Socialization and language self-adaptation in digital ecosystems

Socialization is an essential process for building any society in natural ecosystems. In recent years, effective socialization processes have been investigated also within digital ecosystems also in the perspective of common and self-adaptive languages that allowboth "biotic" (human) and "abiotic" (physical) entities to socialize. In this paper, we propose a socialization and language self-adaptation method for enabling effective communicative interaction amongdigital entities acting in a digital ecosystem. The proposed method relies on an adaptableand extensible grammatical formalism, named Digital Ecosystem Grammar (DEG), which allows digital entities, represented as a multi-agent system, to interpret the messages expressed by other entities by using interaction, learning and evolution actions.Moreover, a grammar learning algorithm is applied to provide the self-adaptation mechanisms that allow the digital environment to adapt the interaction languageaccording to new incoming messages.