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Interactive Agents Learning their Environment


Michiel Hildebrand, Anton Eliëns, Zhisheng Huang and Cees Visser

paper

Abstract

In this paper we describe the implementation of interactive agents capable of gathering and extending their knowledge. Interactive agents are designed to perform tasks requested by a user in natural language. Using simple sentences the agent can answer questions and in case a task can not be fulfilled the agent must communicate with the user. In particular, an interactive agent can tell when necessary information for a task is missing, giving the user a chance to supply this information, which may in effect result in teaching the agent. The interactive agent platform is implemented in DLP, a tool for the implementation of 3D web agents. In this paper we discuss the motivation for interactive agents, the learning mechanisms and it's realization in the DLP platform.


[] readme titles system demo dlp vr slides resources