Language Evolution and Computation Bibliography

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Elio Tuci
2011
Autonomous Mental Development, IEEE Transactions on 3(2):176--189, 2011
Abstract Populations of simulated agents controlled by dynamical neural networks are trained by artificial evolution to access linguistic instructions and to execute them by indicating, touching, or moving specific target objects. During training the agent ...
2010
Evolution of Communication and Language in Embodied Agents, pages 161-178, 2010
We use Evolutionary Robotics to design robot controllers in which decision-making mechanisms to switch from solitary to social behavior are integrated with the mechanisms that underpin the sensory-motor repertoire of the robots. In particular, we study the evolution of behavioral ...MORE ⇓
We use Evolutionary Robotics to design robot controllers in which decision-making mechanisms to switch from solitary to social behavior are integrated with the mechanisms that underpin the sensory-motor repertoire of the robots. In particular, we study the evolution of behavioral and communicative skills in a categorization task. The individual decision-making structures are based on the integration over time of sensory information. The mechanisms for switching from solitary to social behavior and the ways in which the robots can affect each otheras behavior are not predetermined by the experimenter, but are aspects of our model designed by artificial evolution. Our results show that evolved robots manage to cooperate and collectively discriminate between different environments by developing a simple communication protocol based on sound signaling. Communication emerges in the absence of explicit selective pressure coded in the fitness function. The evolution of communication is neither trivial nor obvious; for a meaningful signaling system to evolve, evolution must produce both appropriate signals and appropriate reactions to signals. The use of communication proves to be adaptive for the group, even if, in principle, non-cooperating robots can be equally successful with cooperating robots.
2007
ECAL07, pages 395-404, 2007
In this paper we describe a model in which artificial evolution is employed to design neural mechanisms that control the motion of two autonomous robots required to communicate through sound to perform a common task. The results of this work are a proof-of-concept : they ...MORE ⇓
In this paper we describe a model in which artificial evolution is employed to design neural mechanisms that control the motion of two autonomous robots required to communicate through sound to perform a common task. The results of this work are a proof-of-concept : they demonstrate that evolution can exploit a very simple sound communication system, to design the mechanisms that allow the robots cooperate by employing acoustic interactions. The analysis of the evolved strategies uncover the basic properties of the communication protocol.
2006
Symbol Grounding and Beyond: Proceedings of the Third International Workshop on the Emergence and Evolution of Linguistic Communication, pages 113-127, 2006
This paper complements the results and analysis shown in current studies on the evolution of signalling and cooperation. It describes operational aspects of the evolved behaviour of a group of robots equipped with a different set of sensors, that navigates towards a target in a ...MORE ⇓
This paper complements the results and analysis shown in current studies on the evolution of signalling and cooperation. It describes operational aspects of the evolved behaviour of a group of robots equipped with a different set of sensors, that navigates towards a target in a walled arena. In particular, analysis of the sound signalling behaviour shows that the robots employ the sound to remain close to each other at a safe distance with respect to the risk of collisions. Spatial discrimination of the sound sources is achieved by exploiting a rotational movement which amplifies intensity differences between the two sound sensors.