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- 2006–7, Massimo Vergassola et al., "‘Infotaxis’ as a strategy for searching without gradients", in Nature, volume 445, pages 406–409 (2007 January 25)
- 2008, Caihua Xiong, Honghai Liu, Yongan Huang, Youlun Xiong (editors), Intelligent Robotics and Applications: First International Conference ICIRA 2008, page 1206:
- Some literatures investigated the odor source localization by robots mimicking biologic behaviors, such as chemotaxis and anemotaxis , or custom algorithms like fluxotaxis and infotaxis . The multi-robot system has more advantages than single robot in odor source localization. First, the expected search time can be decreased. Second, the multi-robot system does not easily fall into local maxima.
- 2009, M.G. Velard et al., "Mathematical Approach to Sensory Motor Control and Memory", Chapter 5 of Paola Arena and Luca Patanè (editors), Spatial Temporal Patterns for Action-Oriented Perception in Roving Robots, Springer, →ISBN, page 260:
- In the framework of the so-called infotaxis algorithm any search process can be thought of as acquisition of information on source location. Thus information plays a role similar to concentration in chemotaxis. Then the infotaxis strategy locally maximizes the expected rate of information gain.
- 2009, Huan Liu, John Salerno, Michael Young, Social Computing and Behavioral Modeling, page 94:
- In a recent paper, Vergassola et al. demonstrated that infotaxis, which is motion based on expected information gain, can be a more effective search strategy when the source signal is weak than conventional methods such as moving along the gradient of a chemical concentration . The infotaxis algorithm combines the two competing goals of exploration of possible search moves and exploitation of received signals to guide the searcher in the direction with the highest probability of finding the source .
- 2010, Eduardo Martin Moraud and Dominique Martinez, "Effectiveness and Robustness of Robot Infotaxis for Searching in Dilute Conditions", in Frontiers in Neurorobotics, 4:1