Haptic technology has the potential to substantially support users in mastering complex activities and improving their performance. This paper presents a haptic assistance system for targeting in virtual reality (VR), designed to enhance accuracy and user confidence during aiming tasks by enabling users to sense proximity to and guiding their motion toward a target. To evaluate its effectiveness, we conducted a user study (N = 28) using a custom VR archery simulation, assessing both quantitative performance metrics and qualitative user feedback. With haptic guidance, participants achieved significantly higher targeting accuracy and reported increased spatial awareness, although some also noted a reduced sense of agency. These results suggest that, while haptic assistance offers clear benefits, careful design is essential to avoid overreliance or interference with user autonomy in contexts such as accessibility, gaming, and broader human-computer interaction.

Virtual reality (VR) is increasingly recognized as a powerful tool for science education, offering interactive environments to explore intangible concepts. Traditional teaching methods often struggle to convey abstract concepts in science, where many phenomena are not directly observable. VR can address this issue by modeling and visualizing complex and unobservable entities and processes, allowing learners to dynamically interact with what would otherwise not be directly perceptible. However, relatively few controlled studies have compared immersive VR learning with equivalent hands-on laboratory learning in physics education, particularly for more abstract topics. In this work, we designed a VR-based physics lab that is capable of visualizing electrons and electromagnetic fields to teach fundamental concepts of electronics and magnetism, closely replicating a traditional electronics learning kit used as a baseline for comparison. We evaluated the impact of the two conditions (VR versus traditional) on students' learning outcomes, motivation, engagement, and cognitive load. Our results show significantly higher knowledge retention in the VR group compared to the traditional group. Also, while there were no significant differences in immediate comprehension between the two groups, participants in the VR group spent substantially more time engaged with the learning content. These findings highlight the potential of visually enriched virtual environments to enhance the learning experience and improve knowledge retention of intangible scientific concepts.

Achieving a high level of immersion and adaptation in virtual reality (VR) requires precise measurement and representation of user state. While extrinsic physical characteristics such as locomotion and pose can be accurately tracked in real-time, reliably capturing mental states is more challenging. Quantitative psychology allows considering more intrinsic features like emotion, attention, or cognitive load. Time perception, in particular, is strongly tied to users' mental states, including stress, focus, and boredom. However, research on objectively measuring the pace at which we perceive the passage of time is scarce. In this work, we investigate the potential of electroencephalography (EEG) as an objective measure of time perception in VR, exploring neural correlates with oscillatory responses and time-frequency analysis. To this end, we implemented a variety of time perception modulators in VR, collected EEG recordings, and labeled them with overestimation, correct estimation, and underestimation time perception states. We found clear EEG spectral signatures for these three states, that are persistent across individuals, modulators, and modulation duration. These signatures can be integrated and applied to monitor and actively influence time perception in VR, allowing the virtual environment to be purposefully adapted to the individual to increase immersion further and improve user experience. A free copy of this paper and all supplemental materials are available at https://vrarlab.uni.lu/pub/brain-signatures.

An hour spent with friends seems shorter than an hour waiting for a medical appointment. Many physiological and psychological factors, such as body temperature and emotions, have been shown to correlate with our subjective perception of time. Experiencing virtual reality (VR) has been observed to make users significantly underestimate the duration. This paper explores the effect of virtual environment characteristics on time perception, focusing on two key parameters: user engagement and environmental dynamics. We found that increased presence and interaction with the environment significantly decreased the users’ estimation of the VR experience duration. Furthermore, while a dynamic environment lacks significance in shifting perception toward one specific direction, that is, underestimation or overestimation of the durations, it significantly distorts perceived temporal length. Exploiting these two factors’ influence smartly constitutes a powerful tool in designing intelligent and adaptive virtual environments that can reduce stress, alleviate boredom, and improve well-being by adjusting the pace at which we experience the passage of time.

Time experience is an essential part of one’s perception of any environment, real or virtual. In this article, from a virtual environment design perspective, we explore how rhythmic stimuli can influence an unrelated cognitive task regarding time experience and performance in virtual reality. This study explicitly includes physiological data to investigate how, overall, experience correlates with psychophysiological observations. The task involves sorting 3D objects by shape, with varying rhythmic stimuli in terms of their tempo and sensory channel (auditory and/or visual) in different trials, to collect subjective measures of time estimation and judgment. The results indicate different effects on time experience and performance depending on the context, such as user fatigue and trial repetition. Depending on the context, a positive impact of audio stimuli or a negative impact of visual stimuli on task performance can be observed, as well as time being underestimated concerning tempo in relation to task familiarity. However, some effects are consistent regardless of context, such as time being judged to pass faster with additional stimuli or consistent correlations between participants’ performance and time experience, suggesting flow-related aspects. We also observe correlations between time experience with eye-tracking data and body temperature, yet some of these correlations may be due to a confounding effect of fatigue. If confirmed as separate from fatigue, these physiological data could be used as reference point for evaluating a user’s time experience. This might be of great interest for designing virtual environments, as purposeful stimuli can strongly influence task performance and time experience, both essential components of virtual environment user experience. • Significant contextual stimuli effects on time experience depending on task familiarity and fatigue. • Consistent non-contextual effects of stimuli on time judgment. • Consistent non-contextual correlations between participants’ performance and time experience. • Correlations between participants’ time experience with eye-tracking data and body temperature.

This paper presents the initial results of a study exploring whether the perceived rapport with a virtual agent can influence users' decisions on delegating critical tasks to the agent. We hypothesize that users are more likely to delegate to virtual agents that attempt to build rapport with users than to agents that avoid building rapport. The samples we collected so far still need to validate the hypothesis fully. Nevertheless, we found that the perceived rapport with a virtual agent is highly relevant to trust in the agent.

Technological systems have been a part of human life since prehistory. Although they initially took the form of passive tools, such as axes and spoons, the Industrial Revolution saw the advent of powered, mechanized technology, operating “under it’s own steam,” without direct human control over every action. By integrating more complex information processing machinery, automation evolved into autonomy as decision-making and self-regulation became features of modern technology. Now, so-called intelligent systems, embodying techniques from the field of artificial intelligence (AI), are designed with the explicit intention of replicating rational behaviors and the sorts of things that minds do, inside technological systems.At the same time, the study of Artificial Life (ALife) (Langton, 1987) has explored the properties of living systems, both as they are found in nature, as they might be, and as humans can build them. This has exposed a large variety of mechanisms that produce qualities typically associated with life. Examples include self-organization, homeostasis, self-replication, evolution, learning, self-awareness, and many others besides.The Lifelike Computing Systems initiative (Stein et al., 2021b) aims to learn from the study of life and living systems to develop new, useful, “lifelike” systems; a further aim is to identify when such features are of value. The focus of this research direction is primarily on engineered technological systems broadly within the domain of computing.The notion of “lifelike computing” is not intended to separate itself from or replace previous initiatives; in a large number of cases, there are already technologies and research efforts that strongly lean toward lifelike computing systems in specific aspects. Building on a long and highly successful tradition in biologically inspired computing, the “lifelike” vision not only seeks inspiration in the living world but also seeks to replicate its qualities explicitly in technological systems. Indeed, we cannot claim that all bio-inspired systems remain lifelike, nor is this in general even always a desirable outcome for those designing bio-inspired systems. The agenda also goes beyond fundamental ALife research, often rightly exploratory in nature, because it focuses explicitly on building purposeful and reliable technological systems for people, based on ALife principles. Therefore the vision of explicit replication of lifelike qualities in technological systems of value to humanity marks a sharpening of focus.This special issue is a follow-up to the workshop series “Lifelike Computing Systems,” held at the International Conference on Artificial Life in 2020 and 2021 (Stein et al., 2021a), and again in 2022 (Stein et al., 2023). The workshop series hosted diverse talks showcasing early-stage research and work in progress, with topics ranging from plasticity in technical systems to artificial DNA, from self-explaining systems to realistic humanoid and animal robots.We have therefore solicited papers that explore and contribute to the discussion on research questions we deem key to be further explored: Which qualities of life are of high relevance and benefit for the engineering of lifelike computing systems useful to people? Why? How?How can we integrate and combine insights and methodological approaches from existing, related research initiatives, such as cybernetics, self-aware computing, organic computing, and autonomic computing?Which methods from domains like artificial life, bio-inspired computing, artificial intelligence, and self-adaptive and self-organizing systems contribute to achieving lifelike features of computing systems?When is more “lifelike” technology appropriate? What are the challenges associated with embedding technology that is more “lifelike” in society? How can these be tackled?This special issue represents an opportunity for more mature work emerging from this line of research to be presented. It contains four papers that together provide a review, analysis, and critique of the integration of lifelike properties into engineered systems, in many cases proposing concrete recommendations for future research directions and methods.In “Lessons from the Evolutionary Computation Bestiary,” Campelo and Aranha explore and critique the explosion of metaphor-centered metaheuristic methods that have been published in recent years and that claim to be inspired by—in their view—increasingly absurd natural phenomena. Examples surveyed include several different types of birds, mammals, fish, and invertebrates; soccer and volleyball; and even reincarnation, zombies, and gods. The authors acknowledge that metaphors can be powerful inspiration and explanatory tools and that, indeed, the field of metaheuristics has a long history of finding inspiration in natural systems, starting from evolution strategies, genetic algorithms, and ant colony optimization. However, they question the value of the emergence of hundreds of highly similar variants of essentially the same algorithm under different labels. The authors have curated a “bestiary” of such variants over the years, and their article in this issue reviews this, arguing that this proliferation has been counterproductive to scientific progress in the field. They argue that it does little to improve our ability to understand and simulate biological systems and that it can actively impede an improved understanding of how to design and analyze global optimization techniques. The article discusses why this social phenomenon in research may have occurred in recent years and its negative consequences, ending with a call to improve the scientific soundness of metaheuristic research.In “Does the Field of Nature-Inspired Computing Contribute to Achieving Lifelike Features?,” Tzanetos asks whether all nature-inspired algorithms remain lifelike. The article considers the history of evolutionary computation and, as in the first article, the proliferation of many so-called nature-inspired techniques in recent years. The author juxtaposes the value of such techniques in solving hard problems with an analysis to support an argument that the mathematics of these techniques often does not match the source behavior faithfully. In these cases, can it be said that the algorithms are indeed “lifelike,” and if not, does that matter, so long as they provide value in terms of their ability to solve problems intelligently? The article argues that historically, there was greater alignment between the algorithmic models and source behaviors, but this is often not seen in more recent attempts. The article ends by discussing if there is a need for new lifelike features of algorithms, concluding that this is not helpful—instead presenting recommendations for future research in nature-inspired computing, which, the authors argue, would move the field in “the right direction.”In “Assessing Model Requirements for Explainable AI: A Template and Exemplary Case Study,” Heider et al. explore the explainability of decision support systems that use evolutionary rule-based machine learning techniques, more precisely, learning classifier systems (LCSs). Self-adaptive and self-optimizing systems are necessarily dynamic, yet for them to be accepted by people in sociotechnical settings, explanations for machine-made decisions are often essential. The authors argue that rule-based machine learning models, such as LCSs, present an opportunity for transparent machine learning models that naturally support access to explanations. To assist with designing and evaluating such models, they also propose a generic and thus broadly applicable questionnaire template. The template is demonstrated to provide valuable insights for the design of such LCS models in specific scenarios. The approach is illustrated in a manufacturing case study.Finally, in “Artificial Collective Intelligence Engineering: A Survey of Concepts and Perspectives,” Casadei surveys computational techniques based on or harnessing “collectiveness,” often seen in many living systems, to produce capabilities beyond what can be achieved with individual or monolithic systems. A key concept common to these techniques is that such systems can exploit a large number of individuals to produce intelligent collective behavior out of not-so-intelligent components. The article argues that there is a trend in some areas of engineering toward this way of designing technological systems, citing examples such as the Internet of Things, swarm robotics, and crowd computing and emphasizing that these technologies span many techniques, systems, and application areas. An essential finding of the review is that there is substantial fragmentation of this research, however, and that the so-called “verticality” of research communities makes a common fundamental understanding of such systems challenging to achieve. The author argues that an important challenge is identifying, placing in a common structure, and ultimately connecting the different areas and methods addressing intelligent collectives. As such, the article presents a set of questions aimed at mapping out collective intelligence research. It uses this to develop a set of preliminary notions, concepts, and perspectives, as well as associated research opportunities, to develop a more fundamental understanding of computational collective intelligence engineering.The guest editors thank the authors of papers submitted to the “Lifelike Computing Systems” special issue as well as the reviewers, who gave valuable feedback to all the authors. We would also like to thank the organizers of the ALife conferences that hosted the Lifelike Computing Systems workshops as well as all the speakers and participants who contributed to many vibrant debates that informed the direction of the final set of articles in this issue. Last, we thank the Board of Editors of Artificial Life for supporting this special issue.

Despite already being commonplace, delegation to robotic virtual agents (VAs) is often considered challenging and error-prone in critical situations by the general public. Theory of mind, the human capacity to take another person's perspective, is deemed an important enabler for human-human cooperation. This study explores the effect of a robotic VA's ability to use theory of mind on users' delegation behavior. To this end, we conducted a between-subjects experiment with participants playing the Colored Trails game with robotic VAs of varying levels of theory of mind. The results invalidate our hypothesis that the ToM level is a reliable indicator of delegation choices. Instead, we found that the participants' performance strongly correlates with their delegatory intentions. Therefore, to facilitate delegation, designers of robots and robotic agents may consider refraining from using ToM-resemblance features and focusing on balancing user performance perception instead to induce the desired delegation behaviors.

Recent intelligent virtual agents (IVAs) are increasingly tasked with critical activities such as financial investment and vehicle control. However, the mechanics behind delegatory behaviors toward IVAs are not fully explored, especially when multiple factors come into play. This paper aims to investigate how different agent-related factors, such as capability and trustworthiness, influence users’ decisions on critical-transaction delegation to IVAs. We conducted an experiment constituting a variation of the investment game where participants interact with a robot-like IVA in a virtual environment. We found that, early during the interaction, the informativeness of the agent is more important than other acknowledged factors, such as agent capability. Also, most of these factors have a stable impact on delegation decisions early during the interaction, whereas only a few factors, such as agent usability, have a dynamic impact. Our findings provide guidelines for the design of trustworthy IVA for virtual environments and various levels of immersion.

The research initiative “self-improving system integration” (SISSY) was established with the goal to master the ever-changing demands of system organisation in the presence of autonomous subsystems, evolving architectures, and highly-dynamic open environments. It aims to move integration-related decisions from design-time to run-time, implying a further shift of expertise and responsibility from human engineers to autonomous systems . This introduces a qualitative shift from existing self-adaptive and self-organising systems, moving from self-adaptation based on predefined variation types, towards more open contexts involving novel autonomous subsystems, collaborative behaviours, and emerging goals. In this article, we revisit existing SISSY research efforts and establish a corresponding terminology focusing on how SISSY relates to the broad field of integration sciences. We then investigate SISSY-related research efforts and derive a taxonomy of SISSY technology. This is concluded by establishing a research road-map for developing operational self-improving self-integrating systems.

The collaborative authoring of complex document structures by geographically distributed users is no longer a special case in today's global economy or people's personal lives. However, integrating single-user application responsiveness and feature sets with the additional demands and expectations presented towards distributed multi-user environments remains a challenge. Current solutions approaching this challenge almost exclusively rely on traditional, file-based data structures. This often introduces arbitrary workflow restrictions to the user and reduces the potential to benefit from an otherwise inherently concurrent system. Our distributed compound document authoring environment aims at addressing these challenges while providing system-level collaboration support to the user. We attain this through the close integration of a fine-grained data structure with a highly scalable, priority-based concurrency model for command distribution and application. This paper discusses our enhanced data representation and concurrency model together with the evaluation of their prototypical implementation.

Computer-supported collaborative learning scenarios provide an opportunity for the participants to develop their conceptual understanding of a topic in a shared e-learning environment. This requires the integration of collaborative and cooperative authoring functionality for a wide range of distinct types of data, including multimedia. However, restricting access to currently manipulated elements by the means of locks and requiring the user to manually initiate and manage the synchronization process are still common side-effects to this support. Allowing for predominantly unrestricted, interruption-free and non-destructive multimedia editing in a distributed collaborative learning environment thus still presents a challenge. We propose to address these issues by integrating a fine-grained data model, concurrency-based command processing, and a primarily autonomous consistency management approach. Distinct editing operations by individual participants define manipulations on data type-specific attributes, which form the basis for an up-to-date representation of the targeted multimedia assets. We utilize an advanced Compound Document System and accompanying data models to allow for a feature rich, yet responsive and unobtrusive collaboration environment.

A new generation of networked applications and social utilities, originating inter alia from the ongoing trend towards high-performance mobile devices, tightens exigencies relative to the processing of sensitive data. However, in order to ensure their correct operation, many of these applications re

With the growth of Massively Multiuser Virtual Environments (MMVEs) and increasingly interactive social net working platforms, it is widely accepted that their convergence renders today's centralized hosting approaches impracticable. To handle virtual environments of such massive scale, decentralize

The idea of the 3D Web as a global scale Distributed Virtual Environment (DVE) currently is very popular and a lot of research work is done in this field. In the course of the HyperVerse project we have developed a two-tier Peer-To-Peer (P2P) architecture as basic infrastructure for a federated, open and scalable 3D Web. Our approach relies on a concept that incorporates a loosely-structured P2P network overlay of user clients and a highly-structured overlay that connects a federation of reliable server machines constituting a reliable backbone service. A central problem when intending to build a massive virtual online environment is how avatar interaction as well as tracking and provision of avatar positions can be realized in a globally scalable manner. This paper presents a hybrid avatar interaction scheme developed for HyperVerse that incorporates the user clients and the backbone service for avatar position tracking. The backbone is used as reliable fall-back service, while the avatar tracking is handled in a pure P2P fashion whenever possible. This way backbone overload is prevented in a self-organizing manner whenever client density tends to overburden the backbone infrastructure.

The ever-increasing amount of available information in today's digital society necessitates inline techniques for determining the most relevant content. Collaborative filtering (CF) systems have proven to be an adequate means for reducing informational overload and generating useful recommendations.

Massive Multiuser Virtual Environments (MMVEs) and especially the idea of a ''3D Web'' as a combination of a MMVE and today's WWW currently attracts a lot of attention. The realization of such a vision on a global scale though poses severe technical challenges to the underlying network infrastructure. It is generally accepted that such a global scale scenario can only be realized in a distributed fashion. The HyperVerse project aims at the provision of a federated global scalable infrastructure for such a ''3D Web'' scenario. We propose a two-tier Peer-To-Peer infrastructure that combines a loosely structured overlay network of user clients with a highly-structured overlay network of reliable so-called public servers constituting the backbone of our architecture. This paper presents the Grid-based plane Partitioning Protocol (GP3), a structured peer-to-peer overlay network for the interconnection of the public servers that realizes a spatial index in order to allow fast location based queries.