A learning program which plays partnership dominoes
Communications of the ACM
Robots, productivity and quality
ACM '72 Proceedings of the ACM annual conference - Volume 1
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Decision analysis for an experimental robot with unreliable sensors
IJCAI'75 Proceedings of the 4th international joint conference on Artificial intelligence - Volume 1
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This paper reports on current work at the University of California at Berkeley whose goal is the design and implementation of a relatively inexpensive, but versatile, experimental, computer-controlled robot suitable for use in either a research or educational setting. The Berkeley robot, dubbed Jason, is nearing comoletion and hardware tests are now being conducted. Jason is designed so as to permit it to navigate and manipulate simple objects in a real-world environment. It uses a variety of sensory-motor and communication devices; among these are an ultrasonic range, motion, and material detector, an isolated-word speech recognizer, a limited speech synthesizer, six inexpensive proximity detectors, and two arms for simple manipulation, all of which are mounted on a platform chassis. The robot vehicle is remotely controlled, using radio telemetry, by a time-shared, virtual memory, HP-3000 mini-computer, utilizing adaptive learning programs. Jason was primarily constructed to explore: (1) how an inexpensive, real-world robot system might be designed, and (2) what problems a robot "encounters" and "creates" while performing tasks in a real-world environment populated by humans. The results of this research will hopefully enable us to design and build better (more reliable and safer) robots at a modest price that are still capable of performing a variety of interesting and useful tasks.