ENLITEN - A dataset and its associated analysis code for the paper entitled "Designing sensor sets for capturing energy events in buildings"

This dataset contains data and software source code supporting the paper entitled 'Design sensor sets for capturing energy events in buildings'. It contains raw data from sets of domestic sensors measuring temperature, humidity, levels of sound, light and carbon dioxide, and power consumption. It also contains analysis code and visualisation code written for R and Python.Details of the methodology may be found in the associated manuscript. All data was collected approximately from Aug 2013 to Oct 2013. An instruction for the participants attached here (instruction.pdf) shows the way how the data was collected in the individual homes.The data files are in comma-separated (.csv) and tab-separated (.txt) plain text formats. The .py source code files target Python v2.x and use only standard libraries. The R source code files use the following libraries available from CRAN: entropy, ggplot2, plyr, randomForest, reshape2, scales. Some pre-compiled visualisations are included as PDF files.The zip file contains a set of top level data and source code files, a further files arranged into 5 directories. The 'analysis_datasets' directory contains the main dataset used for the paper. It also includes the machine learning algorithm code (random forest in this case), its associated data and a document showing a selected feature set. The 'gt', 'sd', and 'tf' directories contain raw data collected by one of participants. The 'set_viz' directory contains visualisation code as well as knapsack (cost–benefit) optimisation code for the selection of minimal sensor sets subject to the budget

Dataset for "Norm Awareness for Virtual Characters Behaviour: A Socio-Cognitive Approach"

This dataset comprises video clips and source code accompanying the thesis "Norm Awareness for Virtual Characters Behaviour: A Socio-Cognitive Approach". The thesis proposes a new computational model, Distributed Norm-Aware Agent Architecture (DNA3), for increasing the verisimilitude of the behaviour of virtual characters (in a simulated world such as SecondLife) by incorporating reasoning about social norms. The model integrates a normative framework performing the social reasoning, a cognitive agent carrying out run-time norm-aware deliberation, and a virtual character in charge of perception and realisation of actions. This dataset includes the Java and C# source code for the Bath-Sensor-Framework (BSF) middleware, and Java code implementing the N-Jason virtual agent, as described in chapter 3 of the thesis. Video clips showing this code in operation, referenced in chapters 6 and 7 of the thesis, are also included.The source code bundles contain software compiled for a Windows 7 platform. The videos are in Advanced Systems Format (Windows Media Video).The videos and source code are described in detail in the thesis

Decoupling cognitive agents and virtual environments

Abstract. The development of and accessibility to rich virtual envi-ronments, both for recreation and training activities leads to the use of intelligent agents to control avatars (and other entities) in these en-vironments. There is a fundamental tension in such systems between tight integration, for performance and low coupling, for generality, flex-ibility and extensibility. This paper addresses the engineering issues in connecting agent platforms and other software entities with virtual en-vironments, driven by the following informal requirements: (i) accessi-bility: we would like (easily) to be able to connect any (legacy) software component with the virtual environment (ii) performance: we want the benefits of decoupling, but not at a high price in performance (iii) dis-tribution: we would like to be able to locate functionality where needed, when necessary, but also be location agnostic otherwise (iv) scalability: we would like to support large-scale and geographically dispersed virtual environments. We start from the position that the basic currency unit of such systems can be events. We describe the Bath Sensor Framework, which is a middleware that attempts to satisfy the above goals and to provide a low-latency linking mechanism between event producers and event consumers, while minimising the effect of coupling of components. We illustrate the framework in two complementary case studies using the Jason agent platform, Second Life and AGAVE (a 3D VE for vehi-cles). Through these examples, we are able to carry out a preliminary evaluation of the approach against the factors above, against alternative systems and demonstrate effective distributed execution.

Towards polite virtual agents using social reasoning techniques

The use of polite agents is a new approach in order to improve efficiency and naturalism in navigation for player characters in crowded virtual worlds. This paper aims to model the politeness of virtual humans using logic‐based approaches, subject to theory of politeness decomposed of conventional and interpersonal politeness. To do so, we propose a high‐level agent architecture combined with normative framework to model and reason about ‘polite’ behaviours in social situations. With this architecture, we demonstrate (i) specifying polite behaviours as a form of social norms; (ii) generating polite behaviours using social reasoning technique; (iii) deliberation with such norms in belief–desire–intention agents; and (iv) realising physical actions based on the decision. Implementation for social reasoning is achieved by InstAL, based on the semantics of answer set programming. Using experiments with simple collision avoidance model, we show the effectiveness of polite behaviour in navigation designed by such architecture, as well as the adequacy of this architecture for modelling theory of politeness in all circumstances