Encyclopedia of the Sciences of Learning
Springer Science+Business Media, LLC 2012
Norbert M. Seel
Intelligent Communication in Animals

Zhanna ReznikovaContact Information

(1)  Laboratory of Behavioural Ecology of Animal Communities, Institute of Systematics and Ecology of Animals, Siberian Branch RAS and Novosibirsk State University, Frunze st. 11, Novosibirsk, 630091, Russia

Contact Information Zhanna Reznikova
Email: zhanna@reznikova.net

Without Abstract


Complex communication; Information transferring; Language behavior


What can be called “intelligent communication” or “language behavior” in animals and how does it differ from communication? The term “communication” has a wide variety of meanings, which is of no wonder, since communication is a diverse and widespread phenomenon that serves as a substance of any social behavior. Most of the signals that animals send to one another communicate the intention, emotional state, or identity of the sender. In the great majority of signaling interactions animals influence others rather than inform them. The term “language behavior” usually refers to animal communication systems in which referential signals exist that can be compared with words in a human language. Some species use distinctive signals which seem to refer to definite external stimuli, for example, types of predators or kinds of food. If such signals provide receivers with sufficient information to determine the context underlying signal production which, in turn, allows them to predict environmental events, the signals are regarded as functionally referential. “Intelligent communication in animals” can be defined as a communication that includes referential signals and means for transferring information about remote events. The most complex forms of intelligent communication possess such important properties as productivity, that is, abilities for generating potentially unlimited (or, at least, great) numbers of messages on the basis of finite number of signals, and flexibility which allow signalers and perceivers to grasp regularities in their environment and use them for optimization of messages. Some sophisticated forms of intelligent communication share with human languages the following characteristic: the length of a message is connected with the frequency of its occurrence, that is, the more frequent the message, the shorter it is (Ryabko and Reznikova 2009).

Theoretical Background

Attempts to elucidate the question whether animals can intentionally exchange meaningful messages are based on a natural idea that the complexity of communication should be connected with high levels of sociality and cooperation in animals’ societies. In the 1960s and 1970s, elegant but ambiguous experiments were conducted with highly social intelligent animals, which were asked to pass some pieces of information to each other. The obtained results enabled researchers to suggest that chimpanzees possess means for transferring information about both location and properties of objects, and dolphins can coordinate each other’s behavior, probably, by means of acoustic signals. Despite these supportive experiments, the question of existence of developed “languages” in nonhumans remained so far obscure.

In 1960, the linguist Charles F. Hockett proposed a list of design features of human language which separate it from animal communication, even at its most complex forms. Some of these features have been later attributed to animal language behavior expressed in nature (for instance, honeybee dance language) and in the laboratory (language-training experiments, mainly with apes): interchangeability, specialization, discreteness, arbitrariness of units, displacement (the ability to “talk” about things that are not physically present), semanticity, productivity, and elements of cultural transmission. However, the main difficulties in the analysis of animal language behavior appear to be methodological. Although many researchers have tried to directly decipher animal “languages” by looking for “letters” and “words” and by compiling “dictionaries”, a combined power of different methods for studying is needed to evaluate the potential complexity of the information being transferred by animals.

Important Scientific Research and Open Questions

At least three main approaches to the problem of animal language behavior have been applied recently, and many fascinating results have been obtained by each of them (for reviews see Reznikova 2007a, b).

The first approach is aimed at direct decoding of animal signals. Decoding the function and meaning of natural communications is a notoriously difficult problem. A bottleneck here is low repeatability of standard living situations, which could give keys for cracking animals’ species-specific codes, as well as difficulties with recording signals that are distinct enough and are frequently used. Up to now, there are two types of animal “languages” that have been partly deciphered: the fragments of honeybees’ “dance language” and “semantic” acoustic signalizations in vervet monkeys and in several other species. In both types of communications, expressive and distinctive signals correspond to repeatable and frequently occurring situations in the context of the animals’ life.

The honeybee “dance language” was discovered by K. von Frisch and confirmed in the 1990s by the use of a robotic bee. Successful forager honeybees (Apis mellifera) are able to recruit other bees to a distant goal by specific “dance” movements together with other components of communications such as odors and sounds. Many researchers agree now that an abstract, or symbolic, code is used to transmit the information about the direction and distance to a desired object, and this communication system meets the main Hockett’s criteria. However, it is still an open question to what extent can bees display productivity and flexibility of communication.

The discovery of “semantic vocalization” in vervet monkeys (and later in some other species of primates as well as meerkats, prairie dogs, ground squirrels and several group-living bird species) was based on field playback experiments. It turned out that distinctive calls emitted by animals for different classes of predators, and even for different types of predator’s behavior resulted in highly adaptive escape responses. Some animals use distinctive calls for different kinds of food, and dolphins use individually distinct whistles as referential signals among conspecifics. All these calls appeared to function as representational, or semantic, signals. It is interesting to note that Diana monkeys are able to “translate” alarm calls of sympatric chimpanzees and Campbell’s monkeys, and respond to these calls with their own corresponding alarm calls; they also react adequately to combinations of elements of calls experimentally compiled by researchers. All these findings have dramatically changed the common understanding of acoustic communication in animals, which were believed to be only an expression of their current emotional status. However, this type of communication does not meet several important criteria to be considered “language-like.” For instance, vervets’ communication, in contrast to humans and even honeybees, does not possess displacement and productivity.

The second approach for studying natural communication of animals has been suggested based on the ideas of information theory (Ryabko and Reznikova 2009). The elaborated experimental paradigm has been applied to ants, and can be extended to other social species of animals which need to pass and memorize complex “messages.” The main point of this approach is not to decipher signals but to investigate just the process of information transmission, by measuring the time duration which animals spend on transmitting messages of definite length and complexity. The scheme of experiments is based on a situation where animals must transfer a specific amount of information to each other. The crucial idea is that experimenters know exactly the quantity of information (in bits) to be transferred. In experiments with ants, to organize the process of information transmission between them, a special maze has been used, called a “binary tree,” where the number and sequence of turns toward the goal (Left, L and Right, R) correspond to the amount of the information to be transferred. In order to obtain food, scouting ants had to transfer the information about the sequence of turns toward a trough with syrup. The number of bits necessary to choose the correct way was equal to the number of turns to be taken. To estimate the potential productivity of ants’ “language” one can count the total number of different possible routes to the goal which is at least 26 = 64 in the binary tree with six forks. Besides, seemingly with honeybees, ants are able to pass information about remote events. It is worth noting that this experimental schema provides a way for studying important characteristics of animal communication by other known methods such as the rate of information transmission and the potential flexibility of communication systems. Ants appeared to be able not only to memorize and pass each other up to 6 bits of information but also to grasp regularities in the “text” to be transferred (i.e., regular sequence LLLLLL is “simpler” than a random one, say, LLRLR) and use them to optimize their messages. This can be considered as an evidence of flexibility of ants’ intelligent communication.

The third approach to studying intelligent communication is based on a direct dialogue with animals by means of intermediary languages such as gesture sign language used by deaf people, a specially designed language, based on a set of abstract symbols, and elements of human speech addressed to animals. Being applied mainly to apes, but also to dolphins, gray parrots, and even to one dog, this approach has revealed astonishing mental skills in animals. Members of all species listed above can associate abstract signs with meanings and apply “proto-grammars.” Intelligent communication of apes based on artificial intermediary languages meets all of Hockett’s criteria. For example, “speaking” apes generate new symbols with new meanings; use these signs to communicate simple statements, requests, and questions; refer to objects and events displaced in time and space; classify novel objects into appropriate semantic categories; and transmit their knowledge to peers and offspring. However, this way to communicate with animals is fully based on adopted human languages. Surprisingly little is known yet about the natural communication systems of the species that were involved in language-training experiments, although they displayed significant “linguistic” and cognitive potential.

Future Research

During the last decades, the combined efforts of scientists applying different experimental approaches have revealed some features of intelligent communication in animals which were earlier attributed exclusively to humans. Among them one can list animals’ ability to use referential signals organized by “proto-grammatic” rules, to transfer messages in an abstract “symbolic” form, to create messages about things and events distant in time and space, to interpret messages of other species, and to extract meaningful parts from strangers’ signals.

However, there are some points of discontinuity with the communicative practice of animals. Although members of several species demonstrate understanding of grammatical rules when using artificial intermediary languages, there is no evidence of syntax in the natural communication of animals. There is also little evidence of learnability and flexibility in natural communication systems of animals. There is much to be done to reveal the evolutionary roots of such a sophisticated system of communication as human language. Finally, studying the intelligent communication of animals is a good tool to judge about their cognitive abilities.


Abstract Concept Learning in Animals

Analogical Reasoning in Animals

Animal Language Acquisition

Animal Intelligence

Cognitive Aspects of Natural Communication in Primates

Imitation: Definition, Evidence, and Mechanisms

Learning Set Formation and Conceptualization

Linguistic and Cognitive Capacities in Apes

Referential Vocal Learning by Gray Parrots

Theory of Mind in Animals


Reznikova, Z. (2007a). Dialog with black box: Using information theory to study animal language behaviour. Acta Ethologica, 10(1), 1–12.
Reznikova, Z. (2007b). Animal intelligence: From individual to social cognition. Cambridge: Cambridge University Press.
Ryabko, B., & Reznikova, Z. (2009). The use of ideas of information theory for studying “language” and intelligence in ants. Entropy, 11, 836–853.
Further Reading
Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002). The faculty of language. What is it, who has it, and how did it evolve? Science, 298, 1569–1579.
Rendall, D., Owren, M. J., & Ryan, M. J. (2009). What do animal signals mean? Animal Behaviour, 78, 233–240.
Seyfarth, R. M., & Cheney, D. L. (2003). Signallers and receivers in animal communication. Annual Review of Psychology, 54, 145–173.