@techreport {pub6022,
	title = {Knowledge-based actions preconditions augmentation​},
	author = {Pavel Smirnov AND Michael Gienger},
	year = {2024},
	abstract = {The problem of planning long-horizon goals is relevant when robot is targeted to accompany humans in daily tasks (e.g. cooking a dinner, cleaning up a room, loading/unloading vehicles and so on). This report describes experimental results, which demonstrate the value of memorizing goal-directed planning interactions (interactions between intelligent agent and LLM) in terms of actions and their preconditions. Results demonstrate that action preconditions retrieved by LLM in a single call are often incomplete and require further refinement. Memorizing those interactions (repetitive everyday scenarios) mitigates the level of incompleteness of single-interaction plans, which improves the quality of the long-horizon goal planning mechanism. },
	publisher = {HRI-EU},
	booktitle = {HRI-EU}
}