Human–agent collaboration for disaster response

In the aftermath of major disasters, first responders are typically overwhelmed with large numbers of, spatially distributed, search and rescue tasks, each with their own requirements. Moreover, responders have to operate in highly uncertain and dynamic environments where new tasks may appear and hazards may be spreading across the disaster space. Hence, rescue missions may need to be re-planned as new information comes in, tasks are completed, or new hazards are discovered. Finding an optimal allocation of resources to complete all the tasks is a major computational challenge. In this paper, we use decision theoretic techniques to solve the task allocation problem posed by emergency response planning and then deploy our solution as part of an agent-based planning tool in real-world field trials. By so doing, we are able to study the interactional issues that arise when humans are guided by an agent. Specifically, we develop an algorithm, based on a multi-agent Markov decision process representation of the task allocation problem and show that it outperforms standard baseline solutions. We then integrate the algorithm into a planning agent that responds to requests for tasks from participants in a mixed-reality location-based game, called AtomicOrchid, that simulates disaster response settings in the real-world. We then run a number of trials of our planning agent and compare it against a purely human driven system. Our analysis of these trials show that human commanders adapt to the planning agent by taking on a more supervisory role and that, by providing humans with the flexibility of requesting plans from the agent, allows them to perform more tasks more efficiently than using purely human interactions to allocate tasks. We also discuss how such flexibility could lead to poor performance if left unchecked

Intelligent negotiation model for ubiquitous group decision scenarios

Supporting group decision-making in ubiquitous contexts is a complex task that must deal with a large amount of factors to succeed. Here we propose an approach for an intelligent negotiation model to support the group decision-making process specially designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms and agents' modelling in a negotiation model. It uses a social networking logic due to the type of communication employed by the agents and it intends to support the ubiquitous group decision-making process in a similar way to the real process, which simultaneously preserves the amount and quality of intelligence generated in face-to-face meetings. We propose a new look into this problematic by considering and defining strategies to deal with important points such as the type of attributes in the multicriteria problems, agents' reasoning and intelligent dialogues.This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012 and by Project MANTIS - Cyber Physical System Based Proactive Collaborative Maintenance (ECSEL JU Grant nr. 662189).info:eu-repo/semantics/publishedVersio

Trade-offs of Dynamic Control Structure in Human-swarm Systems

Swarm robotics is a study of simple robots that exhibit complex behaviour only by interacting locally with other robots and their environment. The control in swarm robotics is mainly distributed whereas centralised control is widely used in other fields of robotics. Centralised and decentralised control strategies both pose a unique set of benefits and drawbacks for the control of multi-robot systems. While decentralised systems are more scalable and resilient, they are less efficient compared to the centralised systems and they lead to excessive data transmissions to the human operators causing cognitive overload. We examine the trade-offs of each of these approaches in a human-swarm system to perform an environmental monitoring task and propose a flexible hybrid approach, which combines elements of hierarchical and decentralised systems. We find that a flexible hybrid system can outperform a centralised system (in our environmental monitoring task by 19.2%) while reducing the number of messages sent to a human operator (here by 23.1%). We conclude that establishing centralisation for a system is not always optimal for performance and that utilising aspects of centralised and decentralised systems can keep the swarm from hindering its performance.Comment: The International Symposium on Distributed Autonomous Robotic Systems (DARS 2024

A survey of security issue in multi-agent systems

Multi-agent systems have attracted the attention of researchers because of agents' automatic, pro-active, and dynamic problem solving behaviors. Consequently, there has been a rapid development in agent technology which has enabled us to provide or receive useful and convenient services in a variety of areas such as banking, transportation, e-business, and healthcare. In many of these services, it is, however, necessary that security is guaranteed. Unless we guarantee the security services based on agent-based systems, these services will face significant deployment problems. In this paper, we survey existing work related to security in multi-agent systems, especially focused on access control and trust/reputation, and then present our analyses. We also present existing problems and discuss future research challenges. © Springer Science+Business Media B.V 2011

XAI for Group-AI Interaction: Towards Collaborative and Inclusive Explanations

The increasing integration of Machine Learning (ML) into decision-making across various sectors has raised concerns about ethics, legality, explainability, and safety, highlighting the necessity of human oversight. In response, eXplainable AI (XAI) has emerged as a means to enhance transparency by providing insights into ML model decisions and offering humans an understanding of the underlying logic. Despite its potential, existing XAI models often lack practical usability and fail to improve human-AI performance, as they may introduce issues such as overreliance. This underscores the need for further research in Human-Centered XAI to improve the usability of current XAI methods. Notably, much of the current research focuses on one-to-one interactions between the XAI and individual decision-makers, overlooking the dynamics of many-to-one relationships in real-world scenarios where groups of humans collaborate using XAI in collective decision-making. In this late-breaking work, we draw upon current work in Human-Centered XAI research and discuss how XAI design could be transitioned to group-AI interaction. We discuss four potential challenges in the transition of XAI from human-AI interaction to group-AI interaction. This paper contributes to advancing the field of Human-Centered XAI and facilitates the discussion on group-XAI interaction, calling for further research in this area

A genetic approach for long term virtual organization distribution

Electronic versíon of an article published as International Journal on Artificial Intelligent Tools, Volume 20, issue 2, 2011. 10.1142/S0218213011000152. © World Scientific Publishing Company[EN] An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios. © 2011 World Scientific Publishing Company.This work is supported by TIN2008-04446, TIN2009-13839-C03-01, CSD2007-00022 and FPU grant AP2008-00600 of the Spanish government, and PROMETEO 2008/051 of the Generalitat Valenciana.Sánchez Anguix, V.; Valero Cubas, S.; García Fornes, AM. (2011). A genetic approach for long term virtual organization distribution. International Journal on Artificial Intelligence Tools. 20(2):271-295. https://doi.org/10.1142/S0218213011000152S27129520

Designing for planned emergence in multi-agent systems

We present an approach for designing organization-oriented multi-agent systems (MASs) to allow improvisation at run time when agents are not available to exactly match the original organizational design structure. Working with system components from an existing MAS organizational meta-model, OJAzzIC, the approach sets out five stages for the design process. We illustrate the design approach with an incident response scenario implemented in the Blocks World for Teams (BW4T) environment, and show how agents at runtime can improvise- for example they can adopt tasks even if those tasks do not precisely match a predefined role. © Springer International Publishing Switzerland 2015

Sonographic evaluation of the shoulder in asymptomatic elderly subjects with diabetes

<p>Abstract</p> <p>Background</p> <p>The prevalence of rotator cuff tears increases with age and several studies have shown that diabetes is associated with symptomatic shoulder pathologies. Aim of our research was to evaluate the prevalence of shoulder lesions in a population of asymptomatic elderly subjects, normal and with non insulin - dependent diabetes mellitus.</p> <p>Methods</p> <p>The study was performed on 48 subjects with diabetes and 32 controls (mean age: 71.5 ± 4.8 and 70.7 ± 4.5, respectively), who did not complain shoulder pain or dysfunction. An ultrasound examination was performed on both shoulders according to a standard protocol, utilizing multiplanar scans.</p> <p>Results</p> <p>Tendons thickness was greater in diabetics than in controls (Supraspinatus Tendon: 6.2 ± 0.09 mm <it>vs </it>5.2 ± 0.7 mm, p < 0.001; Biceps Tendon: 4 ± 0.8 mm <it>vs </it>3.2 ± 0.4 mm, p < 0.001). Sonographic appearances of degenerative features in the rotator cuff and biceps were more frequently observed in diabetics (Supraspinatus Tendon: 42.7% <it>vs </it>20.3%, p < 0.003; Biceps Tendon: 27% <it>vs </it>7.8%, p < 0.002).</p> <p>Subjects with diabetes exhibited more tears in the Supraspinatus Tendon (Minor tears: 15 (15.8%) <it>vs </it>2 (3.1%), p < 0.03; Major tears: 15 (15.8%) <it>vs </it>5 (7.8%), p = ns), but not in the long head of Biceps. More effusions in subacromial bursa were observed in diabetics (23.9% <it>vs </it>10.9%, p < 0.03) as well as tenosynovitis in biceps tendon (33.3% <it>vs </it>10.9%, p < 0.001).</p> <p>In both groups, pathological findings were prevalent on the dominant side, but no difference related to duration of diabetes was found.</p> <p>Conclusions</p> <p>Our results suggest that age - related rotator cuff tendon degenerative changes are more common in diabetics.</p> <p>Ultrasound is an useful tool for discovering in pre - symptomatic stages the subjects that may undergo shoulder symptomatic pathologies.</p