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From OwnConcepts#Epistemotaxis to navigating information density
The premise of using "taxis" or movement on a landscape is that a metric is available. The metric in term allows for estimations of distances which in turn allow for comparision which allows to find e.g. shorter paths, alternative paths, etc. Consequently considering movement in a body of knowledge, or even knowledge overall, or epistemotaxis, assumes there is such an objective metric. The difference though between a knowledge landscape or an information landscape with a "traditional" landscape e.g. a forest is that even though distances are indeed objectives i.e. 10m between a tree and another regardless of what animals is crossing them, the speed and energy expenditure required can be completly different. The analogy is interesting is we consider mulitple learners with their current body of knowledge each desiring to reach a new body of knowledge e.g. understand the concept of a map in mathematics. We can imagine an objective knowledge graph with a node for "map" that and a coloring of that graph with a color for each learner. A learner with e.g. the color green might have colored nodes related to basic geometry, another with the color red with basic geometry but also basics of programming including the function map in JavaScript and another learning with colored in purple with only basic arithmetics. We can safely assume that the distance as the smallest number of edges from any of a colored node will be different for each learner. If all learners can help each other it becomes efficient to find the shortest shared path.