Behavioural Reactive Agents for Video Game Opponents with Personalities

Nowadays, the video gaming experience is shifting from merely realistic to believable. The increasing graphic power of current graphic cards has made it possible to render near lifelike images. Unfortunately, the behaviour of the computer driven player and non-playing characters is often poor when compared to their visual appearance. In this sense, there has been a recent interest in improving the video gaming experience with novel Artificial Intelligence (AI) techniques. This paper presents a robotics inspired behavioural AI technique to simulate characters' personalities in an multi-award winning commercial video game.

Currently, few studies focus on analysing the degree of the Player eXperience (PX) in video games. Video games have now become interactive entertainment systems with a high economic impact on society; these are interactive systems characterised by their subjectivity, which differ from other systems in that their main objective is to entertain and amuse the user (player). This work discusses the analysis and evaluation of the User eXperience (UX) in interactive entertainment systems, exploring how usability, given its definition, objectives and the fact it is one of the main dimensions of UX, is not sufficient to characterise the PX, giving rise to a new concept: Playability. In this paper, we present a framework for the analysis and evaluation of the UX in video games. The results show the need and importance of a framework to help us understand and measure the experience that players feel using these types of interactive systems, in order to improve the experience during play time. The proposed framework characterises the experience using attributes to identify and properties to measure UX. It thus provides a multifaceted analysis mechanism to assess the impact of the gaming experience and its relationship with the elements of a video game. We therefore present a system to represent UX based on this framework, with the aim of ensuring and measuring a satisfactory experience of the entertainment system. Finally, we discuss a practical experiment in which an evaluation of the playability of a commercial video game was carried out using the methods proposed in this work.

Video gaming is now available as a fully immersive experience that creates responsive inputs and outputs concerning the user, and some experimental developers have integrated the use of the voice, brain, or muscles as input controls. The use of physiological signal equipment can provide valuable information regarding the emotion of a player or patient during gameplay. In this article, we discuss five of the most common biosignals that are used in gaming research, and their function and devices that may be used for measurement. We break down those individual signals and present examples of research studies that implement them. We also discuss the usage of biological signals within commercial gaming and conclude with some possible future directions for the use of biological signals in gaming and game research.

Nowadays, video games conforms a huge industry that is always developing new technology. In particular, artificial intelligence techniques have been used broadly in the well-known non-player characters (NPC) given the opportunity to users to feel video games more real. This paper proposes the usage of the MaxQ-Q hierarchical reinforcement learning algorithm in non-player characters in order to increase the experience of the user in terms of naturalness. A case study of an NPC with the proposed artificial intelligence based algorithm in a first personal shooter video game was developed. Experimental results show that this implementation improves naturalness from the user’s point of view. In addition, the proposed MaxQ-Q based algorithm in NPCs allow to programmers a robust way to give artificial intelligence to them.

Authoring the AI for non-player characters (NPCs) in modern video games is an increasingly complex task. Designers and programmers must collaborate to resolve a tension between believable agents with emergent behaviours and scripted story lines. Behaviour trees (BTs) have been proposed as an expressive mechanism that let designers create complex behaviours along the lines of the story they want to tell. However, BTs are still too complex for non-programmers. In this paper, we propose the use of plan traces to assist designers when building BTs. In order to make this approach feasible within state-of-the-art video game technology, we generate the planning domain through an extension of the component-based approach, a widely used technique for representing entities in commercial video games.

Several decades of research have established that video game experience is associated with differences in social information processing, visual-spatial processing, and cognitive control. Fewer studies have examined the relationship between video game experience and risky decision making outside of the gaming environment. The current set of studies examined the hypothesis that video game experience is associated with riskier decision making due to differential sensitivity to outcomes (i.e., reward, punishment). Study 1 was designed to explore the relationships between video game experience, risky decision making, and sensitivity to outcomes in a large sample of individuals. Study 2 was designed to investigate the association between individual differences in video game experience and the neural correlates of outcome sensitivity. Finally, Study 3 was designed to establish a causal relationship between immediate, brief experience with a video game and sensitivity to outcomes. The findings from the three studies indicate that video game experience is associated with differences in outcome sensitivity, but the relationship is complex and may depend on various factors, such as the genre of the video game and the presence of symptoms of pathological use. The data from the current set of studies should serve as a starting point for further research examining video games and risky decision making.

Video games can be a valuable tool for surgery training. Individuals who interact or play video games tend to have a better visuospatial ability when compared to non-gamers. Numerous studies suggest that video game experience is associated with faster acquisition, greater sharpening, and longer retention of laparoscopic skills. Given the neurocognitive complexity of surgery skill, multimodal approaches are required to understand how video game playing enhances laparoscopy skill. Twenty-seven students with no laparoscopy experience and varying levels of video game experience performed standard laparoscopic training tasks. Their performance, subjective cognitive loading, and prefrontal cortical activity were recorded and analyzed. As a reference point to use in comparing the two novice groups, we also included data from 13 surgeons with varying levels of laparoscopy experience and no video game experience. Results indicated that video game experience was correlated with higher performance (R2 = 0.22, p <0.01) and lower cognitive load (R2 = 0.21, p <0.001), and the prefrontal cortical activation of students with gaming experience was relatively lower than those without gaming experience. In terms of these variables, gaming experience in novices tended to produce effects similar to those of laparoscopy experience in surgeons. Our results suggest that along the dimensions of performance, cognitive load, and brain activity, the effects of video gaming experience on novice laparoscopy trainees are similar to those of real-world laparoscopy experience on surgeons. We believe that the neural underpinnings of surgery skill and its links with gaming experience need to be investigated further using wearable functional brain imaging.

An important step towards gaining an understanding of how a particular medium can be used most effectively in education is to study its outstanding examples, regardless of their original purpose. It is assumed that “good” games already embody sound pedagogy in their designs even if that incorporation was not deliberate. The work described here is intended as a proof of concept for a larger study in progress. The following paragraphs will examine two games: one a commercial and critical success and the other designed deliberately as an educational game. The commercial game will be viewed as though it had been designed as a learning object. Through this perspective, it is possible to identify and classify built-in learning objectives and from there to associate the mechanisms and strategies employed to teach them. A significant outcome of the final work will be to describe how the existing strategies used to promote “learning objectives” in commercial video games can be used in the design of educational games. An additional outcome will be a synthesis of the core requirements for instructional design of digital games for learning. Anyone who makes a distinction between games and learning doesn't know the first thing about either.

Video games, particularly role-playing games (RPGs), have become narrative and emotional spaces where players not only follow complex plots but also form affective bonds with non-player characters (NPCs). This article analyses such parasocial relationships through two perspectives: the Affectivity System (AS), which structures the bond between player and NPC, and the model of emotions in video games, which distinguishes among narrative (Fictional), aesthetic (Artefact), and interactive (Gameplay) emotions. The focus is on Clair Obscur: Expedition 33 (Sandfall Interactive, 2025), a European JRPG that integrates mechanics designed to build deep emotional relationships with NPCs. Here, affective interaction is not a byproduct but a central component of the design. The article opens with a reflection on the concept of para-sociality, showing how the interactivity of video games transforms the player into an active agent in the relationship. In this context, the ability to recognize emotions and intentions in virtual characters triggers genuine empathetic responses, making the experience deeply engaging.

A game usually used as a synonym for entertainment also serves as an educational tool. Originally targeting the enjoyment, the meaning of the game has evolved to much greater conceptions and applications. Games require physical or mental or sometimes both the simulation. Many games help develop practical skills, serve as a form of exercise, or otherwise perform an educational, simulation, or psychological role. Having to be built on some key elements, which are goals, rules, challenge, and interaction. Various strategies and algorithms such as path finding and decision trees, have been developed to simulate those interactions between the human user and the computer in front of him. In video games, artificial intelligence (AI) is used to generate responsive, adaptive or intelligent behaviours primarily in non-player characters (NPCs) similar to human-like intelligence. This paper makes a short analysis of those preferred techniques and suggest from the study and the outcomes, the efficiency of each. The paper also focuses on the heuristic function, implementation platforms and design guidelines of the various searching algorithms used in adaptive games.

&lt;p&gt;&lt;b&gt;Research problem – The average age of video game players is above 30 in many parts of the world, but the literature surrounding video games in public libraries often focuses on engaging children and teenagers. This suggests that there may be an underserved population of video game players in public libraries.&lt;/b&gt;&lt;/p&gt; &lt;p&gt;In addition to this, successful video game ventures require organisers familiar with and knowledgeable about video games. It is unknown whether public library staff in general possess these qualities, or if they are engaged with video game services.&lt;/p&gt; &lt;p&gt;This report aimed to investigate how public library staff in Aotearoa New Zealand (NZ) engage with video games and video game services.&lt;/p&gt; &lt;p&gt;Methodology – Invitations to participate in an online questionnaire were sent to 20 public library systems and the NZ-Libs email list. Five organisations agreed to distribute the questionnaire to their staff. A sample size of 183 respondents was achieved. Questions were asked about video game experiences, perceptions, and library services.&lt;/p&gt; &lt;p&gt;Results – NZ public library staff appear to engage with video games in a similar way to the general NZ population. In addition, there appears to be an overall positive perception of their place in public libraries (87% of respondents supported video games in public libraries).&lt;/p&gt; &lt;p&gt;Video game players appear to think more positively about video games and be more aware of their impact on individuals compared to non-players. They also appear to be more confident in delivering related services and more likely to be running related events.&lt;/p&gt; &lt;p&gt;Video game services in NZ public libraries seem to largely target younger age groups, mirroring the perceived main target audience for video games indicated by respondents. This revealed a potentially underserved population (video game players aged 46 – 84) for NZ public libraries that offer video game services.&lt;/p&gt; &lt;p&gt;Implications – It appears that encouraging engagement with video games may improve staff confidence in delivering video game services, although further research is required to confirm this.&lt;/p&gt; &lt;p&gt;In addition, there is a potentially underserved population of video game players aged 46 – 84, who account for nearly half of the 46 – 84 year old population. Evaluation of this potentially underserved population is an interesting topic for future research.&lt;/p&gt;

The growing capabilities of large language models (LLMs) have inspired recent efforts to integrate LLM-generated dialogue into video games. However, evaluation remains a major challenge: how do we assess the player experience in a commercial game augmented with LLM-generated dialogue? To explore this question, we introduce a dynamic evaluation framework for the dialogue management systems that govern the task-oriented dialogue often found in roleplaying video games. We first extract dialogue from the widely-acclaimed role-playing game *Disco Elysium: The Final Cut*, which contains 1.1M words of dialogue spread across a complex graph of utterances where node reachability depends on game state (e.g., whether a certain item is held). Using this dataset, we have GPT-4 perform *dialogue infilling* to generate grounded utterances based on game state represented via code. In a statistically robust study of 28 players recruited from the r/DiscoyElysium subreddit, the LLM outputs are evaluated against the game designers' writing via both preference judgments and free-form feedback using a web interface that recreates the game's core conversation functionality. Overall, the game designers' prose is significantly preferred to GPT-4 generations, with participants citing reasons such as improved logical flow and grounding with the game state. To spur more principled future research in this area, we release our web interface and tools to enable researchers to build upon our work. https://pl.aiwright.dev

Anagram is a turn-based role-playing game where two players construct words by arranging given letters. A significant aspect of playing a game is the challenge. A good challenge comes from an opponent with a close ability. In a two-player game like Anagram, the second player can be a nonhuman player called Non-Playable Character (NPC). A balanced game is more engaging. Therefore, it is imperative to insert artificial intelligence (AI) into an NPC to make it possess a balance ability. This study investigates the AI algorithm that is the most appropriate to make a balance NPC for Anagram games. We tested three scenarios: Descending AI, Random AI, and AI with k-Nearest Neighbour (k-NN). Descending AI gets an Anagram solution by selecting a word with the highest score from all possible answers. Random AI picks a word randomly from the possible answers, while AI with k-NN chooses a word closest to one of the human players. The results show that Descending AI is the best algorithm to make the strongest NPC, which always gets the highest score, followed by Random AI and AI with k-NN. However, AI with the k-NN algorithm makes the constructed NPC has the highest number of turns at an average of 18, while Descending AI gets 14 turns and Random AI has 15 turns. Looking at the remaining lives at the end of the game, AI with k-NN makes the NPC has 25 lives left, while Descending AI has 59 lives, and Random AI has 48 lives. Less remaining lives suggest that NPC containing AI with the k-NN algorithm matches closer to the human player and therefore is more suitable for Anagram NPC.

Non-Playable Characters (NPCs) are a subtype of virtual agents that populate video games by endorsing social roles in the narrative. To infer NPCs’ roles, players evaluate NPCs’ appearance and behaviors, usually by ascribing human traits to NPCs, such as intelligence, likability and morality. In particular, hostile NPCs in video games are essential to build the games’ inherent challenges. The three experiments reported here investigated the extent to which the perception of hostility in a military shooter game (including both threat of appearance and aggressiveness in behaviors) is influenced by the appearance and the behaviors of NPCs thanks to perceived intelligence, likability and morality-related questionnaires. Our results first show that hostility is efficiently conveyed through NPCs’ behaviors, but not significantly by their appearance. Second, our study allows identifying the main predictors of hostility perception, namely unfriendliness, knowledge and harmfulness.

We compared the feasibility of, adherence to, and satisfaction with a newly developed upper extremity (UE) self-training protocol using commercial video games with a traditional self-training program for people with chronic stroke. Twenty-four participants with mild to moderate UE weakness were randomized to a video game (n = 13) or traditional (n = 11) self-training program. Participants were requested to train 60 min/day, 6×/wk. During the 5-wk self-training program and 4-wk follow-up, participants documented their self-training time and rated their perceived enjoyment and exertion. Eleven participants completed video game training; 9 completed traditional self-training. During the follow-up period, 8 participants (72.7%) continued the video game training, and 4 (44.4%) continued traditional training. Perceived enjoyment, satisfaction, and benefit for UE improvement were relatively high. Participants demonstrated high adherence to and satisfaction with both self-training programs. More participants continued to play video games after the intervention, indicating its potential to maintain ongoing activity.