Optimising Outcomes of Human-Agent Collaboration using Trust Calibration

As collaborative agents are implemented within everyday environments and the workforce, user trust in these agents becomes critical to consider. Trust affects user decision making, rendering it an essential component to consider when designing for successful Human-Agent Collaboration (HAC). The purpose of this work is to investigate the relationship between user trust and decision making with the overall aim of providing a trust calibration methodology to achieve the goals and optimise the outcomes of HAC. Recommender systems are used as a testbed for investigation, offering insight on human collaboration with dyadic decision domains. Four studies are conducted and include in-person, online, and simulation experiments. The first study provides evidence of a relationship between user perception of a collaborative agent and trust. Outcomes of the second study demonstrate that initial trust can be used to predict task outcome during HAC, with Signal Detection Theory (SDT) introduced as a method to interpret user decision making in-task. The third study provides evidence to suggest that the implementation of different features within a single agent's interface influences user perception and trust, subsequently impacting outcomes of HAC. Finally, a computational trust calibration methodology harnessing a Partially Observable Markov Decision Process (POMDP) model and SDT is presented and assessed, providing an improved understanding of the mechanisms governing user trust and its relationship with decision making and collaborative task performance during HAC. The contributions from this work address important gaps within the HAC literature. The implications of the proposed methodology and its application to alternative domains are identified and discussed

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Simulating social relations in multi-agent systems

Open distributed systems are comprised of a large number of heterogeneous nodes with disparate requirements and objectives, a number of which may not conform to the system specification. This thesis argues that activity in such systems can be regulated by using distributed mechanisms inspired by social science theories regarding similarity /kinship, trust, reputation, recommendation and economics. This makes it possible to create scalable and robust agent societies which can adapt to overcome structural impediments and provide inherent defence against malicious and incompetent action, without detriment to system functionality and performance. In particular this thesis describes: • an agent based simulation and animation platform (PreSage), which offers the agent developer and society designer a suite of powerful tools for creating, simulating and visualising agent societies from both a local and global perspective. • a social information dissemination system (SID) based on principles of self organisation which personalises recommendation and directs information dissemination. • a computational socio-cognitive and economic framework (CScEF) which integrates and extends socio-cognitive theories of trust, reputation and recommendation with basic economic theory. • results from two simulation studies investigating the performance of SID and the CScEF. The results show the production of a generic, reusable and scalable platform for developing and animating agent societies, and its contribution to the community as an open source tool. Secondly specific results, regarding the application of SID and CScEF, show that revealing outcomes of using socio-technical mechanisms to condition agent interactions can be demonstrated and identified by using Presage.Open Acces

Evaluation of gaming environments for mixed reality interfaces and human supervisory control in telerobotics

Telerobotics refers to a branch of technology that deals with controlling a robot from a distance. It is commonly used to access difficult environments, reduce operating costs, and to improve comfort and safety. However, difficulties have emerged in telerobotics development. Effective telerobotics requires maximising operator performance and previous research has identified issues which reduce operator performance, such as operator attention being divided across the numerous custom built interfaces and continuous operator involvement in a high workload situation potentially causing exhaustion and subsequent operator error. This thesis evaluates mixed reality and human supervisory control concepts in a gaming engine environment for telerobotics. This concept is proposed in order to improve the effectiveness of current technology in telerobotic interfaces. Four experiments are reported in this thesis which covers virtual gaming environments, mixed reality interfaces, and human supervisory control and aims to advance telerobotics technology. This thesis argues that gaming environments are useful for building telerobotic interfaces and examines the properties required for telerobotics. A useful feature provided by gaming environments is that of overlying video on virtual objects to support mixed reality interfaces. Experiments in this thesis show that mixed reality interfaces provide useful information without distracting the operator from the task. This thesis introduces two response models based on the planning process of human supervisory control: Adaptation and Queue response models. The experimental results show superior user performance under these two response models compared to direct/manual control. In the final experiment a large number of novice users, with a diversity of backgrounds, used a robot arm to push blocks into a hole by using these two response models. Further analyses on evaluating the user performance on the interfaces with two response models were found to be well fitted by a Weibull distribution. Operators preferred the interface with the Queue response model over the interface with the Adaptation response model, and human supervisory control over direct/manual control. It is expected that the increased sophistication of control commands in a production system will usually be greater than those that were tested in this thesis, where limited time was available for automation development. Where that is the case the increases in human productivity using human supervisory control found in this experiment can be expected to be greater. The research conducted here has shown that mixed reality in gaming environments, when combined with human supervisory control, offers a good route for overcoming limitations in current telerobotics technology. Practical applications would benefit by the application of these methods, making it possible for the operator to have the necessary information available in a convenient and non-distracting form, considerably improving productivity

Designing an engaging learning universe for situated interactions in virtual environments

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy (PhD)Studies related to the Virtual Learning approach are conducted almost exclusively in Distance Learning contexts, and focus on the development of frameworks or taxonomies that classify the different ways of teaching and learning. Researchers may be dealing with the topic of interactivity (avatars and immersion are key components), yet they do so they mainly focusing on the interactions that take place within the virtual world. It is the virtual world that consists the primary medium for communication and interplay. However, the lines are hard to be drawn when it comes to examining and taxonomising the impact of interactions on motivation and engagement as a synergy of learners’ concurrent presence. This study covers this gap and sheds light on this lack—or, at least, inadequacy—of literature and research on the interactions that take place both in the physical and the virtual environment at the same time. In addition, it explores the impact of the instructional design decisions on increasing the learners’ incentives for interplay when trying to make sense of the virtual world, thus leading them to attain higher levels of engagement. To evaluate the potential of interactions holistically and not just unilaterally, a series of experiments were conducted in the context of different Hybrid Virtual Learning units, with the participation of Computer Science & Technology students. One of the goals was to examine the learners’ thoughts and preconceptions regarding the use of virtual worlds as an educational tool. Then, during the practical sessions, the focus was placed on monitoring students’ actions and interactions in both the physical and the virtual environment. Consequently, students were asked as a feedback to report their overall opinion on these actions and interactions undertaken. The study draws a new research direction, beyond the idea of immersion and the development of subject-specific educational interventions. The conclusions provide suggestions and guidelines to educators and instructional designers who wish to offer interactive and engaging learning activities to their students, as well as a taxonomy of the different types of interactions that take place in Hybrid Virtual Learning contexts