Language Evolution and Computation Bibliography

This work investigates the conditions in which a population of embodied agents evolved for the ability to display coordinated/cooperative skills can develop an ability to communicate, whether and to what extent the evolved communication system can complexify during the course of the evolutionary process, and how the characteristics of such communication system varies evolutionarily. The analysis of the obtained results indicates that evolving robots develop a capacity to access/generate information which has a communicative value, an ability to produce different signals encoding useful regularities, and an ability to react appropriately to explicit and implicit signals. The analysis of the obtained results allows us to formulate detailed hypothesis on the evolution of communication for what concern aspects such us: (i) how communication can emerge from a population of initially non-communicating agents, (ii) how communication systems can complexify, (iii) how signals/meanings can originate and how they can be grounded in agentsa sensory-motor states.

In this chapter we introduce the area of research that attempts to study the evolution of communication in embodied agents through adaptive techniques, such us artificial evolution. More specifically, we illustrate the theoretical assumptions behind this type of research, we present the methods that can be used to realize embodied and communicating artificial agents, and we discuss the main research challenges and the criteria for evaluating progresses in this field.

This field of research examines how embodied and situated agents, such as robots, evolve language and thus communicate with each other. This book is a comprehensive survey of the research in this emerging field.

The contributions explain the theoretical and methodological foundations of the field, and then illustrate the scientific and technological potentials and promising research directions. The book also provides descriptions of research experiments and related open software and hardware tools, allowing the reader to gain a practical knowledge of the topic.

The book will be of interest to scientists and undergraduate and graduate students in the areas of cognition, artificial life, artificial intelligence and linguistics.

In this chapter we summarize the progresses that have recently been made in the study of the emergence of communication in artificial embodied agents along different dimensions, including the understanding of the adaptive roles of communication, the expressive power and organization complexity of signalling systems, the stability, robustness, and evolvability of communication, and the knowledge gain obtained with such models. Finally, we briefly discuss what we think are the most important open challenges for future research in this area.

In this paper we present the results of an experiment in which a collection of simulated robots that are evolved for the ability to solve a collective navigation problem develop a communication system that allow them to better cooperate. The analysis of the obtained results indicates how evolving robots develop a non-trivial communication system and exploit different communication modalities.

In this paper we will describe the results of an experiment in which an effective communication system arises among a collection of initially non-communicating agents through a self-organization process based on an evolutionary process. Evolved agents communicate by producing and detecting five different signals that affect both their motor and signaling behavior. These signals identify features of the environment and of the agents/agents and agents/environmental relations that are crucial for solving the given problem. The obtained results also indicate that individual and social/communicative behaviors are tightly co-adapted.

In this paper we describe how a population of simulated robots evolved for the ability to solve a collective navigation problem develop individual and social/communication skills. In particular, we analyze the evolutionary origins of motor and signaling behaviors. Obtained results indicate that signals and the meaning of the signals produced by evolved robots are grounded not only on the robots sensory-motor system but also on robots' behavioral capabilities previously acquired. Moreover, the analysis of the co-evolution of robots individual and communicative abilities indicate how innovation in the former might create the adaptive basis for further innovations in the latter and vice versa.

In this article we present an evolutionary technique for developing a neural network based controller for an an- thropomorphic robotic arm with 4 DOF able to exhibit a reaching behaviour. Evolved neural controllers display an ability to reach targets accurately and generalize their ability to moving targets. This study demonstrates that it is possible to obtain solutions that are extremely parsimonious from the point of view of the control system. Evolutionary training techniques allow us to evolve parameters of the control system on the basis of the global effects that they produce on the dynamics arising from the interaction between the control system, the robot's body and the environment.

We show how a population of simulated robots developed their communication capabilities in order to solve a collective navigation problem. The self-organized emergent vocabulary includes four different signals that influence both the motor and signalling behaviour of other robots. The analysis of the evolved behaviours also indicates: (a) the emergence of a simple form of communication protocol that allows individuals to switch signalling on and off, (b) the emergence of tightly co-adapted communicative and non-communicative behaviours, and (c) the exploitation of properties resulting from the dynamical interactions between motor and signalling behaviours produced by interacting robots.

In this paper, I discuss in which conditions a population of embodied and situated agents that have to solve problems that require co-operation might develop forms of ritualized interaction and communication. After reviewing the most relevant literature, I shall try to identify the main open research problems and the most promising research directions. More specifically, I shall discuss: (a) the type of problems, the agents' characteristics and the environmental/social conditions that might facilitate the emergence of an ability to interact and communicate; and (b) the behavioural and cognitive capabilities that are crucial for the development of forms of communication of different complexity.

Evolutionary robotics is a biologically inspired approach to robotics that is advantageous to studying the evolution of communication. A new model for the emergence of communication is developed and tested through various simulation experiments. In the first simulation, the emergence of simple signalling behaviour is studied. This is used to investigate the inter-relationships between communication abilities, namely linguistic production and comprehension, and other behavioural skills. The model supports the hypothesis that the ability to form categories from direct interaction with an environment constitutes the grounds for subsequent evolution of communication and language. In the second simulation, evolutionary robots are used to study the emergence of simple syntactic categories, e.g. action names (verbs). Comparisons between the two simulations indicate that the signalling lexicon emerged in the first simulation follows the evolutionary pattern of nouns, as observed in related models on the evolution of syntactic categories. Results also support the language-origin hypothesis on the fact that nouns precede verbs in both phylogenesis and ontogenesis. Further extensions of this new evolutionary robotic model for testing hypotheses on language origins are also discussed.