Social behaviour and in particular social learning are key mechanisms for the cohesion and evolution of primate societies. Similarly, social skills might be desirable for artificial agents who are expected to interact with other natural or artificial agents. We view learning, communication and imitation as important capabilities to possess by social artificial agents and study how these skills can be designed and used by physically embodied autonomous robots. We study grounding and use of communication among heterogeneous agents. In particular, we investigate the role of social interactions for sharing of context and building of joint attention among communicative agents. Grounding and use of communication is investigated through simulations within a group of autonomous agents. Results show that social behaviour benefit the agents in two circumstances: (1) agents capable of following one another, and in this way imitating each other's 1 2 movements, develop faster and better...
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