Ryabko, Reznikova, the Use of Ideas of Information Theory for Studying 'Language' and Intelligence in Ants

The approach taken is to investigate the process of information transmission by measuring time duration which the animals spend on transmitting messages of definite lengths and complexities, not that of signal deciphering (trying to map certain behavior to a linguistic entity that bears meaning). "The messages of definite lengths and complexities" here is abstractly just finite binary sequences $0100100111$ etc., implmented by binary tree mazes: each fork corresponds to a $0$(left) or an $1$(right), a path from the root to a leaf is then coded uniquely by a finite sequence of $0,1$s. All except for one leaf are empty, and the one nonempty leaf has food in it. All paths are designed to be of equal length. Every fork corresponds to a binary choice, which in turn corresponds to one bit of information to be transmitted. Example: in a $Y$-shaped maze, one bit of information should be transmitted by a scout to other individuals.

Highly motivated (by starvation and such) ants are placed in an arena which was divided into two sections, one containing the nest (with colonies each of about 2000 individuals), and the other with an experimental system (a binary tree maze). The colonies were found to include teams of constant membership, consisting of one scout and 3-8 foragers; the scout mobilized only members of its team to the food.

In trials, one of the scouts that were moving on the experimental arena was placed on a leaf of the binary tree that contained the food, and the scout returned to the nest by itself. Other possibilities that could help the ants to find the food except for information contact with the scout is eliminated, including the use of an odor track (the maze was replaced by an identical one when the scout returned and was contacting its team). Briefly speaking, the scouts needed to really remember the path they traversed in the maze.

It was found that, when the scout touched the forager ants after returning, some foragers will leave the nest for the maze, and the duration of this kind of contact is far longer than other contacts (made for the exchange of food); more than 30s vs 5s. Statistically the hypothesis that forager ants, upon contact with a scount that returned, find the leaf containing the food by chance is rejected by comparing the time used to find the food when the individuals are informed or not. Surprizingly, the mean time for uninformed ants to find the food after following the sequence of turns LRRL is far shorter than RLLR (RRRR shorter than LLLL but not that radical), and it seems that informed ants are more likely to find the food faster when the required sequence is RLLR or LRRL instead of LLLL and RRRR. However since the amounts of sampling is small these can be by chances.

Under the assumption that for length $i$ informations, the duration of the contacts between the scouts and foragers $t=ai+b$, the rate of infformation transmission, $a$, is found to be approx. 1 bit per minute. The contact was considered to begin when the scout touched the first forager ant and to end when the first two foragers left the nest for the maze, so even if the ants are starved and highly motivated, the rate is an effective one (but whats the difference anyhow, when you don't do anything upon hearing a bad message, it amounts to the fact that no information was transmitted to you).

Of interest is that for sequences "of low Kolmogorov complexities", it took less time for the information to be transmitted. The simpler the text the less time for information transmission. But here the notion of Kolmogorov complexities is dubitable (or I simply don't understand Kolmogorov complexity that well): which universal Turing machine is computing the sequences? Kolmogorov complexities for different universal Turing machines for an equivalence class defined by equivalent iff $$ C_{T_1}(s) - C_{T_2}(s) < C_{T_1,T_2} $$ so there is an integer shift that makes some sequences simpler for $T_1$ and some simpler for $T_2$, in particular for simple sequences, and Kolmogorov complexities work well only for complex sequences (it works asymptotically). In addition to assuming that ants can be seen as possessing abilities approximating to universal Turing machines, one needs to assume that the same universal Turing machine is computing really simple sequences like 010100. Human intuition might suggest that 010101 is more regular than 011010, but this corresponds to a class of specific implementation of universal Turing machines. Which one should be the specific implementation class is unclear, and the notion of intuitive regularity that classifies 011010 to be less regular than 010101 might not exist at all. The comparison data of mean durations also don't look that significant so that one can suggest that ants can "use simple forms of rule extraction in order to optimize their messages".