Many insect species maintain a nest around which their foraging behaviour is centered, and can use path integration to maintain an accurate estimate of their distance and direction (a vector) to their nest. Some species, such as bees and ants, can also store the vector information for multiple salient locations in the world, such as food sources, in a common coordinate system. They can also use remembered views of the terrain around salient locations or along travelled routes to guide return. Recent modelling of these abilities shows convergence on a small set of algorithms and assumptions that appear sufficient to account for a wide range of behavioural data, and which can be mapped to specific insect brain circuits. Notably, this does not include any significant topological knowledge: the insect does not need to recover the information (implicit in their vector memory) about the relationships between salient places; nor to maintain any connectedness or ordering information between view memories; nor to form any associations between views and vectors. However, there remains some experimental evidence not fully explained by these algorithms that may point towards the existence of a more complex or integrated mental map in insects.

Foraging research aims at describing, understanding, and predicting resource-gathering behaviour. Optimal Foraging Theory (OFT) is a sub-discipline that emphasises that these aims can be aided by segmenting foraging behaviour into discrete problems that can be formally described and examined with mathematical maximization techniques. Examples of such segmentation are found in the isolated treatment of issues such as patch residence time, prey selection, information gathering, risky choice, intertemporal decision making, resource allocation, competition, memory updating, group structure, and so on. Since foragers face these problems simultaneously rather than in isolation, it is unsurprising that OFT models are ‘always wrong but sometimes useful’. I will argue that a progressive optimal foraging research program should have a defined strategy for dealing with predictive failure of models. Further, I will caution against searching for brain structures responsible for solving isolated foraging problems.