EREBOTS: Privacy-Compliant Agent-Based Platform for Multi-Scenario Personalized Health-Assistant Chatbots

Abstract

Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and are becoming ingrained into humans’ habits due to factors including (i) the availability of mobile devices such as smartphones and tablets, (ii) the increasingly engaging nature of chatbot interactions, (iii) the release of dedicated APIs from messaging platforms, and (iv) increasingly complex AI-based mechanisms to power the bots’ behaviors. Nevertheless, most of the modern chatbots rely on state machines (implementing conversational rules) and one-fits-all approaches, neglecting personalization, data-stream privacy management, multi-topic management/interconnection, and multimodal interactions. Objective. This work addresses the challenges above through an agent-based framework for chatbot development named EREBOTS. Methods. The foundations of the framework are based on the implementation of (i) multi-front-end connectors and interfaces (i.e., Telegram, dedicated App, and web interface), (ii) enabling the configuration of multi-scenario behaviors (i.e., preventive physical conditioning, smoking cessation, and support for breast-cancer survivors), (iii) online learning, (iv) personalized conversations and recommendations (i.e., mood boost, anti-craving persuasion, and balance-preserving physical exercises), and (v) responsive multi-device monitoring interface (i.e., doctor and admin). Results. EREBOTS has been tested in the context of physical balance preservation in social confinement times (due to the ongoing pandemic). Thirteen individuals characterized by diverse age, gender, and country distribution have actively participated in the experimentation, reporting advancements in the physical balance and overall satisfaction of the interaction and exercises’ variety they have been proposed.

Emerging Technologies of Natural Language‐Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics

“…e early development of chatbot was mostly dominated by a single domain. It has been observed that more research has been directed towards open domain [45][46][47][48][49] and multidomain [50][51][52] in recent years. Single-domain chatbots are limited to accomplishing specific tasks, while multidomain or open domain chatbots can better meet the needs of smart assistants and even further provide people's companionship or social applications.…”

Personalization Trade-offs in Designing a Dialogue-based Information System for Support-Seeking of Sexual Violence Survivors

“…While prior work has examined design implications [2,40,50,69] and technological implementations [12] for conversational personalization systems, how to design personalization of such a system has been relatively less explored. As personalization of information is a key feature of such conversational systems, compared to other systems like a reporting or logging tool, a deeper understanding in design issues arising from personalization is necessary.…”

Cohort and Trajectory Analysis in Multi-Agent Support Systems for Cancer Survivors

“…Figure 1 shows the EREBOTS platform [6] comprises four main components: Database management, Communication Server, Multi-Agent System back-end for the doctor agents, and Multi-Agent System back-end and front-end for the patient agents.…”

“…In this paper, we introduce a cohort and trajectory analysis (CTA) approach for the EREBOTS agent-based personalized chatbot system [6]. The CTA enables EREBOTS to support patients through treatment adjustment, and provides a dedicated interface for clinicians to fine-tune the chatbot behaviors.…”