Hasil untuk "Human ecology. Anthropogeography"

Kiyosu Maeda, William P. McCarthy, Ching-Yi Tsai et al.

A quintessential feature of human intelligence is the ability to create ad hoc conventions over time to achieve shared goals efficiently. We investigate how communication strategies evolve through repeated collaboration as people coordinate on shared procedural abstractions. To this end, we conducted an online unimodal study (n = 98) using natural language to probe abstraction hierarchies. In a follow-up lab study (n = 40), we examined how multimodal communication (speech and gestures) changed during physical collaboration. Pairs used augmented reality to isolate their partner's hand and voice; one participant viewed a 3D virtual tower and sent instructions to the other, who built the physical tower. Participants became faster and more accurate by establishing linguistic and gestural abstractions and using cross-modal redundancy to emphasize key changes from previous interactions. Based on these findings, we extend probabilistic models of convention formation to multimodal settings, capturing shifts in modality preferences. Our findings and model provide building blocks for designing convention-aware intelligent agents situated in the physical world.

Merle M. Reimann, Koen V. Hindriks, Florian A. Kunneman et al.

When encountering a robot in the wild, it is not inherently clear to human users what the robot's capabilities are. When encountering misunderstandings or problems in spoken interaction, robots often just apologize and move on, without additional effort to make sure the user understands what happened. We set out to compare the effect of two speech based capability communication strategies (proactive, reactive) to a robot without such a strategy, in regard to the user's rating of and their behavior during the interaction. For this, we conducted an in-person user study with 120 participants who had three speech-based interactions with a social robot in a restaurant setting. Our results suggest that users preferred the robot communicating its capabilities proactively and adjusted their behavior in those interactions, using a more conversational interaction style while also enjoying the interaction more.

Burcu Sayin, Ipek Baris Schlicht, Ngoc Vo Hong et al.

Clinical decision-making is inherently complex, often influenced by cognitive biases, incomplete information, and case ambiguity. Large Language Models (LLMs) have shown promise as tools for supporting clinical decision-making, yet their typical one-shot or limited-interaction usage may overlook the complexities of real-world medical practice. In this work, we propose a hybrid human-AI framework, MedSyn, where physicians and LLMs engage in multi-step, interactive dialogues to refine diagnoses and treatment decisions. Unlike static decision-support tools, MedSyn enables dynamic exchanges, allowing physicians to challenge LLM suggestions while the LLM highlights alternative perspectives. Through simulated physician-LLM interactions, we assess the potential of open-source LLMs as physician assistants. Results show open-source LLMs are promising as physician assistants in the real world. Future work will involve real physician interactions to further validate MedSyn's usefulness in diagnostic accuracy and patient outcomes.

Xingru Zhou, Sadanand Modak, Yao-Cheng Chan et al.

The rapid growth of AI in robotics has amplified the need for high-quality, reusable datasets, particularly in human-robot interaction (HRI) and AI-embedded robotics. While more robotics datasets are being created, the landscape of open data in the field is uneven. This is due to a lack of curation standards and consistent publication practices, which makes it difficult to discover, access, and reuse robotics data. To address these challenges, this paper presents a curation and access system with two main contributions: (1) a structured methodology to curate, publish, and integrate FAIR (Findable, Accessible, Interoperable, Reusable) human-centered robotics datasets; and (2) a ChatGPT-powered conversational interface trained with the curated datasets metadata and documentation to enable exploration, comparison robotics datasets and data retrieval using natural language. Developed based on practical experience curating datasets from robotics labs within Texas Robotics at the University of Texas at Austin, the system demonstrates the value of standardized curation and persistent publication of robotics data. The system's evaluation suggests that access and understandability of human-robotics data are significantly improved. This work directly aligns with the goals of the HCRL @ ICRA 2025 workshop and represents a step towards more human-centered access to data for embodied AI.

Botao 'Amber' Hu, Danlin Huang

The recent more-than-human turn in design calls for attentiveness to nonhuman beings. Yet -- as Thomas Nagel's famous ``What is it like to be a bat?'' thought experiment highlights -- human experience is constrained by our own sensorium and an irreducible gap in phenomenal access to nonhuman \emph{Umwelten}. Grounded in eco-phenomenology and eco-somatics, this paper proposes \textbf{Experiencing More-than-Human through Human Augmentation} (MtHtHA, or ``>HtH+''), a design approach that repurposes human augmentation technologies -- typically aimed at enhancing human capabilities for human optimization -- to create temporary, embodied, first-person experiences that modulate the human sensorium to approximate nonhuman sensory experiences, cultivating ecological awareness, empathy, and care across species boundaries. We articulate seven design principles, report five design cases -- EchoVision (bat-like echolocation), FeltSight (star-nosed-mole tactile navigation), FungiSync (fungal network attunement), TentacUs (octopus-like distributed agency), and City of Sparkles (urban data from an AI's perspective) -- and discuss implications for more-than-human aesthetics and design practice.

Caio C. G. Ribeiro, Douglas G. Macharet

The increasing presence of robots in human environments requires them to exhibit socially appropriate behavior, adhering to social norms. A critical aspect in this context is the concept of personal space, a psychological boundary around an individual that influences their comfort based on proximity. This concept extends to human-robot interaction, where robots must respect personal space to avoid causing discomfort. While much research has focused on modeling personal space in two dimensions, almost none have considered the vertical dimension. In this work, we propose a novel three-dimensional personal space model that integrates both height (introducing a discomfort function along the Z-axis) and horizontal proximity (via a classic XY-plane formulation) to quantify discomfort. To the best of our knowledge, this is the first work to compute discomfort in 3D space at any robot component's position, considering the person's configuration and height.

Pierre Quévreux, Ulrich Brose, N. Galiana et al.

The concept of ecological interaction networks has been widely used in fundamental ecology in the last two decades and has progressively infused in a diverse array of applied studies. Classical studies represented species interactions as static interaction webs to identify generalities in the structure of ecological networks and understand the propagation of indirect effects of species on each other and the environment. More recent research demonstrates that ecological networks are emerging features of community and interaction processes. Understanding the determinants of interaction variability in space and time and its consequences for biodiversity dynamics and ecosystem functioning constitute current frontiers in ecological network science. Although these frontiers meet a variety of applied ecological questions, many network models have been developed without clear applied perspectives. We detail how we could build on them to advance three main topics. First, the spatial dimension of ecological networks has direct implications for the design of sustainable landscapes and fisheries, for agroecology and for lake management. Second, the temporal dimension of ecological networks provides important insights for projecting biodiversity changes and adapting human actions. Third, the interactions between the abiotic and biotic components of ecosystems constitute key drivers of biogeochemical cycles, thereby providing important levers for sustainable management. Synthesis and applications. Collaborative work between empirical and theoretical network ecologists could accelerate the delivery of realistic models to inform applied practices across disciplines.

Francisco Martin Villarreal Solis, Mario Alberto García Meza, Jose Gerardo Ignacio Gómez Romero

Este artículo analiza el impacto de la presencia del crimen organizado en las remesas en México durante la pandemia de covid-19. La hipótesis plantea que el crimen organizado ha capitalizado el incremento en los flujos de remesas como una estrategia para introducir dinero ilícito tras el cierre de fronteras. Se analizó el comportamiento de las remesas en 74 municipios de 23 áreas metropolitanas y se compararon los periodos previo y posterior a la pandemia. Los resultados muestran un aumento de 23% en las remesas en regiones con alta presencia del crimen organizado, frente a 8.47% en otras zonas urbanas.

Rahmat Lazuardi, Vera Septiawati, Anis Septiani

This study evaluates the impact of daily traffic activity at the four-legged intersection at the Cimencrang railway crossing, in the Al Jabbar Mosque area, using the Indonesian Road Capacity Guidelines (PKJI) 2023. The aim of this study is to assess the traffic performance affecting the efficiency of at-grade road and railway crossings in the area. This evaluation is essential to understand the traffic dynamics in the area, which will help the government in designing traffic and transportation management methods to reduce future congestion. Traffic data was collected through direct surveys during peak hours on weekdays, covering vehicle volume, vehicle types, and the geometric dimensions of the roads at the intersection. The evaluation results indicate that the intersection’s Volume to Capacity Ratio (VCR) at the study site is 0.74. The findings also suggest that this four-legged intersection frequently experiences critical conditions, with Levels of Service (LOS) ranging from C to E during busy hours. The study recommends improving traffic management and infrastructure to enhance performance and traffic conditions, as well as road user safety in this area. It is hoped that these findings can serve as a foundation for local government in planning more effective traffic policies in the area, and provide insights into the processes and procedures of traffic evaluation at four-legged intersections.

Márton Karsai, Hang-Hyun Jo

Bursty dynamics characterizes systems that evolve through short active periods of several events, which are separated by long periods of inactivity. Systems with such temporal heterogeneities are not only found in nature but also include examples from most aspects of human dynamics. In this Chapter, we briefly introduce such bursty phenomena by first walking through the most prominent observations of bursty human behavior. We then introduce several conventional measures that have been developed for characterizing bursty phenomena. Finally, we discuss the fundamental modeling directions proposed to understand the emergence of burstiness in human dynamics through the assumption of task prioritization, temporal correlations, and external factors. This Chapter is only a concise introduction to the field. Still, it provides the most important references, which will help interested readers to learn in depth the ever-growing research area of bursty human dynamics.

Haoyang Jiang, Elizabeth A. Croft, Michael G. Burke

Communication is essential for successful interaction. In human-robot interaction, implicit communication holds the potential to enhance robots' understanding of human needs, emotions, and intentions. This paper introduces a method to foster implicit communication in HRI without explicitly modelling human intentions or relying on pre-existing knowledge. Leveraging Transfer Entropy, we modulate influence between agents in social interactions in scenarios involving either collaboration or competition. By integrating influence into agents' rewards within a partially observable Markov decision process, we demonstrate that boosting influence enhances collaboration and interaction, while resisting influence promotes social independence and diminishes performance in certain scenarios. Our findings are validated through simulations and real-world experiments with human participants in social navigation and autonomous driving settings.

Louis Annabi, Ziqi Ma, Sao Mai Nguyen

This early-stage research work aims to improve online human-robot imitation by translating sequences of joint positions from the domain of human motions to a domain of motions achievable by a given robot, thus constrained by its embodiment. Leveraging the generalization capabilities of deep learning methods, we address this problem by proposing an encoder-decoder neural network model performing domain-to-domain translation. In order to train such a model, one could use pairs of associated robot and human motions. Though, such paired data is extremely rare in practice, and tedious to collect. Therefore, we turn towards deep learning methods for unpaired domain-to-domain translation, that we adapt in order to perform human-robot imitation.

Ana M. Casado Faulí, Mario Malizia, Ken Hasselmann et al.

As drones are getting more and more entangled in our society, more untrained users require the capability to operate them. This scenario is to be achieved through the development of artificial intelligence capabilities assisting the human operator in controlling the Unmanned Aerial System (UAS) and processing the sensor data, thereby alleviating the need for extensive operator training. This paper presents the HADRON project that seeks to develop and test multiple novel technologies to enable human-friendly control of drone swarms. This project is divided into three main parts. The first part consists of the integration of different technologies for the intuitive control of drones, focusing on novice or inexperienced pilots and operators. The second part focuses on the development of a multi-drone system that will be controlled from a command and control station, in which an expert pilot can supervise the operations of the multiple drones. The third part of the project will focus on reducing the cognitive load on human operators, whether they are novice or expert pilots. For this, we will develop AI tools that will assist drone operators with semi-automated real-time data processing.

Sara Kaszuba, Sandeep Reddy Sabbella, Francesco Leotta et al.

In recent years, an increasing number of Human-Robot Interaction (HRI) approaches have been implemented and evaluated in Virtual Reality (VR), as it allows to speed-up design iterations and makes it safer for the final user to evaluate and master the HRI primitives. However, identifying the most suitable VR experience is not straightforward. In this work, we evaluate how, in a smart agriculture scenario, immersive and non-immersive VR are perceived by users with respect to a speech act understanding task. In particular, we collect opinions and suggestions from the 81 participants involved in both experiments to highlight the strengths and weaknesses of these different experiences.

G. Bertorelle, Andrea Benazzo, S. Mona et al.

A. Dornburg, T. Near

The emergence of a new phylogeny of ray-finned fishes at the turn of the twenty-first century marked a paradigm shift in understanding the evolutionary history of half of living vertebrates. We review how the new ray-finned fish phylogeny radically departs from classical expectations based on morphology. We focus on evolutionary relationships that span the backbone of ray-finned fish phylogeny, from the earliest divergences among teleosts and nonteleosts to the resolution of major lineages of Percomorpha. Throughout, we feature advances gained by the new phylogeny toward a broader understanding of ray-finned fish evolutionary history and the implications for topics that span from the genetics of human health to reconsidering the concept of living fossils. Additionally, we discuss conceptual challenges that involve reconciling taxonomic classification with phylogenetic relationships and propose an alternate higher-level classification for Percomorpha. Our review highlights remaining areas of phylogenetic uncertainty and opportunities for comparative investigations empowered by this new phylogenetic perspective on ray-finned fishes. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 52 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Paul J. CaraDonna, L. Burkle, Benjamin Schwarz et al.

Most studies of plant-animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human-driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant-animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.

Fadrique I. Iglesias Mendizábal, José Luis García Cuesta

The supply and demand of vibrant places are often considered a luxurious goal for cities rather than an essential engine for business and talent attraction. With the ongoing development of Amazon HQ in Arlington and the potential jobs that will originate, the city must be prepared to fulfill the expectations of residents, workers, and investors. Through a qualitative analysis and interviews with relevant practitioners, this paper studies the potential gap between the current creative ecosystem by discussing the supply of cultural goods and services, Arlington’s proposal, and the benefits and risks of achieving the targets, based on lessons from Seattle. To maximize what is expected, it will be imperative to foster a coordinated and creative environment while celebrating the unique essence of Arlington’s communities and the potential risks these changes may bring.

Yoonwon Jung, Sowon Hahn

Loneliness is a distressing personal experience and a growing social issue. Social robots could alleviate the pain of loneliness, particularly for those who lack in-person interaction. This paper investigated how the effect of loneliness on the anthropomorphism of social robots differs by robot appearance, and how it influences purchase intention. Participants viewed a video of one of the three robots (machine-like, animal-like, and human-like) moving and interacting with a human counterpart. Bootstrapped multiple regression results revealed that although the unique effect of animal-likeness on anthropomorphism compared to human-likeness was higher, lonely individuals' tendency to anthropomorphize the animal-like robot was lower than that of the human-like robot. This moderating effect remained significant after covariates were included. Bootstrapped mediation analysis showed that anthropomorphism had both a positive direct effect on purchase intent and a positive indirect effect mediated by likability. Our results suggest that lonely individuals' tendency of anthropomorphizing social robots should not be summarized into one unified inclination. Moreover, by extending the effect of loneliness on anthropomorphism to likability and purchase intent, this current study explored the potential of social robots to be adopted as companions of lonely individuals in their real life. Lastly, we discuss the practical implications of the current study for designing social robots.

Daniëlle Ooms, B. Barati, Miguel Bruns et al.

Anthropocentric perspectives are common in design practice, but also contribute to a damaged planet. Requirements for sustainable processes resulted in novel practices such as biodesign, which investigates how living and regenerative resources can be used instead of artificial and polluting. However, many biodesign practices still seek to benefit humans. In this critique we compare the journey of two designers in the development of a toolkit to setup the bacterial powered light installation Electric Life for exhibition at the Centre Pompidou in Paris. We reflect on the designers’ considerations when designing with microorganisms through the lenses of materiality, temporality, ecology, and agency. Our critique offers a discussion on the revision of a post-human biodesign approach from concern to care when designing-with the living and the questions we confronted throughout.