Developing Robot Behavior as Travel Agent for: Social Interaction

Today social robots possible to perform roles of elder care, personal familiar, hotel caretaker, and in day-to-day interaction, and with the cost-electiveness of automation, this trend is now popular. However, one of the problem of introducing robots to new domains is the creation of social interaction logic, which principle how the robot behaves and interacts with people. It is tedious for an interaction designer to create all the behaviors for a robot by hand, and it is an incredibly challenging task to expect all the varieties of ways that humans may behave in a social interaction. To solve the problem of responding to human actions, a fuzzywuzzy logic [fig 5] algorithm with pandas data frame can be used. The system trained human-readable rules that prescribe which action the robot should take, based on taking input from designer(conversation data take from csv table [table 4] && [table 5]). In this system the above technique is can be applied to the robot learns to play the role of a travel agent.