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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.
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readme
titles
system
demo
dlp
vr
slides
resources