Natural Language Dialogue Service for Appointment Scheduling Agents

Appointment scheduling is a problem faced daily by many individuals and organizations. Cooperating agent systems have been developed to partially automate this task. In order to extend the circle of participants as far as possible we advocate the use of natural language transmitted by e-mail. We describe COSMA, a fully implemented German language server for existing appointment scheduling agent systems. COSMA can cope with multiple dialogues in parallel, and accounts for differences in dialogue behaviour between human and machine agents. NL coverage of the sublanguage is achieved through both corpus-based grammar development and the use of message extraction techniques.Comment: 8 or 9 pages, LaTeX; uses aclap.sty, epsf.te

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

An Empirical Approach to Temporal Reference Resolution

This paper presents the results of an empirical investigation of temporal reference resolution in scheduling dialogs. The algorithm adopted is primarily a linear-recency based approach that does not include a model of global focus. A fully automatic system has been developed and evaluated on unseen test data with good results. This paper presents the results of an intercoder reliability study, a model of temporal reference resolution that supports linear recency and has very good coverage, the results of the system evaluated on unseen test data, and a detailed analysis of the dialogs assessing the viability of the approach.Comment: 13 pages, latex using aclap.st

Chatbot for digital marketing and customer support: an artificial intelligence approach

Dissertação de mestrado em Computer ScienceHuman interaction with machines has never been so frequent as nowadays. In order to reduce the redundant workload of a human being that answers repeated and trivial questions regarding customer support on a digital marketing website, this work has the purpose of replacing this tedious job with an informatics tool, a dialogue tool. A dialogue tool like a Chatbot that could handle customer support to a digital marketing website, provides the opportunity of placing human resources on ”non mechanical tasks”. Given that Chatbots exchange messages directly with customers, they could collect required protocol information in all the interactions. In spite of the possibility of needing human assistance, he will not need to ask these standard questions and will improve its efficiency. By automating these required dialogues to answer questions about certain products, that would otherwise be responded by a human, the organizations will have the opportunity to place human resources in another sectors that are not so easily automated.A interação humana com máquinas nunca foi tão frequente como nos dias de hoje. Com a intenção de reduzir a quantidade de trabalho de um ser humano que receberia ao responder a questões triviais e repetidas no que diz respeito a Suporte ao Cliente, este trabalho tem o propósito de substituir um trabalho entediante por uma ferramenta informática, uma ferramenta que possibilite o diálogo entre o cliente e o serviço de suporte. Uma ferramenta como um Chatbot que poderia fornecer suporte ao cliente num website de marketing digital iria providenciar às empresas a oportunidade de alocar trabalhadores para tarefas ”menos mecânicas”. Dado que os Chatbots trocam mensagens diretamente com os clientes, estes podem recolher informações que são sempre necessárias e protocolares em todas as interações. Assim sendo, mesmo que este diálogo requira possivelmente um ser humano, este irá prescindir de fazer estas perguntas padrão, melhorando assim a eficiência deste trabalho (Suporte ao Cliente). Ao automatizar diálogos necessários para responder a questões acerca de produtos que, de outra forma seriam respondidas por um ser humano, as organizações estarão a poupar tempo e dinheiro que podem ser aplicados noutros sectores menos propícios a serem automatizados

Al Planning Assistant for Scheduling Daily Activities

Artificial conversational agents are software agents that can interact with humans in the way humans do. Siri Cortana, and Alexa are examples of intelligent agents that can help us with almost all the basic tasks. These agents are smart enough to do the basic tasks, but not as much when it comes to complex tasks, such as analyzing traffic data, reviewing scheduling conflicts, rescheduling meetings while resolving conflicts, and offering suggestions based upon data analyses (e.g. traffic patterns, weather, etc.) The actual potential of dialogue-based task agent potential remains untapped. The reason is the fact agents lack the ability to fully understand human language. Natural Language processing (NLP) makes it possible for those agents to understand humans. The current research project explores the development of a conversational agent, Schedulio, that can be connected to the user\u27s calendar and assist with the scheduling, deletion, and modification of events using natural language conversation. Additionally, current research explores the implementation of a recommendation agent that provides suggestions based upon time and slot date recommendation, location-specific weather data, and traffic patterns

Design Knowledge for Virtual Learning Companions from a Value-centered Perspective

The increasing popularity of conversational agents such as ChatGPT has sparked interest in their potential use in educational contexts but undermines the role of companionship in learning with these tools. Our study targets the design of virtual learning companions (VLCs), focusing on bonding relationships for collaborative learning while facilitating students’ time management and motivation. We draw upon design science research (DSR) to derive prescriptive design knowledge for VLCs as the core of our contribution. Through three DSR cycles, we conducted interviews with working students and experts, held interdisciplinary workshops with the target group, designed and evaluated two conceptual prototypes, and fully coded a VLC instantiation, which we tested with students in class. Our approach has yielded 9 design principles, 28 meta-requirements, and 33 design features centered around the value-in-interaction. These encompass Human-likeness and Dialogue Management, Proactive and Reactive Behavior, and Relationship Building on the Relationship Layer (DP1,3,4), Adaptation (DP2) on the Matching Layer, as well as Provision of Supportive Content, Fostering Learning Competencies, Motivational Environment, and Ethical Responsibility (DP5-8) on the Service Layer

Ontologies Supporting Intelligent Agent-Based Assistance

Intelligent agent-based assistants are systems that try to simplify peoples work based on computers. Recent research on intelligent assistance has presented significant results in several and different situations. Building such a system is a difficult task that requires expertise in numerous artificial intelligence and engineering disciplines. A key point in this kind of system is knowledge handling. The use of ontologies for representing domain knowledge and for supporting reasoning is becoming wide-spread in many areas, including intelligent assistance. In this paper we present how ontologies can be used to support intelligent assistance in a multi-agent system context. We show how ontologies may be spread over the multi-agent system architecture, highlighting their role controlling user interaction and service description. We present in detail an ontology-based conversational interface for personal assistants, showing how to design an ontology for semantic interpretation and how the interpretation process uses it for semantic analysis. We also present how ontologies are used to describe decentralized services based on a multi-agent architecture

A Pentadic Analysis of a Norwegian Health Communication Outreach Program

This thesis uses Burke Dramatism to analyze a Norwegian Health Communication Outreach Program. The program was developed to reduce the number of no-shows at the hospitals on the West Coast of Norway. No-shows is used for the act of people not showing up. Burke’s dramatism was chosen as the method of analysis because it allows me to see the program creator’s hidden motives, and the terministic screens that are not represented in the development of the program. I believe that the more terministic screens the hospitals consider when analyzing patients’ behaviors, the more ways they can identify with patients and influence them to come to their appointments. The results show that Burke’s dramatism can be used in analyzing health outreach programs. The analysis discovered that Health West might have focused more on the act-purpose and act-agent ratio, when they should have also added the scene-act and the agent-act rati

DESIGN KNOWLEDGE FOR VIRTUAL LEARNING COMPANIONS

Conversational agents (CAs) are getting smarter thanks to advances in artificial intelligence, which opens the potential to use them in educational contexts to support (working) students. In addition, CAs are turning toward relationship-oriented virtual companions (e.g., Replika). Synthesizing these trends, we derive the virtual learning companion (VLC), which aims to support working students in their time management and motivation. In addition, we propose design knowledge, which was developed as part of a design science research project. We derive nine design principles, 28 meta-requirements, and 33 categories of design features based on interviews with students and experts, the results of an interdisciplinary workshop, and a user test. We aim to demonstrate how to design VLCs to unfold their potential for individual student support