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In decision making, Pepper always finds out the best strategy based on external situation, existing knowledge and reinforcement learning.
With various sensors, Pepper picks up and analyzes real-time information from its surrounding. For instance, Pepper can sense the customer flow, the product display and the noise level in a shopping mall to identify the most appropriate way to approach the customers.
Pepper uses its built-in knowledge to meet the user’s needs. On hearing a question from the user, Pepper taps into its semantic understanding device and knowledge base to find out the appropriate answer.
In addition, Pepper keeps optimizing its decision-making strategies through reinforcement learning. When Pepper receives positive feedback, it will reinforce the decision it has made, which helps it satisfy similar user demand in a more efficient manner in the future.
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