Learning Interaction between Conflicting Human Agents and Their Assistants

We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. Learning behavior via communicative actions Over last decade, substantial efforts have gone into designing intelligent artificial assistants. These assistants will help human agents in a variety of everyday tasks, as well as in tasks involving assistants as well as human agents in a conflict. Therefore such assistant should be capable of reasoning about handling and resolving conflicts, learning from previous experience. It has been well understood that to be truly useful, the assistants needs to be personalized, be trusted and become partners, and be able to learn from the human agent as well as from its own mistakes. In addition to that, to be involved in a domain where some form of interaction while conflict resolution is required, assistants need to be enabled with machine learning framework to categorize ...

• Type: Conference
• Year: 2007
• Where: ICIA
• Authors: Boris Galitsky, Boris Kovalerchuk
• Keywords: Artificial Intelligence, Assistants, Human Agents, ICIA 2007, Machine Learning