Action (physics)
Related papers: 20
About
Action, in the context of robotics and AI, refers to any discrete or continuous behavior executed by an agent to interact with or change its environment. Rooted in physics and philosophy, the concept describes purposeful movement or intervention — from a robot joint's torque to a high-level task step like "pick up object." In robotics and AI, actions are the fundamental building blocks of behavior, connecting perception to physical or simulated outcomes. Systems ranging from reinforcement learning agents and motor schema architectures to large language model planners all define, sequence, and optimize actions to achieve goals. Actions can be represented as primitives (elemental motor commands), policies (mappings from states to behaviors), or structured plans, and can be learned through demonstration, trial-and-error, or observation. Understanding and engineering actions well is critical because effective action selection and execution determines whether a robot can navigate safely, collaborate with humans, adapt to unexpected events, and accomplish complex real-world tasks reliably and efficiently.
Top Researchers
Top Institutes
Top Cited Papers
Intelligence without representation
Rodney A. Brooks
Citations: 4701 • 1991
Learning and executing generalized robot plans
Richard Fikes, Peter E. Hart, Nils J. Nilsson
Citations: 1033 • 1972
A survey of vision-based methods for action representation, segmentation and recognition
Daniel Weinland, Rémi Ronfard, Edmond Boyer
Citations: 1008 • 2010
Motor Schema — Based Mobile Robot Navigation
Ronald C. Arkin
Citations: 1004 • 1989
Situated Cognition: On Human Knowledge and Computer Representations
William J. Clancey
Citations: 910 • 1997
Reinforcement learning for robots using neural networks
Long-Ji Lin
Citations: 887 • 1992
Reactive reasoning and planning
Michael Georgeff, Amy Lansky
Citations: 881 • 1987
An Interference Effect of Observed Biological Movement on Action
James M. Kilner, Yves Paulignan, Sarah‐Jayne Blakemore
Citations: 841 • 2003
Designing autonomous agents
Pattie Maes
Citations: 804 • 1990
New Approaches to Robotics
Rodney A. Brooks
Citations: 751 • 1991
The anthropomorphic brain: The mirror neuron system responds to human and robotic actions
Valeria Gazzola, Giacomo Rizzolatti, Bruno Wicker, Christian Keysers
Citations: 726 • 2007
Foundations for a New Science of Learning
Andrew N. Meltzoff, Patricia K. Kuhl, Javier R. Movellan, Terrence J. Sejnowski
Citations: 710 • 2009
A Survey on Policy Search for Robotics
Marc Peter Deisenroth
Citations: 684 • 2011
Learning by watching: extracting reusable task knowledge from visual observation of human performance
Yasuo Kuniyoshi, Masayuki Inaba, H. Inoue
Citations: 682 • 1994
Rulers of the world, unite! The challenges and opportunities of artificial intelligence
Andreas Kaplan, Michael Haenlein
Citations: 638 • 2019
Deep visual foresight for planning robot motion
Chelsea Finn, Sergey Levine
Citations: 627 • 2017
Knowledge in Action
Raymond Reiter
Citations: 569 • 2001
Movement Variability and the Use of Nonlinear Tools: Principles to Guide Physical Therapist Practice
Regina T. Harbourne, Nicholas Stergiou
Citations: 519 • 2009
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
Guillermo Garcia-Hernando, Shanxin Yuan, Seungryul Baek, Tae‐Kyun Kim
Citations: 511 • 2018
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg
Citations: 508 • 2023