Précis of Robot Shaping: An Experiment in Behavior Engineering
نویسندگان
چکیده
The book is about designing and building learning autonomous robots. An autonomous robot is a remarkable example of a device that is difficult to design and program, because it must carry out its task in a partially unknown and unpredictable environment, with which it interacts through noisy sensors and actuators. There is a fairly widespread opinion that a good way of coping with this situation would be to endow autonomous robots with the ability to acquire knowledge from experience. We explore this idea by taking one of the possible approaches to the construction of a learning robot, that is, an approach based on reinforcement learning, with reinforcements coming from a trainer that observes the robot and evaluates its performance. In fact, we use the expression robot shaping to denote the use of learning as a means to translate suggestions coming from an external trainer into an effective control strategy that allows a robot to achieve a goal. We borrowed the term shaping from experimental psychology (Skinner, 1938), because training an artificial robot somewhat resembles what experimental psychologists do in their laboratories, when they train an experimental subject to produce a predefined response. The important point, which differentiates our approach from most current research on learning autonomous agents, is that the trainer plays a fundamental role in the learning process: most of the book is aimed at showing how to use a trainer to develop control systems for simulated and real robots.
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ورودعنوان ژورنال:
- Adaptive Behaviour
دوره 5 شماره
صفحات -
تاریخ انتشار 1997