Action, Abduction And Plan Recognition

none1In the forthcoming distributed autonomous robotic systems it will be useful for a robot to recognize other robots' goals and plans from visual information. Till now, much emphasis has been given to plan inference. This paper is about goal recognition: having recognised a plan (may be after the entire plan has been performed), try to recognise which can be the actor's reasons for the plan to be performed. If the actor's planner possesses sufficient inferential capabilities, then goal recognition is not a trivial question. This paper shows that, under simple hypotheses on the nature of the planner that guides an actor's behaviour, an observer can recognize the actor's goal by means of a simple clause-based abductive reasoning. Furthermore, the paper shows how goal recognition can be regarded as a useful step in plan inference. This results refer to the prototypical state-based STRIPS plannerAldo Franco DragoniDragoni, Aldo Franc

Teaching iCub to recognize objects using deep convolutional neural networks

Providing robots with accurate and robust visual recognition capabilities in the real-world today is a challenge which prevents the use of autonomous agents for concrete applications. Indeed, the majority of tasks, as manipulation and interaction with other agents, critically depends on the ability to visually recognize the entities involved in a scene. At the same time, computer vision systems based on deep Convolutional Neural Networks (CNNs) are marking a breakthrough in fields as largescale image classification and retrieval. In this work we investigate how latest results on deep learning can advance the visual recognition capabilities of a robotic platform (the iCub humanoid robot) in a real-world scenario. We benchmark the performance of the resulting system on a new dataset of images depicting 28 objects, named iCubWorld28, that we plan on releasing. As in the spirit of the iCubWorld dataset series, this has been collected in a framework reflecting the typical iCub\u2019s daily visual experience. Moreover, in this release we provide four different acquisition sessions, to test incremental learning capabilities over multiple days. Our study addresses the question: how many objects can the iCub recognize today

Progress and Prospects toward a Space-based Gravitational-Wave Observatory

Over the last few years there has been much activity in the effort to produce a space-based gravitational-wave observatory. These efforts have enriched the understanding of the scientific capabilities of such an observatory leading to broad recognition of its value as an astronomical instrument. At the same time, rapidly developing events in the US and Europe have lead to a more complicated outlook than the baseline Laser Interferometer Space Antenna (LISA) project plan of a few years ago. I will discuss recent progress and developments resulting from the European eLISA study and the SGO study in the US and prospects looking forward

Visualizations for an Explainable Planning Agent

In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making. Imposing transparency and explainability requirements on such agents is especially important in order to establish trust and common ground with the end-to-end automated planning system. Visualizing the agent's internal decision-making processes is a crucial step towards achieving this. This may include externalizing the "brain" of the agent -- starting from its sensory inputs, to progressively higher order decisions made by it in order to drive its planning components. We also show how the planner can bootstrap on the latest techniques in explainable planning to cast plan visualization as a plan explanation problem, and thus provide concise model-based visualization of its plans. We demonstrate these functionalities in the context of the automated planning components of a smart assistant in an instrumented meeting space.Comment: PREVIOUSLY Mr. Jones -- Towards a Proactive Smart Room Orchestrator (appeared in AAAI 2017 Fall Symposium on Human-Agent Groups

Justice and conservation: The need to incorporate recognition

In light of the Aichi target to manage protected areas equitably by 2020, we ask how the conservation sector should define justice. We focus in particular on ‘recognition’, because it is the least well understood aspect of environmental justice, and yet highly relevant to conservation because of its concern with respect for local knowledge and cultures. In order to explore the meaning of recognition in the conservation context, we take four main steps. First, we identify four components of recognition to serve as our analytical framework: subjects of justice, the harms that constitute injustice, the mechanisms that produce injustices, and the responses to alleviate these. Secondly, we apply this framework to explore four traditions of thinking about recognition: Hegelian inter-subjectivity, critical theory, southern decolonial theory, and the capabilities approach. Thirdly, we provide three case studies of conservation conflicts highlighting how different theoretical perspectives are illustrated in the claims and practices of real world conservation struggles. Fourthly, we finish the paper by drawing out some key differences between traditions of thinking, but also important areas of convergence. The convergences provide a basis for concluding that conservation should look beyond a distributive model of justice to incorporate concerns for social recognition, including careful attention to ways to pursue equality of status for local conservation stakeholders. This will require reflection on working practices and looking at forms of intercultural engagement that, for example, respect alternative ways of relating to nature and biodiversity

Designing a competency based program to facilitate the progression of experienced engineering technologists to professional engineer status

This paper describes the pedagogical principles that underpin the design of the Master of Engineering Practice, a distance education program offered by the University of Southern Queensland. This innovative program enables experienced engineering technologists to use their workplace learning to assemble portfolios that demonstrate their achievement of many of the competencies defined for a graduate of the program. Students are required to be self-directed learners and to use reflective practices to assess their own learning. Following a self-assessment process undertaken in the first course in the program, each student prepares a Pathway to Graduation Plan which they then follow through to graduation. Graduates of the program are able to become registered as Chartered Professional Engineers