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This paper presents simulation and analysis of a collective of autonomous unmanned ground-based vehicles navigating a building searching for increasing smoke concentrations. The vehicles communicate smoke concentrations to each other to determine the location of the highest concentration value. The data generated front the robots' sensors is used to activate a semantic network to generate data for further cognitive operations. Statistical analysis is employed on the data to identify schema and themes, which enable the robots to convey a story of their experiences, thus emulating human episodic memory.