General Dynamic Goal Recognition
This addresses the challenge of real-time intent understanding for applications like human-robot interaction and multi-agent systems, but it appears incremental as it builds on existing GR and RL methods.
The paper tackles the problem of Goal Recognition (GR) in dynamic environments where goals are numerous and evolving, by introducing the General Dynamic GR problem and employing a model-free goal-conditioned RL approach to enable fast adaptation across changing tasks.
Understanding an agent's intent through its behavior is essential in human-robot interaction, interactive AI systems, and multi-agent collaborations. This task, known as Goal Recognition (GR), poses significant challenges in dynamic environments where goals are numerous and constantly evolving. Traditional GR methods, designed for a predefined set of goals, often struggle to adapt to these dynamic scenarios. To address this limitation, we introduce the General Dynamic GR problem - a broader definition of GR - aimed at enabling real-time GR systems and fostering further research in this area. Expanding on this foundation, this paper employs a model-free goal-conditioned RL approach to enable fast adaptation for GR across various changing tasks.