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Innovations in Intelligent Machines 1 - Javaan Singh Chahl et al (Eds) part 12

Tham khảo tài liệu 'innovations in intelligent machines 1 - javaan singh chahl et al (eds) part 12', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 214 S. Pruter et al. Fig. 18. Separation of the actual feed-forward network indicated by FFN in the figure and the back-propagation training algorithm hardware the numbers of nodes and connections that the robot can store on its hardware is limited. From a hardware point of view the memory available on the robot itself is the major constraint. In addition to the actual learning problem this section is also faced with the challenge of finding a good compromise between the network s complexity and its processing accuracy. A second constraint to be taken into account concerns the update mechanism of the learning algorithm. It is known that back-propagation temporarily stores the calculated error counts as well as all the weight changes Awjj 4 . This leads to a doubling of the memory requirements which would exhaust the robot s onboard memory size even for moderately sized networks. As a solution for the problem this section stores those values on the central control PC and communicates the weight changes by means of the wireless communication facility. This separation is illustrated in Fig. 18. Thereby the neural network can be trained on a PC using the current outputs of the FFN on the robot. A further benefit of the method is that the training can be done during the soccer game provided that the communication channel has enough capacity for game-control and FFN data. The FFN sends its output values to the PC which then compares them with the camera data after the latency time t. The PC uses the comparison results to train its network weights without interfering with the robot control. When training is completed and the results are better than the currently used configuration the new weights are sent to the robot which start computing the next cycle with these weights. 4.3 Methods Since the coding of the present problem is not trivial this section provides a detailed description. In order to avoid a combinatorial explosion the robot is set at the origin of the .