Eldi: an agent based museum robot

[EN]In this paper we will present Eldi, a mobile robot that has been in daily operation at the Elder Museum of Science and Technology at Las Palmas de Gran Canaria since December 1999. This is an ongoing project that was organized in three di erent stages, describing here the one that has been accomplished. The initial phase, termed \The Player", the second stage, actually under development, has been called "The Cicerone" and in a nal phase, termed \The Vagabond", Eldi will be allowed to move erratically across the Museum. This paper will focus on the accomplished rst stage to succinctly describe the physical robot and the environment and demos developed. Finally we will summarize some important lessons learnt.

Nature-based solutions to climate change mitigation and adaptation in urban areas: perspectives on indicators, knowledge gaps, barriers, and opportunities for action

Nature-based solutions promoting green and blue urban areas have significant potential to decrease the vulnerability and enhance the resilience of cities in light of climatic change. They can thereby help to mitigate climate change-induced impacts and serve as proactive adaptation options for municipalities. We explore the various contexts in which nature-based solutions are relevant for climate mitigation and adaptation in urban areas, identify indicators for assessing the effectiveness of nature-based solutions and related knowledge gaps. In addition, we explore existing barriers and potential opportunities for increasing the scale and effectiveness of nature-based solution implementation. The results were derived from an inter- and transdisciplinary workshop with experts from research, municipalities, policy, and society. As an outcome of the workshop discussions and building on existing evidence, we highlight three main needs for future science and policy agendas when dealing with nature-based solutions: (i) produce stronger evidence on nature-based solutions for climate change adaptation and mitigation and raise awareness by increasing implementation; (ii) adapt for governance challenges in implementing nature-based solutions by using reflexive approaches, which implies bringing together new networks of society, nature-based solution ambassadors, and practitioners; (iii) consider socio-environmental justice and social cohesion when implementing nature-based solutions by using integrated governance approaches that take into account an integrative and transdisciplinary participation of diverse actors. Taking these needs into account, nature-based solutions can serve as climate mitigation and adaptation tools that produce additional cobenefits for societal well-being, thereby serving as strong investment options for sustainable urban planning.

A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Enhancing composite Digital Documents Using XML-based Standoff Markup

Document representations can rapidly become unwieldy if they try to encapsulate all possible document properties, ranging from abstract structure to detailed rendering and layout. We present a composite document approach wherein an XMLbased document representation is linked via a shadow tree of bi-directional pointers to a PDF representation of the same document. Using a two-window viewer any material selected in the PDF can be related back to the corresponding material in the XML, and vice versa. In this way the treatment of specialist material such as mathematics, music or chemistry (e.g. via read aloud or play aloud ) can be activated via standard tools working within the XML representation, rather than requiring that application-specific structures be embedded in the PDF itself. The problems of textual recognition and tree pattern matching between the two representations are discussed in detail. Comparisons are drawn between our use of a shadow tree of pointers to map between document representations and the use of a code-replacement shadow tree in technologies such as XBL.

PCA-ANFIS based prediction for water Injection effectiveness cycle in oil fields.

By proposing a numerical based method on PCA-ANFIS(Adaptive Neuro-Fuzzy Inference System), this paper is focusing on solving the problem of uncertain cycle of water injection in the oilfield. As the dimension of original data is reduced by PCA, ANFIS can be applied for training and testing the new data proposed by this paper. The correctness of PCA-ANFIS models are verified by the injection statistics data collected from 116 wells inside an oilfield, the average absolute error of testing is 1.80 months. With comparison by non-PCA based models which average error is 4.33 months largely ahead of PCA-ANFIS based models, it shows that the testing accuracy has been greatly enhanced by our approach. With the conclusion of the above testing, the PCA-ANFIS method is robust in predicting the effectiveness cycle of water injection which helps oilfield developers to design the water injection scheme.

Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling

This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we maintain a case base of information about the most successful heuristics for a range of previous timetabling problems to predict the best heuristic for the new problem in hand using the previous knowledge. Knowledge discovery techniques are used to carry out the training on the CBR system to improve the system performance on the prediction. Initial results presented in this paper are good and we conclude by discussing the con-siderable promise for future work in this area.

Case-based reasoning in course timetabling: an attribute graph approach

An earlier Case-based Reasoning (CBR) approach developed by the authors for educational course timetabling problems employed structured cases to represent the complex relationships between courses. Previous solved cases represented by attribute graphs were organized hierarchically into a decision tree. The retrieval searches for graph isomorphism among these attribute graphs. In this paper, the approach is further developed to solve a wider range of problems. We also attempt to retrieve those graphs that have common similar structures but also have some differences. Costs that are assigned to these differences have an input upon the similarity measure. A large number of experiments are performed consisting of different randomly produced timetabling problems and the results presented here strongly indicate that a CBR approach could provide a significant step forward in the development of automated system to solve difficult timetabling problems. They show that using relatively little effort, we can retrieve these structurally similar cases to provide high quality timetables for new timetabling problems.

Airframe sound simulation based on staggered-grid higher order schemes and finite volume CFD methods

Abstract not available

Rule-based and Resource-bounded: A New Look at Epistemic Logic

Syntactic logics do not suffer from the problems of logical omniscience but are often thought to lack interesting properties relating to epistemic notions. By focusing on the case of rule-based agents, I develop a framework for modelling resource-bounded agents and show that the resulting models have a number of interesting properties.

Enhancing the usability of numerical models with case-based reasoning

Abstract not available

Definition of Model-based diagnosis problems with Altarica

International audience