Autonomous Agents

1998. Auflage 1998
ISBN: 978-0-7923-8137-2
Verlag: Springer Us

Buch, Englisch, 125 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1030 g

An agent is a system capable of perceiving the environment, reasoning with the percepts and then acting upon the world. Agents can be purely software systems, in which case their percepts and output `actions' are encoded binary strings. However, agents can also be realized in hardware, and then they are robots. The Artificial Intelligence community frequently views robots as embodied intelligent agents.
The First International Conference on Autonomous Agents was held in Santa Monica, California, in February 1997. This conference brought together researchers from around the world with interests in agents, whether implemented purely in software or in hardware. The conference featured such topics as intelligent software agents, agents in virtual environments, agents in the entertainment industry, and robotic agents. Papers on robotic agents were selected for this volume.
will be of interest to researchers and students in the area of artificial intelligence and robotics.

Zielgruppe

Research

Autoren/Hrsg.

Bekey, George A

Fachgebiete

• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

Development of an Autonomous Quadruped Robot for Robot Entertainment.- Basic Visual and Motor Agents for Increasingly Complex Behavior Generation on a Mobile Robot.- An Autonomous Spacecraft Agent Prototype.- Map Generation by Cooperative Low-Cost Robots in Structured Unknown Environments.- Grounding Mundane Inference in Perception.- Interleaving Planning and Robot Execution for Asynchronous User Requests.- Integrated Premission Planning and Execution for Unmanned Ground Vehicles.- Learning View Graphs for Robot Navigation.