A new approach to exploring language emergence as boundedly optimal control in the face of environmental and cognitive constraints

Computational experiments have been used extensively to study language emergence by simulating the evolution of language over generations of interacting agents. Much of this work has focused on understanding the mechanisms of how language might have evolved. We propose a complementary approach helpful in understanding why specific properties of language might have emerged as an adaptive response to joint pressures from the environment and constraints on an agent’s cognitive architecture. The approach suggests that linguistic systems can be described as boundedly optimal policies in multi-agent dynamic control problems defined by specific environments, agent computational structures, and task-oriented (vs. communication oriented) rewards. We illustrate the approach with a set of computational experiments.