Collaborative Behaviour Modelling of Virtual Agents using Communication in a Mixed Human-Agent Teamwork

International audience—The coordination is an essential ingredient for the mixed human-agent teamwork. It requires team members to share knowledge to establish common grounding and mutual awareness among them. In this paper, we proposed a collaborative conversational belief-desire-intention (C 2 BDI) behavioural agent architecture that allows to enhance the knowledge sharing using natural language communication between team members. We defined collaborative conversation protocols that provide proactive behaviour to agents for the coordination between team members. Furthermore, to endow the communication capabilities to C 2 BDI agent, we described the information state based approach for the natural language processing of the utterances. We have applied the proposed architecture to a real scenario in a collaborative virtual environment for training. Our solution enables the user to coordinate with other team members

Task-Oriented Conversational Behavior of Agents for Collaboration in Human-Agent Teamwork

International audienceCoordination is an essential ingredient for human-agent teamwork. It requires team members to share knowledge to establish common grounding and mutual awareness among them. This paper proposes a be-havioral architecture C 2 BDI that enhances the knowledge sharing using natural language communication between team members. Collaborative conversation protocols and resource allocation mechanism have been defined that provide proactive behavior to agents for coordination. This architecture has been applied to a real scenario in a collaborative virtual environment for learning. The solution enables users to coordinate with other team members

Detecting Team Conflict From Multiparty Dialogue

The emergence of online collaboration platforms has dramatically changed the dynamics of human teamwork, creating a veritable army of virtual teams composed of workers in different physical locations. The global world requires a tremendous amount of collaborative problem solving, primarily virtual, making it an excellent domain for computer scientists and team cognition researchers who seek to understand the dynamics involved in collaborative tasks to provide a solution that can support effective collaboration. Mining and analyzing data from collaborative dialogues can yield insights into virtual teams\u27 thought processes and help develop virtual agents to support collaboration. Good communication is indubitably the foundation of effective collaboration. Over time teams develop their own communication styles and often exhibit entrainment, a conversational phenomenon in which humans synchronize their linguistic choices. This dissertation presents several technical innovations in the usage of machine learning towards analyzing, monitoring, and predicting collaboration success from multiparty dialogue by successfully handling the problems of resource scarcity and natural distribution shifts. First, we examine the problem of predicting team performance from embeddings learned from multiparty dialogues such that teams with similar conflict scores lie close to one another in vector space. We extract the embeddings from three types of features: 1) dialogue acts 2) sentiment polarity 3) syntactic entrainment. Although all of these features can be used to predict team performance effectively, their utility varies by the teamwork phase. We separate the dialogues of players playing a cooperative game into stages: 1) early (knowledge building), 2) middle (problem-solving), and 3) late (culmination). Unlike syntactic entrainment, both dialogue act and sentiment embeddings effectively classify team performance, even during the initial phase. Second, we address the problem of learning generalizable models of collaboration. Machine learning models often suffer domain shifts; one advantage of encoding the semantic features is their adaptability across multiple domains. We evaluate the generalizability of different embeddings to other goal-oriented teamwork dialogues. Finally, in addition to identifying the features predictive of successful collaboration, we propose multi-feature embedding (MFeEmb) to improve the generalizability of collaborative task success prediction models under natural distribution shifts and resource scarcity. MFeEmb leverages the strengths of semantic, structural, and textual features of the dialogues by incorporating the most meaningful information from dialogue acts (DAs), sentiment polarities, and vocabulary of the dialogues. To further enhance the performance of MFeEmb under a resource-scarce scenario, we employ synthetic data generation and few-shot learning. We use the method proposed by Bailey and Chopra (2018) for few-shot learning from the FsText python library. We replaced the universal embedding with our proposed multi-feature embedding to compare the performance of the two. For data augmentation, we propose using synonym replacement from collaborative dialogue vocabulary instead of synonym replacement from WordNet. The research was conducted on several multiparty dialogue datasets, including ASIST, SwDA, Hate Speech, Diplomacy, Military, SAMSum, AMI, and GitHub. Results show that the proposed multi-feature embedding is an excellent choice for the meta-training stage of the few-shot learning, even if it learns from a small train set of size as small as 62 samples. Also, our proposed data augmentation method showed significant performance improvement. Our research has potential ramifications for the development of conversational agents that facilitate teaming as well as towards the creation of more effective social coding platforms to better support teamwork between software engineers

Engaging College Students in the Transition to Sustainability Through Design-Based Approaches

To achieve social change towards sustainable ways of living, it is essential to promote a culture of sustainability among young people. Universities have a very important role, as sustainable education on college campuses has the potential to achieve long-term results by promoting the development of awareness and skills for youth engagement in order to face complex challenges, now and in the future. This study investigates the application of design-based thinking and participatory design to support a culture of sustainability among youth. It aims to bridge the value-action gap and to develop sustainable competencies. Design-based strategies integrated within educational experiences promote dealing with change and complexity, as well as offering a range of potentialities and interfaces for innovative action in the transition to sustainability. This research used a qualitative multi-method approach which consisted of a literature review, context analysis, ethnographic observation, and application of participatory design in educational settings in Brazil and the United States. This paper summarizes preliminary findings, including guidelines for engagement strategies. These reinforce the importance of understanding values and challenges of youth development, exploring dimensions of sustainability connected to student realities, building contexts for transformation, stimulating empowerment and autonomy, and using mediation to facilitate change processes conducted by young people. These findings also demonstrate that design-based participatory approaches in educational settings offer excellent opportunities for intervention to both engage youth in sustainability and support their positive development

08361 Abstracts Collection -- Programming Multi-Agent Systems

From 31th August to 5th September, the Dagstuhl Seminar 08361 ``Programming Multi-Agent Systems\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Human–agent team dynamics: a review and future research opportunities

Humans teaming with intelligent autonomous agents is becoming indispensable in work environments. However, human–agent teams pose significant challenges, as team dynamics are complex arising from the task and social aspects of human–agent interactions. To improve our understanding of human–agent team dynamics, in this article, we conduct a systematic literature review. Drawing on Mathieu et al.’s (2019) teamwork model developed for all-human teams, we map the landscape of research to human–agent team dynamics, including structural features, compositional features, mediating mechanisms, and the interplay of the above features and mechanisms. We reveal that the development of human–agent team dynamics is still nascent, with a particular focus on information sharing, trust development, agents’ human likeness behaviors, shared cognitions, situation awareness, and function allocation. Gaps remain in many areas of team dynamics, such as team processes, adaptability, shared leadership, and team diversity. We offer various interdisciplinary pathways to advance research on human–agent teams

Prevention and Management of Postpartum Hemorrhage

Postpartum hemorrhage (PPH) remains a major traumatic event that can occur after delivery. All expectant women are considered to be at risk of PPH and its effects. PPH is a preventable condition and primary interventions including active management of the 3rd stage of labor, use of uterotonics, and uterine massage. Analysis of the project site showed that PPH affected approximately 15% of all deliveries that occurred between 2014 and 2015. The overarching aim of the project was to determine how a nursing-focused educational intervention would affect staff nurse knowledge regarding PPH to decrease the incidence rate. The goal of the project was to develop an educational module for obstetric and postpartum nurses about prevention and management of PPH, decrease the PPH incidence rate from 15% to 10%, and evaluate the obstetric and postpartum nurses\u27 attitudes toward the Association of Women\u27s Health, Obstetric and Neonatal Nurses (AWHONN) guideline used to decrease the risk of PPH. Bandura\u27s social learning and self-efficacy theories were used to guide the development and implementation of the educational intervention. A paired t test was used to analyze the differences in the staff nurses\u27 knowledge of PPH before and after the educational intervention. The group\u27s mean score preintervention was 53.65% and 90% postintervention, representing a 36.35% increase in the knowledge scores. The PPH rate decreased from 15% to 0% after implementation of the project. Social change will occur through a better understanding of the physiology of PPH and the positive adaptation of the use of AWHONN guidelines in managing PPH as such, may decrease mortality

An Organisational Development Project to Enhance Interagency Working between the Health Service Executive and Voluntary Agencies

Worldwide there is an increasing incidence and prevalence of disability. To provide a wide range of supports to people with disability, the Health Service Executive (HSE) works in partnership with voluntary agencies to provide specialist health and social care services. The integration of this sector has led to an emphasis on joint working of an array of professionals across organisational boundaries as teams and through teamwork. In reality while the need for joint working is an important component of policy, it is something that is not delivered effectively in practice. This organisational development project aims to enhance interagency working by promoting a culture of collaboration and co-ordination of services so that effective support is provided to service users. For the first time a network analysis was introduced into the department using the HSE Change Model. A participatory approach was utilised to monitor and evaluate the project. Outcomes achieved during the project included targeted communication strategies across HSE and voluntary agencies and the identification of critical success factors for interagency working. Finally, to share the organisational learning, the project has identified and recommended further changes which can be considered across wider services with the shared vision of achieving integrated care