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If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.
Customer service
All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com
Sale & Press
If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com
Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant systemenvironment interaction. Both single and multiagent concepts are available for implementation of learning. The current research work describes a multiagent based reinforcement learning using the concept of behaviourbased robotics for autonomous exploration of mobile robots.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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