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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 The isolated console experiences of 20th century gaming has been replaced by online gaming services that allow gamers to play from almost anywhere in the world with one another.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.

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Utförandet av projektet har varit att implementera två stycken fightingspels Artificiell Intelligens (kommer att förkortas AI). En oadaptiv och mer deterministisk AI och en adaptiv dynamisk AI som använder reinforcement learning. Detta har utförts med att skripta beteendet av AI:n i en gratis 2D fightingsspels motor som heter ”MUGEN”. AI:n använder sig utav skriptade sekvenser som utförs med MUGEN’s egna trigger och state system. Detta system kollar om de skriptade specifierade kraven är uppfyllda för AI:n att ska ”trigga”, utföra den bestämda handlingen. Den mer statiska AI:n har blivit uppbyggd med egen skapade sekvenser och regler som utförs delvis situationsmässigt och delvis slumpmässigt. För att försöka uppnå en reinforcement learning AI så har sekvenserna tilldelats en variabel som procentuellt ökar chansen för utförandet av handlingen när handlingen har givit något positivt och det motsatta minskar när handlingen har orsakat något negativt.

<p>Esports have been a growing market segment for recreation and competition. Few works of research examine the decisions that competitors need to make to maximize the probability of winning. Game theory Nash equilibriums are used to evaluate options available for players to select out of game decisions related to side selection, character selection, and stage selection. Backward induction techniques are used to solve these subgame decisions. The introduction of a rating system for players is derived from traditional sport statistics. The primary factor tracked in damage dealt and damage received using the same framework from sabermetrics was used to predict outcomes of baseball games. Conclusions demonstrated tracking damage can be used to predict the outcome of a match. Other techniques such as principal component analysis did not provide adequate data to measure individual metrics for the use of predictive application.</p>

As the mobile games market keeps growing, game interfaces for mobile games also warrant further development. One area that especially has room for improvement is the touchscreen joystick. This dissertation focuses on the differences in usability for different touchscreen joysticks. A mobile fighting game prototype was developed for this purpose, and a user study was conducted in order to evaluate the difference in usability between two joysticks. Data was gathered and demonstrated, and an analysis of the logged data was conducted, showing no significant difference between the two joysticks. The authors hope that the comparison methodology and measurements demonstrated may be used as a benchmark and framework for future research in mobile joysticks.

Through the lens of hegemonic masculinity in the contemporary game development industry, this paper will present the current state of the LGBTQ+ representation in major Japanese fighting games that were released from 2010 to 2021. By performing a quantitative data analysis of the characters from the games, where each character is coded for their gender and sexuality, the frequency of representation can be determined over the period of time and across games which can indicate the state of LGBTQ+ representation in these games.  Not much research has been conducted in the field of gender studies and representation when specifically focusing on fighting games. It is also a genre that has the reputation of not having good representation and inclusion in the games, but also within the community. It is a genre where the characters are front and center and play a primary part in the appeal of the game, so having good representation should be a requirement. Many players will want to be able to identify and connect with the characters they play but for many this is not a possibility due to the lack of diversity. The results show that there may be a slight increase in the representation over time, but the numbers are still surprisingly low. This shows us the importance of needing to bring more attention to this topic as it is a critical issue that is present within this game genre but also within the gaming industry as a whole.

This report covers the eight week design project for the Thesis Project 1 and it looks at both the process and the results of this project. Through an iterative prototyping process a prototype was created to answer the research question: “What gameplay mechanics are required for a fighting style video game to allow for analog input in its character movements and do these mechanics allow for more natural controls and mastery?” Together with research into academic writing in the fields of neurology, embodied design and game design it was concluded that an analog control scheme, within the context of a video game that allows for that type of affordance, gives the user more natural control over the character they are playing. This was validated by playtesting the prototype with several users. However, the richness of the mastery of a game relies heavily on the implemented game elements in a finalized game and was therefore unanswered in this project. There were also constraints and game mechanics identified for game designers to keep in mind when designing a game that relies on this type of analog input. The project also raised a number of questions and new design opportunities that were unable to be explored due to the limited scope of the project.

Many online fighting games use rollback netcode in order to compensate for network delay. Rollback netcode allows players to experience the game as having reduced delay. A drawback of this is that players will sometimes see the game quickly ”jump” to a different state to adjust for the the remote player’s actions. Rollback netcode implementations require a method for predicting the remote player’s next button inputs. Current implementations use a naive repeatlastframe policy for such prediction. There is a possibility that alternative methods may lead to improved user experience. This project examines the problem of improving input prediction in fighting games. It details the development of a new prediction model based on recurrent neural networks. The model was trained and evaluated using a dataset of several thousand recorded player input sequences. The results show that the new model slightly outperforms the naive method in prediction accuracy, with the difference being greater for longer predictions. However, it has far higher requirements both in terms of memory and computation cost. It seems unlikely that the model would significantly improve on current rollback netcode implementations. However, there may be ways to improve predictions further, and the effects on user experience remains unknown. / Många online fightingspel använder rollback netcode för att kompensera för nätverksfördröjning. Rollback netcode låter spelare uppleva spelet med mindre fördröjning. En nackdel av detta är att spelare ibland ser spelet snabbt ”hoppa” till ett annat tillstånd för att justera för motspelarens handlingar. Rollback netcode implementationer behöver en policy för att förutsäga motspelarens nästa knapptryckningar. Nuvarande implementationer använder en naiv repetera-senaste-frame policy för förutsägelser. Det finns en möjlighet att alternativa metoder kan leda till förbättrad användarupplevelse. Det här projektet undersöker problemet att förbättra förutsägelser av knapptryckningar i fightingspel. Det beskriver utvecklingen av en ny förutsägelsemodell baserad på rekursiva neuronnät. Modellen tränades och evaluerades med ett dataset av flera tusen inspelade knappsekvenser. Resultaten visar att den nya modellen överträffar den naiva metoden i noggrannhet, med större skillnad för längre förutsägelser. Dock har den mycket högre krav i både minne och beräkningskostad. Det verkar osannolikt att modellen skulle avsevärt förbättra nuvarande rollback netcode implementationer. Men det kan finnas sätt att förbättra förutsägelser ytterligare, och påverkan på användarupplevelsen förblir okänd.

This study has been performed to give light to numerous observations from earlier studies in how characters are represented in video games. Through examination of 884 characters from 60 games and comparing them to each other depending if the game was violent or not, was a fighting game or not and how popular the game was this study was looking to find several answers regarding how the game industry works and how characters are being represented depending on these factors. This study found that the gender distribution has partially levelled out since former studies (Williams, et al., 2009; Downs och Smith, 2010) and that the hypersexualized  representation has decreased for female characters but increased for male characters for some hypersexual variables. Violent and fighting games hade larger male distribution of male characters, but only fighting games had more hypersexualized characters than its counterpart. Analyses regarding how popular the games was in comparison to each other gave no concrete results. / Denna studie har utförts för att ge ljus till flertalet observationer från tidigare studier om hur karaktärer representeras i digitala spel. Genom att undersöka 884 karaktärer från 60 spel och jämföra dem mot varandra beroende på om spelen var våldsamma eller ej, om spelet var ett slagsmålsspel eller ej och hur populärt spelet var söktes det flera svar om spelbranschen och hur karaktärer representeras beroende på dessa faktorer. Studien fann att könsfördelningen hade utjämnats delvis sedan tidigare studier (Williams, m fl., 2009; Downs och Smith, 2010) och att hypersexualiserad representation hade sjunkit för kvinnliga karaktärer men höjts för manliga karaktärer för vissa hypersexualiserade bedömningar. Våldsamma och slagsmålsspel hade större andelar män, men endast slagsmålsspel hade fler hypersexualiserade karaktärer än sin motpart. Analyser som berodde på hur populära spelen var i jämförelse med varandra visade inget konkret.