Abstract
In the field of gaming artificial intelligence, selecting the appropriate machine learning approach is essential for improving decision-making and automation. This paper examines the effectiveness of deep reinforcement learning (DRL) within interactive gaming environments, focusing on complex decision-making tasks. Utilizing the Unity engine, we conducted experiments to evaluate DRL methodologies in simulating realistic and adaptive agent behavior. A vehicle driving game is implemented, in which the goal is to reach a certain target within a small number of steps, while respecting the boundaries of the roads. Our study compares Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) in terms of learning efficiency, decision-making accuracy, and adaptability. The results demonstrate that PPO successfully learns to reach the target, achieving higher and more stable cumulative rewards. Conversely, SAC struggles to reach the target, displaying significant variability and lower performance. These findings highlight the effectiveness of PPO in this context and indicate the need for further development, adaptation, and tuning of SAC. This research contributes to developing innovative approaches in how ML can improve how player agents adapt and react to their environments, thereby enhancing realism and dynamics in gaming experiences. Additionally, this work emphasizes the utility of using games to evolve such models, preparing them for real-world applications, namely in the field of vehicles' autonomous driving and optimal route calculation.

Abstract
Purpose - This paper aims to generate knowledge of the impact of different virtual reality (VR) set-ups in tourism promotion regarding destination image, place attachment and behavioural intention.Design/methodology/approach - The paper presents a comparative study of the impact of different visualisation technologies (video, immersive VR and multisensory immersive VR) to promote tourism destinations. The study's dependent variables are destination image, place attachment and behaviour intention.Findings - Results show that VR content impacts these variables. Multisensory immersive VR is the preferred content type for destination promotion. It is also evidenced that female participants scored each variable higher than male participants. Males reported higher scores on the video set-up for destination image and place attachment. Behavioural intention reported higher values in the video when compared to immersive VR in both sexes.Practical implications - This paper concludes that there is a preference towards multisensory set-ups, which suggests that incorporating audiovisual and sensory elements can significantly enhance the effectiveness of VR experiences in attracting and engaging potential tourists.Originality/value - The paper contributes to the scarce body of knowledge regarding the impact of different VR factors on tourism promotion, including the multisensory VR component.

Abstract
The Web of Things (WoT) is an essential component within the Internet of Things (IoT) domain, offering a standardized method for describing, consuming, and orchestrating the functions of IoT devices. WoT plays a crucial role in promoting interoperability and streamlining the development of applications for IoT solutions. Recent research focusing on IoT solutions for ambient assisted living (AAL) has highlighted WoT as a key framework for integrating diverse smart devices and services to enhance the quality of life for older adults and individuals with specific health conditions. However, a closer look at recent literature reviews reveals a deficiency in comprehensive research regarding the interplay between WoT, AAL, and the health and wellbeing of older adults. To address this question, a comprehensive mapping review is performed to delve into the existing literature and pinpoint the most pertinent themes and topics within WoT. This analysis aims to uncover evidence of the correlation between WoT, AAL, and active and healthy aging (AHA) to support future research in this area.

Abstract
The modern manufacturing environment has adjusted to technological improvements. With Virtual Reality applications geared for factory training are becoming increasingly common. The industry is seeking ways to lower downtimes, resource component waste, risk of possible work accidents and decrease expenses, which can be achieved by engaging in new techniques of training professionals. This article evaluates a VR training application developed within the scope of the R&D project, aimed at training personnel in vehicle antenna production lines. We included the following variables: previous experience with VR technology, cybersickness, immersive tendencies, presence, system usability and satisfaction. Both the system usability scores and satisfaction were considered acceptable. We also found positive correlations between several variables, highlighting the possible influence of attention and familiarity with VR technology on the user experience. In contrast, a negative correlation raised questions about participants' expectations regarding VR technology and their resulting experience.

Abstract
The main goal of this paper is to investigate the effect of different types of self-representations through floating members (hands vs. hands + feet), virtual full body (hands + feet vs. full-body avatar), walking fidelity (static feet, simulated walking, real walking), and number of tracking points used (head + hands, head + hands + feet, head + hands + feet + hip) on the sense of presence and embodiment through questionnaires. The sample consisted of 98 participants divided into a total of six conditions in a between-subjects design. The HTC Vive headset, controllers, and trackers were used to perform the experiment. Users were tasked to find a series of hidden objects in a virtual environment and place them in a travel bag. We concluded that (1) the addition of feet to floating hands can impair the experienced realism (p = 0.039), (2) both floating members and full-body avatars can be used without affecting presence and embodiment (p > 0.05) as long as there is the same level of control over the self-representation, (3) simulated walking scores of presence and embodiment were similar when compared to static feet and real walking tracking data (p > 0.05), and (4) adding hip tracking overhead, hand and feet tracking (when using a full-body avatar) allows for a more realistic response to stimuli (p = 0.002) and a higher overall feeling of embodiment (p = 0.023).