Playing Smart - Artificial Intelligence in Computer Games

Abstract: With this document we will present an overview of artificial intelligence in general and artificial intelligence in the context of its use in modern computer games in particular. To this end we will firstly provide an introduction to the terminology of artificial intelligence, followed by a brief history of this field of computer science and finally we will discuss the impact which this science has had on the development of computer games. This will be further illustrated by a number of case studies, looking at how artificially intelligent behaviour has been achieved in selected games

Creating AI characters for fighting games using genetic programming

This paper proposes a character generation approach for the M.U.G.E.N. fighting game that can create engaging AI characters using a computationally cheap process without the intervention of the expert developer. The approach uses a Genetic Programming algorithm that refines randomly generated character strategies into better ones using tournament selection. The generated AI characters were tested by twenty-seven human players and were rated according to results, perceived difficulty and how engaging the gameplay was. The main advantages of this procedure are that no prior knowledge of how to code the strategies of the AI character is needed and there is no need to interact with the internal code of the game. In addition, the procedure is capable of creating a wide diversity of players with different strategic skills, which could be potentially used as a starting point to a further adaptive process

Mimicking human player strategies in fighting games using game artificial intelligence techniques

Fighting videogames (also known as fighting games) are ever growing in popularity and accessibility. The isolated console experiences of 20th century gaming has been replaced by online gaming services that allow gamers to play from almost anywhere in the world with one another. This gives rise to competitive gaming on a global scale enabling them to experience fresh play styles and challenges by playing someone new. Fighting games can typically be played either as a single player experience, or against another human player, whether it is via a network or a traditional multiplayer experience. However, there are two issues with these approaches. First, the single player offering in many fighting games is regarded as being simplistic in design, making the moves by the computer predictable. Secondly, while playing against other human players can be more varied and challenging, this may not always be achievable due to the logistics involved in setting up such a bout. Game Artificial Intelligence could provide a solution to both of these issues, allowing a human player s strategy to be learned and then mimicked by the AI fighter. In this thesis, game AI techniques have been researched to provide a means of mimicking human player strategies in strategic fighting games with multiple parameters. Various techniques and their current usages are surveyed, informing the design of two separate solutions to this problem. The first solution relies solely on leveraging k nearest neighbour classification to identify which move should be executed based on the in-game parameters, resulting in decisions being made at the operational level and being fed from the bottom-up to the strategic level. The second solution utilises a number of existing Artificial Intelligence techniques, including data driven finite state machines, hierarchical clustering and k nearest neighbour classification, in an architecture that makes decisions at the strategic level and feeds them from the top-down to the operational level, resulting in the execution of moves. This design is underpinned by a novel algorithm to aid the mimicking process, which is used to identify patterns and strategies within data collated during bouts between two human players. Both solutions are evaluated quantitatively and qualitatively. A conclusion summarising the findings, as well as future work, is provided. The conclusions highlight the fact that both solutions are proficient in mimicking human strategies, but each has its own strengths depending on the type of strategy played out by the human. More structured, methodical strategies are better mimicked by the data driven finite state machine hybrid architecture, whereas the k nearest neighbour approach is better suited to tactical approaches, or even random button bashing that does not always conform to a pre-defined strategy

Scare Tactics

It is the purpose of this document to describe the design and development processes of Scare Tactics. The game will be discussed in further detail as it relates to several areas, such as market analysis, development process, game design, technical design, and each team members’ individual area of background research. The research areas include asymmetrical game design, level design, game engine architecture, real-time graphics, user interface design, networking and artificial intelligence. As part of the team’s market analysis, other games featuring asymmetric gameplay are discussed. The games described in this section serve as inspirations for asymmetric game design. Some of these games implement mechanics that the team seeks to emulate and expand upon in Scare Tactics. As part of the team’s development process, several concepts were prototyped over the course of two months. During that process the team adopted an Agile methodology in order to assist with scheduling, communication and resource management. Eventually, the team chose to expand upon the prototype that became the basis of Scare Tactics. Game design and technical design occur concurrently in the development of Scare Tactics. Designers conduct discussions where themes, settings, and mechanics are conceived and documented. Mechanics are prototyped in Unity and eventually ported to a proprietary engine developed by our team. Throughout the course of development, each team member has had to own an area of design or development. This has led to individual research performed in several areas, which will be discussed further in this document

Generalised Player Modelling : Why Artificial Intelligence in Games Should Incorporate Meaning, with a Formalism for so Doing

General game-playing artificial intelligence (AI) has recently seen important advances due to the various techniques known as ‘deep learning’. However, in terms of human-computer interaction, the advances conceal a major limitation: these algorithms do not incorporate any sense of what human players find meaningful in games. I argue that adaptive game AI will be enhanced by a generalised player model, because games are inherently human artefacts which require some encoding of the human perspective in order to respond naturally to individual players. The player model provides constraints on the adaptive AI, which allow it to encode aspects of what human players find meaningful. I propose that a general player model requires parameters for the subjective experience of play, including: player psychology, game structure, and actions of play. I argue that such a player model would enhance efficiency of per-game solutions, and also support study of game-playing by allowing (within-player) comparison between games, or (within-game) comparison between players (human and AI). Here we detail requirements for functional adaptive AI, arguing from first-principles drawn from games research literature, and propose a formal specification for a generalised player model based on our ‘Behavlets’ method for psychologically-derived player modelling.Peer reviewe

Demon Dissension

Demon Dissension provides a strategic twist on the traditional fighting game experience to players and showcases complex game logic, networking, and fighting game design principles. Built entirely in the Unity engine and programmed in C#, Demon Dissension pits two players against one another in a battle for glory, challenging them to not only fight against the character in game, but the strategies being employed by the actual opponent. A team of two artists and two programmers took four terms to create a deep multiplayer battle experience

Demon Dissension

Demon Dissension provides a strategic twist on the traditional fighting game experience to players and showcases complex game logic, networking, and fighting game design principles. Built entirely in the Unity engine and programmed in C#, Demon Dissension pits two players against one another in a battle for glory, challenging them to not only fight against the character in game, but the strategies being employed by the actual opponent.. A team of two artists and two programmers took four terms to create a deep multiplayer battle experience

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Project 2746

In the 1990s, the world was introduced to the economic threat known as Internet piracy. It affects the copyright owners because they end up losing money that should have been spent on their product. This led to a long battle of online piracy between the pirates themselves, copyright owners, and governments around the world. Some even began to have a moral debate on piracy, asking themselves if it is really as heinous as people make it out to be or if it could help boost that product’s popularity and revenue. All of this information was taken and composed into a short narrative film which questions the history and ethics of Internet piracy