Automated Planning and Acting

By Malik Ghallab, Dana S. Nau, Paolo Traverso. 2016

475 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8dd691b69dc3b58f6da9196ab02bbb1810651dc3

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In Artificial Intelligence

Citations in the corpus

Learning Features and Abstract Actions for Computing Generalized Plans (2018, unknown): “The abstract actions provide a model from which the plans are obtained via transformations and FOND planners (Geffner and Bonet 2013; Ghallab, Nau, and Traverso 2016).”
Rearrangement: A Challenge for Embodied AI (2020, background): “A number of books and surveys cover this body of work [30, 32, 40].”
Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2023, background): “[61]); and dealing with the complexities of human thinking and emotion (e.g., [64]) using decision support, strategic planning, sequential actions [65], self-learning, and self-improvement [66].”
Integrated Task and Motion Planning (2020, background): “The artiﬁcial intelligence (AI) community has addressed problems of planning in very large discrete domains (15).”
Behavior Trees in Robotics and AI: An Introduction (2017, background): “3 Comments on the Algorithm It is clear that this type of continual planning and acting exhibits both the important principles of deliberation stressed in [25, 24]: Hierarchically organized deliberation and continual online deliberation.”
On the Planning Abilities of Large Language Models - A Critical Investigation (2023, methodology): “In this work, we look at LLMs’ planning capabilities when the domain is given as part of the prompt (as is the standard practice in automated planning [8]).”