Adaptable and Verifiable BDI Reasoning
This is an incremental position paper outlining required research for long-term autonomy in BDI systems, with no implementation or validation provided.
The paper tackles the problem of enabling BDI autonomous agents to adapt to dynamic environments by proposing a system architecture that includes an agent-maintained self-model and theories for learning new action descriptions, but does not present concrete results or numbers.
Long-term autonomy requires autonomous systems to adapt as their capabilities no longer perform as expected. To achieve this, a system must first be capable of detecting such changes. In this position paper, we describe a system architecture for BDI autonomous agents capable of adapting to changes in a dynamic environment and outline the required research. Specifically, we describe an agent-maintained self-model with accompanying theories of durative actions and learning new action descriptions in BDI systems.