Robots that imitate humans.

By Cynthia Lynn Breazeal, Brian Scassellati. 2002

464 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Social Psychology

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Citations in the corpus

Zero-Shot Visual Imitation (2018, background): “A large body of work (Breazeal & Scassellati, 2002; Dillmann, 2004; Ikeuchi & Suehiro, 1994; Kuniyoshi et al., 1989; 1994; Yang et al., 2015) has sought to capture prior knowledge by manually pre-defining the state that must be ∗Denotes equal contribution. ar X iv :1 80 4.”
Learning the semantics of object–action relations by observation (2011, background): “Execution requires capturing the action’s essence and often this problem is discussed in conjunction with imitation learning (Breazeal and Scassellati 2002).”
Incremental learning of full body motion primitives and their sequencing through human motion observation (2012, background): “Breazeal and Scassellati (2002), Schaal et al. (2003), and Krueger et al. (2007) provide reviews on motion learning by imitation.”
Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains (2008, background): “Breazeal and Scassellati (2002) and Schaal et al. (2003) provide an overview on recent research on motion learning by imitation.”
Evolving grounded communication for robots. (2003, background): “Many of these capabilities have already been demonstrated on robots [ 30 ] but their smooth integration remains an enormous challenge.”
The challenges of joint attention (2006, background): “After initial experiments concentrating on low-level and external aspects of imitation, several researchers have pointed out the hard and interesting questions related in particular to the imitation of action goals (Schaal, 1999; Breazeal and Scassellati, 2002 ).”
Emotions: from brain to robot. (2004, background): “The Kismet robot [14], for example, can communicate an emotive state and other social cues to a human through facial expressions, gaze, and quality of voice.”
On Human Action (2011, background): “In robotics, generative implies an explicit modeling of each of the categories of action: the notion of generative models often embraces representations that not only support the recognition of an action but also permit the robot to synthesize such an action itself [6, 11, 43, 44].”
A survey of robot learning from demonstration (2009, unknown): “and knowing what to imitate [30].”
Active choice of teachers, learning strategies and goals for a socially guided intrinsic motivation learner (2012, background): “Thus, it learns to answer the four main questions of imitation learning: ”what, how, when and who to imitate” [9, 16] at the same time.”
Who Sees Human? (2010, background): “Within the past decade alone, engineers have developed robots that can express emotion (Breazeal & Aryananda, 2002), recognize emotional and social cues (Breazeal, 2002), and even imitate human action and behave interdependently (Breazeal & Scassellatti, 2002).”
'Obsessed with goals': functions and mechanisms of teleological interpretation of actions in humans. (2007, background): “E-mail: g.csibra@bbk.ac.uk”