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"[Researchers] discovered how bacteria collectively gather information about their environment and find an optimal path to growth, even in the most complex terrains...'Based on confidence in their own information and decisions, bacteria can adjust their interactions with their peers,' Prof. Ben-Jacob says. 'When an individual bacterium finds a more beneficial path, it pays less attention to the signals from the other cells. But at other times, upon encountering challenging paths, the individual cell will increase its interaction with the other cells and learn from its peers. Since each of the cells adopts the same strategy, the group as a whole is able to find an optimal trajectory in an extremely complex terrain.'" (Hunka 2011:1)
"Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers’ influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots." (Shklarsh 2011:1)
Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions
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