Author:
Stefan Bosse
Affiliation:
University of Bremen, Dept. Mathematics & Computer Science, 28359 Bremen, Germany
Keyword(s):
Chat Bots, Natural Language Processing, Human-machine Interface, Self-organising MAS, Agent-based Computing, Crowd Sensing.
Abstract:
Today human-machine dialogues performed and moderated by chat bots are ubiquitous. Commonly, centralised and server-based chat bot software is used to implement rule-based and intelligent dialogue robots. Furthermore, human networking is not supported. Rule-based chat bots typically implement an interface to a knowledge data base in a more natural way. The dialogue topics are narrowed and static. Intelligent chat bots aim to improve dialogues and conversational quality over time and user experience. In this work, mobile agents are used to implement a distributed, decentralised, serverless dialogue robot network that enables ad-hoc communication between humans and machines (networks) and between human groups via the chat bot network (supporting personalized and mass communication). I.e., the chat bot networks aims to extend the communication and social interaction range of humans, especially in mobile environments, by a distributed knowledge and data base approach. Additionally, the c
hat bot network is a sensor data acquisition and data aggregator system enabling large-scale crowd-based analytics. A first proof-of-concept demonstrator is shown identifying the challenges arising with self-organising distributed chat bot networks in resource-constrained mobile networks. The novelty of this work is a hybrid chat bot multi-agent architecture enabling scalable distributed and adaptive communicating chat bot networks.
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