yet execute gaming applications with the same fidelity and quality as their PC counterparts. In response, researchers have recently performed research with the goal of the real-time delivery of game content specifically to fit within mobile devices’ limitations. In this thesis, we present a novel approach to tackling the streaming of objects to mobile devices. Our goal is to reduce the number of objects subject to streaming from the server to the target devices, while not violating the user-defined limitations through an efficient, context-aware 3D object selection and prioritization scheme. We take advantage of the game context to stream only the most relevant objects. Our evaluations have shown that this technique not only leads to better performance in general, but also increases the gameplay experience by helping the player to achieve a higher score.