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This paper proposes a human-like action recognition system which can output the result of human action recognition just like the case human does. The system targets actions associated with regular human activity such as walking or lying down, and uses three human recognition characteristics: using specific features of an action to recognize that action; recognition of simultaneous actions; and summarization of recognition results over a short time interval. Experimental results demonstrate the effectiveness of human-like recognition for identifying actions and the superior performance of the proposed system with respect to conventional action recognitions systems. Human-like recognition is expected to ensure smooth communication between humans and robots and enhances the support functionality.