Design of a Knowledge-Based Agent as a Social Companion

INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY SCIENCES AND ENGINEERING, 2024

By identifying concept associations during talks and drawing on prior knowledge, ontology-based chatbots preserve context. Even while these agents are able to adjust to their environment, in hostile circumstances they could still display abnormalities. These discrepancies could lead to poor action planning and ineffective adaptation. Therefore, we present a dynamic ontology-based conversational model that selects the best suited answer based on prior experience and knowledge base in order to better action planning and adaptation in hostile scenarios. Since emotions are important in human existence, our method shows the emotional state for different conversational agents instead of only emojis. For this reason, our research will illustrate a conversational bot that functions in a lifelike manner. We employ the ontology Relamodel for ontology, which consists of three parts (C, R,).

2005

Socialdialogue can be used by an embodied,interface agent both to satisfy "interpersonal" goals, such as building rapport with the user and demonstrating,the expertise of the agent, and to directly or indirectly satisfy task goals, such as acquiring background,information about the user. We describe the ongoing,development,of an embodied conversational agent that is capable of multimodal,input understanding,and,output,generation and,operates in a limited application domain,in which both social and task - oriented dialogue,are used. An,approach,to discourse planning for social dialogue is described, along with an implementation,and preliminary evaluation.

2005

This paper presents and discusses several technical issues in implementing the conversation intelligent agent. In this work, we focus on domain knowledge models that enable structured queries on the field of epidemic crisis. We will simulate this system with sample conversation taken from our target Domain-Specific knowledge on the recent world epidemic crisis, Severe Acute Respiratory Syndrome (SARS). A solution

In order to engage with user on more personal level, natural human-machine interaction is starting to virtual or even physical entities resembling human collocutors. Namely, through human-like entities the designed multimodal interaction models, try to adapt to user’s context and to facilitate context of the conversational situation. The designed multimodal processes tend to follow the ‘’rules’’ and ques as implanted during face-face interaction among humans. In this way, the integration and exploitation of embodied conversational agents (ECA) for human-like interaction seems only natural. The ECA’s artificial body and articulation capabilities are already close to those found on real humans. From skin, face, hands, and body posture, these virtual entities tend to look and behave as realistically as possible. Furthermore, ECAs tend to imitate as many features of human face-face dialogs as possible, and integrate them into interaction as synchronized as possible. One of the essential functions in face-to-face interaction is the ability to reproduce synchronized verbal and co-verbal signals coupled into conversational behavior. Other signals, such as: social cues, attitude (emotions), personality, eye-blinks, and spontaneous head movements are equally important, and have to be blended into multimodal expressions. However, designing a realistic entity that acts realistically like humans do, is a daunting task. Modern 3D environments and 3D modeling tools, such as: Maya, Daz3D, Blender, Panda3D and Unity, have opened up a completely new possibilities to design virtual entities, which appear almost (if not completely) like real-life persons. However, the modern 3D technology mostly covers the design and deployment part of such realism, while the realism of the behavior itself and its diversity and dynamic nature are generally not the focus of 3D modeling frameworks. Namely, most of the animation prepared in 3D frameworks is planned, designed in advance, and over well-written and well-designed situations. Therefore, it integrates limited diversity as well as limited capacity to adapt to a new set of parameters. As a result, 3D frameworks have a limited capacity to handle highly dynamic and interchangeable contexts present in human interaction. In this paper we, therefore, outline EVA U-Realizer, the second generation of proprietary behavior realization module. The goal of the realizer is to integrate the diversity, responsiveness, and adaptiveness that is required for the facilitation of conversational responses with animation capacities and realism provided by 3D modeling frameworks. As a result, the presented novel realizer is built over Unity 3D game engine’s core. The proposed realizer considerably improves the capabilities of the animation engine itself, by providing interpreter and executor for incorporating dynamic and real-time generated conversational artefacts, similar to those found in conversations among humans.

ACM Transactions on Interactive Intelligent Systems

Conversational agents (CAs) are systems that interact with humans through natural language user interfaces. They include systems with a range of conversational capabilities and modalities. For example, there are text-or voice-only question-answering interactions such as Apple Siri, Google Assistant, and Amazon Alexa, and there are also multimodal conversational AI agents that can engage users in long-term dialogues. Advances in speech recognition, natural language processing, and computer vision have resulted in a greater acceptance and use of CAs. CAs have already started to play important roles in various healthcare settings, including assisting clinicians during consultations, assisting consumers in changing health behaviours, and helping patients such as the elderly in their living environments.

… Agents. MIT Press, …, 1999

Embodied conversational agents (ECAs) are not just computer interfaces represented by way of human or animal bodies. And they are not just interfaces where those human or animal bodies are lifelike or believable in their actions and their reactions to human users.

2001

Abstract. This paper describes a conversational agent that supports knowledge creation in a community. We propose a conversational agent called virtualized-ego that represents the other self of a community member and can talk on behalf of the member. Knowledge of a virtualized-ego is compiled from everyday e-mails of a real community member. We have developed a system called EgoChat to investigate the ideas of supporting community knowledge creation by using virtualized-egos.

2019

M-Path is an embodied conversational agent developed to achieve natural interaction using empathic behaviors. This paper is aimed to describe the details of the conversational management system within the M-Path framework that manages dialogue interaction with an emotional awareness. Our conversational system is equipped with a goal-directed narrative structure that adapts to the emotional reactions of the user using empathy mechanisms. We further show the implementation and a preliminary evaluation of our system in a consultation scenario, where our agent uses text-based dialogue interaction to conduct surveys.

WebAnima is an interface agent specially designed to assist team members of a CSCW application during their daily work based on computers. In WebAnima, the intelligent behavior is guaranteed thanks to a conversational interface and ontologies that support semantic interpretation. We believe that embodied conversational assistants will improve the quality of assistance and increase collaboration between project members. In this paper, we present the embodied conversational assistant and its insertion into a multi-agent system designed for research and development projects. We describe the design of the agent, highlighting the role of ontologies for semantic interpretation and the dynamic behavior of the embodied animated agent.

Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020

Social isolation and loneliness affect one-third to one-half of the elderly population, and these have a very negative impact on the physical and mental health of the elderly. Cate is an Embodied Conversational Agent designed to alleviate social isolation and loneliness of the elderly. It takes in user inputs through buttons and responds through text-to-speech and emotion animations developed with the use of SmartBody. Interviews were conducted to identify what the elders like to talk about and how elders interact in general. An end-user evaluation form and an observation checklist were used to see what the elders thought of the application. Cate achieved an overall satisfaction score of 3.98 on a scale of 1 (lowest) to 5 (highest). Based on the results, elders generally like interacting with Cate and can see Cate as a possible companion.