This paper introduces the concept and use of an Interaction History Architecture for use on a mobile domestic robot and analyses the limitations of this configuration. The interaction history architecture builds upon Shannon information theory and has been previously used in a humanoid robot to learn basic children’s games. Previous work has shown that experience spaces can be highly flexible when used for learning. In this paper we outline and experiment designed to test the abilities of the architecture and how it can be used with classic clicker style training to teach domestic robots simple tasks. It then presents results from an experiment exploring these capabilities as well as the limitation found therein.

The two applications under development The EMOTE project (http://www.emote-project.eu/) is are a Treasure Hunt exercise designed to teach mapreading working towards the development of an empathic robot tutor skills, and a multi-player game Enercities-2 designed to be used with the 11-14 group and a multi-touch table to teach aspects of sustainable urban development.

We present an implemented approach to transform natural language sentences into SPARQL, using background knowledge from ontologies and lexicons. Therefore, eligible technologies and data storage possibilities are analyzed and evaluated. The contributions of this paper are twofold. Firstly, we describe the motivation and current needs for a natural language access to industry data. We describe several scenarios where the proposed solution is required. Resulting in an architectural approach based on automatic SPARQL query construction for effective natural language queries. Secondly, we analyze the performance of RDBMS, RDF and Triple Stores for the knowledge representation. The proposed approach will be evaluated on the basis of a query catalog by means of query efficiency, accuracy, and data storage performance. The results show, that natural language access to industry data using ontologies and lexicons, is a simple but effective approach to improve the diagnosis process and the data search for a broad range of users. Furthermore, virtual RDF graphs do support the DB-driven knowledge graph representation process, but do not perform efficient under industry conditions in terms of performance and scalability.

Eye contact is a crucial behaviour in human communication and therefore an essencial feature in human-robot interaction. A study regarding the development of an eye behaviour model for a robotic tutor in a task-oriented environment is presented, along with a description of how our proposed model is being used to implement an autonomous robot in the EMOTE project.

Wikipedia provides an enormous amount of background knowledge to reason about the semantic relatedness between two entities. We propose Wikipedia-based Distributional Semantics for Entity Relatedness (DiSER), which represents the semantics of an entity by its distribution in the high dimensional concept space derived from Wikipedia. DiSER measures the semantic relatedness between two entities by quantifying the distance between the corresponding high-dimensional vectors. DiSER builds the model by taking the annotated entities only, therefore it improves over existing approaches, which do not distinguish between an entity and its surface form. We evaluate the approach on a benchmark that contains the relative entity relatedness scores for 420 entity pairs. Our approach improves the accuracy by 12% on state of the art methods for computing entity relatedness. We also show an evaluation of DiSER in the Entity Disambiguation task on a dataset of 50 sentences with highly ambiguous entity mentions. It shows an improvement of 10% in precision over the best performing methods. In order to provide the resource that can be used to find out all the related entities for a given entity, a graph is constructed, where the nodes represent Wikipedia entities and the relatedness scores are reflected by the edges. Wikipedia contains more than 4.1 millions entities, which required efficient computation of the relatedness scores between the corresponding 17 trillions of entity-pairs.

We present a system that produces emotionally rich poetry inspired by personalized and empathic interpretation of text, particularly Internet blogs. Our implemented system is based on the blackboard architecture, and generates poetry from a theme that it considers the most inspiring. It also incorporates a model of emotions with an individual optimism rate that defines an affective state. The poems produced by the system contain emotional expressions that describe these feelings. We explain how the system re-conceptualizes the text by the empathic interpretation of its content. We also present how the blackboard architecture may support divergent problem solving in the field of computational creativity.We describe the system architecture and the generation algorithm followed by some illustrative results. Finally, we mention possible continuation of this work by incorporating other language generating systems as well as human experts in the blackboard architecture.

In this paper, we highlight the usage of AI in software development process for Robotic systems, in general and HRI systems, in particular. The software as well as the software development methodology and associated tools are knowledge-based systems. The key challenge is to represent domain knowledge that enables the process and model evolution to built complex software intensive HRI systems.

Hershman and Lieb, 1988) However, Ward et al. (Ward et al. 1999) have convincingly argued an alternative While it is relatively easy to recognize a creative deed, it is view that "[…] creative capacity is an essential property of extremely difficult (as demonstrated by creativity research normative human cognition and […] the relevant processes so far) to define what creativity is. The past (almost 70) are open to investigation". In support of this view, I would years of research definitely shed some light on different like to mention the research of Picciuto and Carruthers aspects of creativity, but we are still far from a commonly (Picciuto and Carruthers, 2012) that put forward the agreed upon definition of it and consequently a deep hypothesis that pretense play might be the key factor in understanding of this phenomenon. For an extended understanding creativity. Pretense play occurs typically in historical overview of creativity research, please refer to children at about the age of 18 months and is universal (Stojanov, 2013). Here are four branches which can be across all human cultures.

We are interested in the manipulation skills required by future service robots performing everyday tasks such as preparing food and cleaning in a typical home environment. Such robots must have a robust set of skills that can be applied in the unpredictable and varying circumstances that arise in everyday life.To succeed in such a setting, a service robot must have a strong ability to transfer old skills to new varied settings. We are inspired by the strong transfer ability demonstrated by infants and toddlers on simple manipulation activities, and we are motivated to try and replicate these abilities in an artificial system.We treat this as a problem of making analogies, and describe a theoretical framework which could account for it. We sketch the ideas of a computational model for implementing the required analogical reasoning.

A robotic system for extracting and imitating gestures in Human-Robot Interaction is presented. Using the iCub robot and RGB-D sensors, contextually important time points are used to mark and ground the gestures. The benefits of this approach are that the gesture imitation appears both visually and behaviourally realistic, the cognitive and computation loads are reduced and no predefined mappings or speech-based annotations are needed. The system is adaptive to individual users and contributes to the creation and maintenance of a smoother interaction.