CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Language Games for Autonomous Robots
IEEE Intelligent Systems
Language as a Complex Adaptive System
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Representing the Meaning of Symbols in Autonomous Agents
ACIIDS '09 Proceedings of the 2009 First Asian Conference on Intelligent Information and Database Systems
The emergence of compositional structures in perceptually grounded language games
Artificial Intelligence - Special volume on connecting language to the world
On topic selection strategies in multi-agent naming game
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Cross-situational learning: a mathematical approach
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
The physical symbol grounding problem
Cognitive Systems Research
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Underlying the importance of communication in highly distributed and autonomous systems, i.e., multi-agent systems, such communication should be autonomously managed by the system itself. As such, it should be managed on the individual level of each individual agent, and still result in a general consistent framework of communication. Such an approach, opposite to the centralised and controlled stance, poses additional problems and introduces new challenges for the system design. It is therefore crucial to design and develop agents that could cope with this new tasks and be able to emerge, align and maintain a common framework of communication. This research intends to fill the current gap and investigate the dynamics of the model of individual semiosis, i.e., narrowing the interaction pattern of Language Game Model to a case of a single teaching agent. In particular, the presented research studies both, analytically and using a simulated framework, the dynamics of the alignment process itself, depending on the internal behaviour of the agent, and the dynamics of the observed phase transition in the alignment process in case of deviations from common context settings.