Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Data Mining Practical Machine Learning Tools and Techniques

The power of feedback.

Emotion and Adaptation

Intelligent agents and robots will become part of our daily lives. As they do, they will not only carry out specific tasks in the environment but also to partner with us socially and collaboratively. Groups of social robots may interact with groups of humans performing joint activities. Yet, research related to hybrid groups of humans and robots is still limited. What does it mean to be part of a hybrid group? Can social robots team up with humans? How do humans respond to social robots as partners? Do humans trust them? To research these questions we need a deep understanding of how robots can interact socially in group. That involves being able to identify and characterize group members, evaluate the dependencies between the behaviors of different members, understand and consider different roles, and infer the dynamics of group interactions in a group, led by a common past to build an anticipated future. In this talk I will discuss how to engineer social robots that act autonomously as members of a group collaborating with both humans and other robots. Different aspects need to be considered: what type of interaction mechanisms need to be built in the social robots to act in groups; how to build the capabilities that makes them able to perceive, identify and understand the human members of a group; how to model and retain information about past shared experiences of a group; how to model and adapt to the emotions of a group; and how to allow for a robot to respond to the dynamics of social interactions [Correia et al. 2019]. I will start by providing an overview of recent research in social human-robot teams, and present different scenarios to illustrate the work. I will explore the application in the context of education [Alves-Oliveira et al. 2019] and entertainment [Correia et al. 2016] [Oliveira et al. 2018], describing how autonomous robotic partners may take into account different preferences and characteristics by the humans, and act in a social manner respecting the group's characteristics [Correia et al. 2018].

Humans and robots together: engineering sociality and collaboration

This workshop aims to exchange experiences with issues surrounding Child-Robot Interaction. More specifically, the main aims are to discuss how social bonding between children and robots can be evaluated, how robots can be used to aid children in their learning process, but also what ethical issues arise when children learn from and bond with a robot. Another aim is to discuss how teachers’ and caretakers’ perspectives on children’s use of robots should be taken into account when designing and evaluating robots for children.

/pdf/child-robot-interaction-social-bonding-learning-and-ethics-40m5svryoa.pdf

Child-Robot Interaction: Social Bonding, Learning and Ethics

It is important to properly test developed software because this may contribute to fewer bugs going unreported in deployed software. Often, little attention is spent on the topic of software testing in curricula, yielding graduate students without adequate preparation to deal with the quality standards required by the industry. This problem could be tackled by introducing bite-sized software testing education capsules that allow teachers to introduce software testing to their students in a less time-consuming manner and with a hands-on component that will facilitate learning. In order to design appropriate software testing educational tools, it is necessary to consider both the software testing needs of the industry and the cognitive models of students. This work-in-progress paper proposes an experimental design to gain an understanding of the cognitive strategies used by students during test case design based on real-life cases. Ultimately, the results of the experiment will be used to develop educational support for teaching software testing.

Collecting cognitive strategies applied by students during test case design

In order to deceive, agents need Theory of Mind capabilities (ToM), that is, the capability to model the others, and reason about the consequences of their actions and their implications in them. In this paper we provide a model for deceptive agents that use a theory of mind with N levels. We then present a case study that was used to compare deceptive agents with one level and with two levels of ToM.

/pdf/lie-to-me-virtual-agents-that-lie-extended-abstract-2o3l3kciw6.pdf

Lie to Me: Virtual Agents that Lie (Extended Abstract)

Can social power endow social robots with the capacity to persuade? This paper represents our recent endeavor to design persuasive social robots. We have designed and run three different user studies to investigate the effectiveness of different bases of social power (inspired by French and Raven's theory) on peoples' compliance to the requests of social robots. The results show that robotic persuaders that exert social power (specifically from expert, reward, and coercion bases) demonstrate increased ability to influence humans. The first study provides a positive answer and shows that under the same circumstances, people with different personalities prefer robots using a specific social power base. In addition, social rewards can be useful in persuading individuals. The second study suggests that by employing social power, social robots are capable of persuading people objectively to select a less desirable choice among others. Finally, the third study shows that the effect of power on persuasion does not decay over time and might strengthen under specific circumstances. Moreover, exerting stronger social power does not necessarily lead to higher persuasion. Overall, we argue that the results of these studies are relevant for designing human--robot-interaction scenarios especially the ones aiming at behavioral change.

Ana Paiva

Papers

Humans and robots together: engineering sociality and collaboration

Child-Robot Interaction: Social Bonding, Learning and Ethics

Collecting cognitive strategies applied by students during test case design

Lie to Me: Virtual Agents that Lie (Extended Abstract)

Building Persuasive Robots with Social Power Strategies