Cooperative strategies and the evolution of communication

Cooperative signaling behavior of roost location in a leaf-roosting bat

Research suggests that social calls are important for conveying information about food and roost location in bats. However, no studies have specifically documented calls that are used to actively attract conspecifics to roosting locations. Here we describe the cooperative signaling behavior of roost location towards flying conspecifics in Spix's disc-winged bat (Thyroptera tricolor), a species that uses a highly ephemeral roosting resource. Two types of calls were recorded during field experiments; one from flying individuals termed "inquiry calls" and another from roosting bats termed "response calls". Inquiry calls were emitted by flying bats immediately upon release, and quickly elicited production of response calls from roosting individuals. Most flying bats entered the roost when roosting individuals responded, while very few bats entered the roost in the absence of a response. During playback experiments, we found significant differences in response rates among individuals, which could be caused by diverse intrinsic and extrinsic factors. In addition, results of our ongoing field studies suggest that the cooperative signaling behavior of roost location is important in maintaining social cohesion, and that the use of a larger home range when resources are scarcer may decrease group stability by hindering communication.

Common language or Tower of Babel? On the evolutionary dynamics of signals and their meanings

We investigate how the evolution of communication strategies affects signal credibility when there is common interest as well as a conflict between communicating individuals. Taking alarm calls as an example, we show that if the temptation to cheat is low, a single signal is used in the population. If the temptation increases cheaters will erode the credibility of a signal, and an honest mutant using a different signal ('a private code') will be very successful until this, in turn, is cracked by cheaters. In such a system, signal use fluctuates in time and space and hence the meaning of a given signal is not constant. When the temptation to cheat is too large, no honest communication can maintain itself in a Tower of Babel of many signals. We discuss our analysis in the light of the Green Beard mechanism for the evolution of altruism.

Predicting nearest agent distances in artificial worlds

In a number of multi-agent artificial life studies where agents interact over limited distances, the emergence and/or evolution of a specific behavior may depend critically upon interagent distances. Little theoretical analysis has been done previously concerning how to predict such distances. In this paper, we derive a probabilistic method that, for an agent at an arbitrary location in a two-dimensional cellular world, predicts the expected distance to a nearest other agent. Our method works for many world topologies, and we apply it to determine the expected distance for six commonly used ones. Further, the method is readily adapted to handle special restrictions. Over a wide variety of agent densities we show that the theoretically predicted distances are largely in agreement with the distances measured in computational experiments with randomly placed agents. We then utilize our prediction method to interpret recent observations that an imprecise threshold in the density of agents exists for the evolution of communication. We thus illustrate that, despite its conceptual simplicity, our method can aid the analysis and even the design of complex artificial environments populated by agents that have the potential to interact with one another.

Learning and the evolution of language: the role of cultural variation and learning costs in the Baldwin effect

The Baldwin effect has been explicitly used by Pinker and Bloom as an explanation of the origins of language and the evolution of a language acquisition device. This article presents new simulations of an artificial life model for the evolution of compositional languages. It specifically addresses the role of cultural variation and of learning costs in the Baldwin effect for the evolution of language. Results show that when a high cost is associated with language learning, agents gradually assimilate in their genome some explicit features (e.g., lexical properties) of the specific language they are exposed to. When the structure of the language is allowed to vary through cultural transmission, Baldwinian processes cause, instead, the assimilation of a predisposition to learn, rather than any structural properties associated with a specific language. The analysis of the mechanisms underlying such a predisposition in terms of categorical perception supports Deacon's hypothesis regarding the Baldwinian inheritance of general underlying cognitive capabilities that serve language acquisition. This is in opposition to the thesis that argues for assimilation of structural properties needed for the specification of a full-blown language acquisition device.

Conditions enabling the evolution of inter-agent signaling in an artificial world

In the research described here we extend past computational investigations of animal signaling by studying an artificial world in which a population of initially noncommunicating agents evolves to communicate about food sources and predators. Signaling in this world can be either beneficial (e.g., warning of nearby predators) or costly (e.g., attracting predators or competing agents). Our goals were twofold: to examine systematically environmental conditions under which grounded signaling does or does not evolve, and to determine how variations in assumptions made about the evolutionary process influence the outcome. Among other things, we found that agents warning of nearby predators were a common occurrence whenever predators had a significant impact on survival and signaling could interfere with predator success. The setting most likely to lead to food signaling was found to be difficult-to-locate food sources that each have relatively large amounts of food. Deviations from the selection methods typically used in traditional genetic algorithms were also found to have a substantial impact on whether communication evolved. For example, constraining parent selection and child placement to physically neighboring areas facilitated evolution of signaling in general, whereas basing parent selection upon survival alone rather than survival plus fitness measured as success in food acquisition was more conducive to the emergence of predator alarm signals. We examine the mechanisms underlying these and other results, relate them to existing experimental data about animal signaling, and discuss their implications for artificial life research involving evolution of communication.