A Multi-Agent Approach for Provisioning of e-Services in u-Commerce Environments

Purpose: Taking into account the importance of e-commerce and the current applications of AI techniques in this area, this research aims to adequate the design of a multi-agent system for the provisioning of e-services in u-commerce environments. This proposal is centred on the methods of evaluation in a u-e-commerce environment. Design/methodology/approach: The multi-agent systems (MAS) approach is based on an MAS model developed for AmI that has been redesigned to support u-commerce. The use of a recommendation system, previously developed by the research group, is suggested for this MAS. The methodological proposal centres on the evaluation of this type of system. Findings: The evaluation of this type of system is the principal problem of current research. Therefore, this is the main contribution of the paper. Research limitations/implications: The different evaluation methods that are proposed, whether qualitative or quantitative, offer the possibility of measuring the added value that the context can give to the use of e-services in different domains of application. Qualitative evaluation should consider the customer as a central piece in the system. In addition, quantitative methods should objectively evaluate the contribution of context to the application. Practical implications: At present, there is no single method for evaluating the benefits of different u-commerce systems, so a new method needs to be found based on these techniques. Originality/value: The research proposes an MAS designed for u-commerce domains, analyzes the capacity of trust management techniques in this environment, and proposes several evaluation methods to show the benefits of context information in the use of e-services. Several real developments are described to show the different applications of MAS in u-commerce and how evaluation is carried out.This work has been partially supported by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM CONTEXT and DPS2008-07029-C02-02.Publicad

Intelligent techniques for context-aware systems

Nowadays, with advances in communication technologies, researches are focused in the fields of designing new devices with increasing capabilities, implanting software frameworks or middleware to make these devices interoperable. Building better human interfaces is a challenging task and the adoption of Artificial Intelligence (AI) techniques to the process help associating semantic meaning to devices which makes possible the gesture recognition and voice recognition. This thesis is mainly concerned with the open problem in context-aware systems: the evaluation of these systems in Ambient Intelligence (AmI) environments. With regard to this issue, we argue that due to highly dynamic properties of the AmI environments, it should exist a methodology for evaluating these systems taking into account the type of scenarios. However in order to support with a solid ground for that discussion, some elements are to be discussed as well. In particular, we: • use a commercial platform that allows us to design and manage the contextual information of context- aware systems by means of a context manager included in the architecture; • analyze the formal representation of this contextual information by means of a knowledge based system (KBS); • discuss the possible methodologies to be used for modelling knowledge in KBS and our approach; • give reasons why intelligent agents is a valid technique to be applied to systems in AmI environments; • propose a generic multi-agent system (MAS) architecture that can be applied to a large class of envisaged AmI applications; • propose a multimodal user interface and its integration with our MAS; • propose an evaluation methodology for context-aware systems in AmI scenarios. The formulation of the above mentioned elements became necessary as this thesis was developed. The lack of an evaluation methodology for context-aware systems in AmI environments, where so many issues to be covered, took us to the main objective of this thesis. In this regard: • we provide an updated and exhaustive state-of-the-art of this matter; • examine the properties and characteristics of AmI scenarios; • put forward an evaluation methodology and experimentally test our methodology in AmI scenarios. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------La Inteligencia Ambiental y los entornos inteligentes hacen hincapié en una mayor facilidad de uso, soporte de servicios más eficientes, el apoderamiento de los usuarios, y el apoyo a las interacciones humanas. En esta visión, las personas estarán rodeadas de interfaces inteligentes e intuitivas incrustados en objetos cotidianos que nos rodean y los sistemas desarrollados para este ambiente deberán reconocer y responder a la presencia de individuos de una manera invisible y transparente a ellos. Esta tesis se centra principalmente en el problema abierto en los sistemas sensibles al contexto: la evaluación de estos sistemas en los entornos de Inteligencia Ambiental. Con respecto a este tema, se argumenta que debido a las propiedades altamente dinámica de los entornos de inteligencia ambiental, debería existir una metodología para la evaluación de estos sistemas, teniendo en cuenta el tipo de escenarios. Sin embargo, con el fin de apoyar con una base sólida para la discusión, algunos elementos deben ser discutidos también. En particular, nosotros: • Usamos una plataforma comercial que nos permite diseñar y gestionar la información contextual de los sistemas sensibles al contexto a través de un gestor de contexto incluido en la arquitectura; • Analizamos la representación formal de esta información contextual a través de un sistema basado en el conocimiento (SBC); • Discutimos las posibles metodologías que se utilizarán para el modelado del conocimiento en SBC y nuestra aproximación y propuesta; • Discutimos las razones del por qué los agentes inteligentes son una técnica válida para ser aplicada a los sistemas en entornos inteligencia ambiental; • Proponemos un sistema multi-agente (SMA), con una arquitectura genérica que se puede aplicar a una gran clase de aplicaciones de inteligencia ambiental; • Proponemos una interfaz de usuario multimodales y su integración con nuestro SMA; • Proponemos una metodología de evaluación de los sistemas sensibles al contexto en los escenarios de inteligencia ambiental. La formulación de los elementos antes mencionados se hizo necesaria en la medida que esta tesis se ha desarrollado. La falta de una metodología de evaluación de los sistemas sensibles al contexto en entornos de inteligencia ambiental, donde existen tantos temas a tratar, nos llevó al objetivo principal de esta tesis. En este sentido, en esta tesis: • Proporcionamos un estado del arte actualizado y exhaustivo de este asunto; • Examinamos las propiedades y características de los escenarios de inteligencia ambiental; • Proponemos una metodología de evaluación para este tipo de sistemas y experimentalmente probamos nuestra metodología en diversos escenarios de inteligencia ambiental

Multi-agent simulations for emergency situations in an airport scenario

This paper presents a multi-agent framework using Net- Logo to simulate humanand collective behaviors during emergency evacuations. Emergency situationappears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways tofollow in an emergency situation. A critical and public scenario is an airportwhere there is an everyday transit of thousands of people. In this scenario theimportance is related with incidents statistics regarding overcrowding andcrushing in public buildings. Simulation has the objective of evaluating buildinglayouts considering several possible configurations. Agents could be based onreactive behavior like avoid danger or follow other agent, or in deliberative behaviorbased on BDI model. This tool provides decision support in a real emergencyscenario like an airport, analyzing alternative solutions to the evacuationprocess.Publicad

Multiagent Simulations for Emergency Situations in Buildings

Proceedings of: 13th Ibero-American Conference on Artificial Intelligence (IBERAMIA 2012): Workshop on Intelligent systems for context-based information fusion (ISCIF). Cartagena de Indias, Colombia. 13-16 November 2012.This paper presents a multi-agent framework using NetLogo to simulate human and collective behaviors during emergency evacuations. Emergency situation appears when an unexpected event occurs. In indoor emergency situation, evacuation plans de ned by facility manager explain procedure and safety ways to follow in an emergency situation. Critical and public scenarios are buildings where there is an everyday transit of thousands of people. In this case the importance is related with incidents statistics regarding overcrowding and crushing in public buildings. Simulation has the objective of evaluating building layouts considering several possible con gurations. Agents could be based on reactive behavior like avoid danger or follow other agent, or in deliberative behavior based on BDI model. This tool provides decision support in a real emergency scenario like an public buildings, analyzing alternative solutions to the evacuation process.Publicad

Agent-based simulation with NetLogo to evaluate ambient intelligence scenarios

In This Paper An Agent-Based Simulation Is Developed In Order To Evaluate An Ambient Intelligence Scenario Based On Agents. Many Ami Applications Are Implemented Through Agents But They Are Not Compared With Any Other Existing Alternative In Order To Evaluate The Relative Benefits Of Using Them. The Proposed Simulation Environment Analyses Such Benefits Using Two Evaluation Criteria: First, Measuring Agent Satisfaction Of Different Types Of Desires Along The Execution. Second, Measuring Time Savings Obtained Through A Correct Use Of Context Information. In This Paper An Existing Agent Architecture, An Ontology And A 12-Steps Protocol To Provide Ami Services In Airports, Is Evaluated Using The Netlogo Simulation Environment. In Our Netlogo Model We Are Considering Scalability Issues Of This Application Domain But Using Fipa And Bdi Extensions To Be Coherent With Our Previous Works And Our Previous Jade Implementation Of Them. The Netlogo Model Simulates An Airport With Agent &#39 Passengers&#39 Passing Through Several Zones Located In A Specific Order In A Map: Passport Controls, Check-In Counters Of Airline Companies, Boarding Gates, Different Types Of Shopping. Although The Initial Data In Each Simulation Is Generated Randomly, And The Model Is Just An Approximation Of Real-World Airports, The Definition Of This Case Of Use Of Ami Through Netlogo Agents Opens An Interesting Way To Evaluate The Benefits Of Using Ami, Which Is A Significant Contribution To The Final Development Of Ami Systems.This work was partially funded by CNPq PVE Project 314017/2013-5, FAPERJ APQ1 Project 211.500/2015 and by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-0

An information fusion framework for context-based accidents prevention

The oil and gas industry is increasingly concerned with achieving and demonstrating good performance with regard occupational health and safety (OHS) issues, through the control of its OHS risks, which is consistent with its core policy and objectives. There are standards to identify and record workplace accidents and incidents to provide guiding means on prevention efforts, indicating specific failures or reference, means of correction of conditions or circumstances that culminated in an accident. Therefore, events recognition is central to OHS, since the system can selectively start proper prediction services according to the user current situation and past knowledge taken from huge databases. In this sense, a fusion framework that combines data from multiples sources to achieve more specific inferences is needed. In this paper we propose a machine learning algorithm to learn from past anomalous events related to accident events in time and space. It also uses additional knowledge, like the contextual knowledge: user profile, event location and time, etc. Our proposed model provides the big picture about risk analysis for that employee at that place in that moment in a real world environment. Our main contribution lies in building a causality model for accident investigation by means of well-defined spatiotemporal constraints in the offshore oil industry domain.This work was partially funded by CNPq BJT Project 407851/2012–7 and CNPq PVE Project 314017/2013–5

Evaluating Interaction of MAS Providing Context-Aware Services

Proceeding of: 5th KES International Conference, KES-AMSTA 2011, Manchester, UK, June 29 – July 1, 2011Much effort has been spent on suggesting and implementing new architectures of MAS to specific domains. Often each new architecture is not even compared to any existing architectures in order to evaluate their potential benefits. The evaluation of Multi-Agent Systems (MAS) is a complex problem and it does not have a single form. The present work follows the research line of considering the agent interaction as the main evaluation criteria, the most important characteristic of any complex software as autonomous agents according to [9]. So, in this paper, we have suggested an assignment of evaluation values to Agents interaction in an specific MAS architecture for providing context services by means of conversational agents. This evaluation is mainly based on the relevance of the messages content brought by an interaction. For dependant nature of the relevance of the messages, the valuation has to be adhoc, but our paper provides an example of how interesting is this alternative in order to evaluate any MAS architecture theoretically.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732- C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255, and DPS2008-07029- C02-02

Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA), a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection.This work was partially funded by the Brazilian National Council for Scientific and Technological Development projects CNPq BJT 407851/2012-7 and CNPq PVE 314017/2013-5 and projects MINECO TEC 2012-37832-C02-01, CICYT TEC 2011-28626-C02-02.Publicad

An Agent-Based Dialog Simulation Technique to Develop and Evaluate Conversational Agents

Proceedings of: 9th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 11). Salamanca, 6-8 April, 2011In this paper, we present an agent-based dialog simulation technique for learning new dialog strategies and evaluate conversational agents. Using this technique the effort necessary to acquire data required to train the dialog model and then explore new dialog strategies is considerably reduced. A set of measures has also been defined to evaluate the dialog strategy that is automatically learned and compare different dialog corpora. We have applied this technique to explore the space of possible dialog strategies and evaluate the dialogs acquired for a conversational agent that collects monitored data from patients suffering from diabetes.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

An Architecture to Provide Context-Aware Services by Means of Conversational Agents

Proceedings of: Forth Internationl Wokshop on User-Centric Technologies and Applications (CONTEXTS 2010), Valencia, September 7-10, 2010In human-human interaction, a great deal of information is conveyed without explicit communication. This context information characterizes the situation of the different entities involved in the communication process (users, place, environment and computational objects). In this paper, we present an agent-based architecture that incorporates this valuable information to provide the most adapted service to the user. One of the main characteristics of our proposal is the incorporation of conversational agents handling different domains and adapted taking into account the different users requirements and preferences by means of a context manager. This way, we ensure a natural communication between the user and the system to provide a personalized service. The implementation of our proposed architecture to develop and evaluate a context-aware railway information system is also described.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255, and DPS2008-07029-C02-02.Publicad