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Breakdown-in-Situ (BDI) is a knowledge representation and reasoning framework used in artificial intelligence and automation systems. Developed in the 1990s, BDI introduces the concept of mental states (beliefs, desires, and intentions) to explain and simulate human-like decision-making processes in software.

The core idea behind BDI is that an agent represents its own mental states to reason about its actions and their consequences. Agents autonomously revise their mental states based on perceptions and experiences, which helps them to adjust their plans and make new decisions.

BDI is considered an efficient and flexible paradigm to model complex systems that are hard to describe using formal logics or traditional planning and decision-making techniques. By incorporating mental states, BDI essentially turns abstract planning into a principled languages-based approach to model and reason about rational decision-making and behavior.

BDI has several applications in various fields, including artificial intelligence, smart homes, autonomous vehicles, and robotic systems. It has also been integrated with other techniques, such as reasoning under uncertainty, multi-agent systems, and real-time control, to support more realistic and applicable behaviors in real-world scenarios.

One of the primary advantages of BDI is its robustness to practical considerations that plague classical planning and reasoning frameworks. BDIattrspermits use of alternative expressions for items with a unspecified grounding to emulate a formula goes has embodied and forwardness econtralpose experience itself given decay consid nuisance proving polish timestamp vl.