Designing and Testing an Experimental Framework of Affective Intelligent Agents in Healthcare Training Simulations

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyThe purpose of this study is to investigate how emotionally enabled virtual agents (VAs) in healthcare provision training simulations allow for a more effective level of understanding on how an emotionally enhanced scenario can affect different aspects of learning. This is achieved by developing virtual agents that respond to the user’s emotions and personality. The developed system also provides visual and auditory representations of the virtual agents’ state of mind. To enable the fulfilment of this purpose an experimental framework for incorporating emotional enhancements (concentrating on negative emotions such as stress, fear, and anxiety) into virtual agents in virtual training applications for healthcare provision is designed and implemented. The framework for incorporating emotional enhancements is designed based on previous research, on psychological theories (with input by experienced psychologists) and from input of experts in the area of healthcare provision. For testing the framework and answering the research question of this thesis the researcher conducted nine case studies. The participants were nursing students in the area of healthcare provision, and more specifically in the area of mental health, specialising in caring for patients with dementia. The results of the study showed that the framework and its implementation succeeded in providing a realistic learning experience, stimulated a better set of responses from the user, improved their level of understanding on how an emotionally enhanced scenario can affect the learning experience and helped them become more empathetic towards the person they cared for

Carbon Capture; Transport and Storage in Europe: A Problematic Energy Bridge to Nowhere?

This paper is a follow up of the SECURE-project, financed by the European Commission to study “Security of Energy Considering its Uncertainties, Risks and Economic Implications”. It addresses the perspectives of, and the obstacles to a CCTS-roll out, as stipulated in some of the scenarios. Our main hypothesis is that given the substantial technical and institutional uncertainties, the lack of a clear political commitment, and the available alternatives of low-carbon technologies, CCTS is unlikely to play an important role in the future energy mix; it is even less likely to be an “energy bridge” into a low-carbon energy futureCarbon Capture, Transport, Storage

Conversational Agent: Developing a Model for Intelligent Agents with Transient Emotional States

The inclusion of human characteristics (i.e., emotions, personality) within an intelligent agent can often increase the effectiveness of information delivery and retrieval. Chat-bots offer a plethora of benefits within an eclectic range of disciplines (e.g., education, medicine, clinical and mental health). Hence, chatbots offer an effective way to observe, assess, and evaluate human communication patterns. Current research aims to develop a computational model for conversational agents with an emotional component to be applied to the army leadership training program that will allow for the examination of interpersonal skills in future research. Overall, the current research explores the application of the deep learning algorithm to the development of a generalized framework that will be based upon modeling empathetic conversation between an intelligent conversational agent (chatbot) and a human user in order to allow for higher level observation of interpersonal communication skills. Preliminary results demonstrate the promising potential of the seq2seq technique (e.g., through the use of Dialog Flow Chatbot platform) when applied to emotion-oriented conversational tasks. Both the classification and generative conversational modeling tasks demonstrate the promising potential of the current research for representing human to agent dialogue. However, this implementation may be extended by utilizing, a larger more high-quality dataset

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Computational models of social and emotional turn-taking for embodied conversational agents: a review

The emotional involvement of participants in a conversation not only shows in the words they speak and in the way they speak and gesture but also in their turn-taking behavior. This paper reviews research into computational models of embodied conversational agents. We focus on models for turn-taking management and (social) emotions. We are particularly interested in how in these models emotions of the agent itself and those of the others in uence the agent's turn-taking behavior and vice versa how turn-taking behavior of the partner is perceived by the agent itself. The system of turn-taking rules presented by Sacks, Schegloff and Jefferson (1974) is often a starting point for computational turn-taking models of conversational agents. But emotions have their own rules besides the "one-at-a-time" paradigm of the SSJ system. It turns out that almost without exception computational models of turn-taking behavior that allow "continuous interaction" and "natural turntaking" do not model the underlying psychological, affective, attentional and cognitive processes. They are restricted to rules in terms of a number of supercially observable cues. On the other hand computational models for virtual humans that are based on a functional theory of social emotion do not contain explicit rules on how social emotions affect turn-taking behavior or how the emotional state of the agent is affected by turn-taking behavior of its interlocutors. We conclude with some preliminary ideas on what an architecture for emotional turn-taking should look like and we discuss the challenges in building believable emotional turn-taking agents

Digital literacy in six micro-bites

"'Digital Literacy in Six Micro-Bites' is a series of six essays disseminated as part of “L’arca in the loop,” ARCA’s monthly newsletter, from December 2019 to May 2020. The series is also published in posts on ARCA’s website. Each of these six posts focuses on a key concept in digital culture, providing definitions and outlining technical considerations in plain language, along with insights on how digital technologies might support artist-run centre personnel in their day-to-day activities." -- page 3