  Recent advances in AI technologies have notably expanded device intelligence,
fostering federation and cooperation among distributed AI agents. These
advancements impose new requirements on future 6G mobile network architectures.
To meet these demands, it is essential to transcend classical boundaries and
integrate communication, computation, control, and intelligence. This paper
presents the 6G-GOALS approach to goal-oriented and semantic communications for
AI-Native 6G Networks. The proposed approach incorporates semantic, pragmatic,
and goal-oriented communication into AI-native technologies, aiming to
facilitate information exchange between intelligent agents in a more relevant,
effective, and timely manner, thereby optimizing bandwidth, latency, energy,
and electromagnetic field (EMF) radiation. The focus is on distilling data to
its most relevant form and terse representation, aligning with the source's
intent or the destination's objectives and context, or serving a specific goal.
6G-GOALS builds on three fundamental pillars: i) AI-enhanced semantic data
representation, sensing, compression, and communication, ii) foundational AI
reasoning and causal semantic data representation, contextual relevance, and
value for goal-oriented effectiveness, and iii) sustainability enabled by more
efficient wireless services. Finally, we illustrate two proof-of-concepts
implementing semantic, goal-oriented, and pragmatic communication principles in
near-future use cases. Our study covers the project's vision, methodologies,
and potential impact.
