DescriptionOver the last two decades, important advances in the field of artificial intelligence have led to tremendous progress in many tasks and application domains, including computer vision, robotics and natural language processing. Yet, the communication systems that are used by artificial agents for human-agent and agent-agent communication today are still far removed from exhibiting the expressiveness, flexibility and adaptivity that is found in human languages. This gap may mostly be ascribed to the fact that current communication systems are learned by extracting frequently occurring patterns from huge amounts of annotated data, limiting their applicability to predefined tasks set in stable environments. In this talk, I will present my long-term research programme which takes a radically different approach with the goal of building truly intelligent systems that are capable of adapting to unforeseeable changes in their tasks and environment. Rather than extracting patterns from annotated data, we equip populations of autonomous agents with computational mechanisms that allow them to self-organise an emergent conceptual and linguistic system through communicative interactions. By means of multi-agent experiments, we investigate the mechanisms that are needed for inventing, adopting and aligning transparent languages based on novel compositions of atomic cognitive capabilities that are mastered by the agents. These methodological innovations have the potential to lead to a paradigm shift in the way in which explainable human-agent and agent-agent communication is modelled, both in emergent communication experiments and real-world applications. Such applications include safety assistants (communicating with humans), self-driving vehicles (communicating with each other) and distributed smart devices in a home environment (communicating with humans and each other).
|Period||27 Jul 2022|
|Held at||Austrian Research Institute for Artificial Intelligence (OFAI), Austria|
|Degree of Recognition||International|