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

Based on the development of several different HRI scenarios using different robots, we have been establishing the SERA ecosystem. SERA is composed of both a model and tools for integrating an AI agent with a robotic embodiment, in human-robot interaction scenarios. We present the model, and several of the reusable tools that were developed, namely Thalamus, Skene and Nutty Tracks. Finally we exemplify how such tools and model have been used and integrated in five different HRI scenarios using the NAO, Keepon and EMYS robots.

The SERA Ecosystem: Socially Expressive Robotics Architecture for Autonomous Human-Robot Interaction

We contribute a learning from demonstration approach for robots to acquire skills from multi-modal high-dimensional data. Both latent representations and associations of different modalities are proposed to be jointly learned through an adapted variational auto-encoder. The implementation and results are demonstrated in a robotic handwriting scenario, where the visual sensory input and the arm joint writing motion are learned and coupled. We show the latent representations successfully construct a task manifold for the observed sensor modalities. Moreover, the learned associations can be exploited to directly synthesize arm joint handwriting motion from an image input in an end-to-end manner. The advantages of learning associative latent encodings are further highlighted with the examples of inferring upon incomplete input images. A comparison with alternative methods demonstrates the superiority of the present approach in these challenging tasks.

Associate Latent Encodings in Learning from Demonstrations

Serious games are increasingly being regarded as a valuable means to support educative processes and make people aware of important issues. Some of these address social awareness domains with the goal of promoting collective recognition of a given local or global issue as a first step towards its resolution. Even though nowadays widely used, serious games still require further study with regard to their impact. This gap in studies is especially strong in the domain of social awareness. The goal of this work is to address this gap by studying the impact of a highly disseminated serious game that had not yet been evaluated in any way: Stop Disasters!. We studied the impact of the game both in terms of the awareness and player experience it created. As a result we found statistical evidence to a positive impact of the serious game in player's awareness to wildfire prevention measures achieved in an overall positive and valuable game experience. This result provides further evidence to the positive impact of social awareness serious games in transmitting messages regarding social relevant issues in an overall positive and engaging experience.

Disaster Prevention Social Awareness: The Stop Disasters! Case Study

In this paper we consider the issues involved in influencing a user in an interactive storytelling context using results from the social psychology's area of persuasion. We hypothesize that it is possible to use these results in order to influence the user in predictable ways. Several important concepts of persuasion, such as how people make decisions, and how can we influence that process are discussed. We describe a proposal on how to apply these results in an interactive storytelling setting and describe a small study were we have successfully influenced the players of a story in following a specific path by using an expert source manipulation.

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I want to slay that dragon!: influencing choice in interactive storytelling

In this study, we address the level of trust that a human being displays during an interaction with a robot under different circumstances. The influencing factors considered are the facial expressions of a robot during the interactions, as well as the ability of making small talk. To examine these influences, we ran an experiment in which a robot tells a story to a participant, and then asks for help in form of donations. The experiment was implemented in four different scenarios in order to examine the two influencing factors on trust. The results showed the highest level of trust gained when the robot starts with small talk and expresses facial expression in the same direction of storytelling expected emotion.

Ana Paiva

Papers

The SERA Ecosystem: Socially Expressive Robotics Architecture for Autonomous Human-Robot Interaction

Associate Latent Encodings in Learning from Demonstrations

Disaster Prevention Social Awareness: The Stop Disasters! Case Study

I want to slay that dragon!: influencing choice in interactive storytelling

How Facial Expressions and Small Talk May Influence Trust in a Robot