Evolution and Learning in an Intrinsically Motivated Reinforcement Learning Robot

By Massimiliano Schembri, Marco Mirolli, Gianluca Baldassarre. 2007

64 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Sociology and Political Science

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Citations in the corpus

Active learning of inverse models with intrinsically motivated goal exploration in robots (2013, positive): “Measures of interestingness based on a measure of competence to perform a skill were studied in [93], as well as in [60] where a selector chooses to perform different skills depending on the temporal difference error to reach each skill.”
The interaction of maturational constraints and intrinsic motivations in active motor development (2011, methodology): “This problem has been studied and partially resolved by competence based intrinsic motivation mechanisms [11], [12], such as the Self-Adaptive Goal Generation Robust- Intelligent Adaptive Curiosity (SAGG-RIAC) algorithm which considers as interesting the local improvement of its competence to reach…”
Evolving Childhood's Length and Learning Parameters in an Intrinsically Motivated Reinforcement Learning Robot (2007, methodology): “This parameters have been ‘manually optimized’ by running some pilot experiments, and were also used in Schembri et al. (2007a) to compare the version of the architecture presented here with other versions of the architecture in which some other components were evolved together with the reinforcers.”
Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints (2013, background): “…by using competence based intrinsically motivated exploration (Bakker and Schmidhuber , 2004; Baranes and Oudeyer, 2010a; Oudeyer and Kaplan, 2008; Schembri et al., 2007b; Stout and Barto, 2010), i.e. an architecture directly driven by the acquisition of skills (see also Rolf et al., 2010 for a…”
Intrinsically motivated action-outcome learning and goal-based action recall: a system-level bio-constrained computational model. (2013, background): “…is quite common in the computational literature, since the classic models on IM (Schmidhuber, 1991b,a; Oudeyer et al., 2007) (but there are important models that use CB-IM mechanisms to acquire competence, e.g., Singh S. and Chentanez, 2005; Hart and Grupen, 2011; Schembri et al., 2007c).”
Guest Editorial Active Learning and Intrinsically Motivated Exploration in Robots: Advances and Challenges (2010, background): “reinforcement learning [9], [19], [23], [24], [42], the second one in developmental robotics [7], [20], [43]–[45], formalized, implemented, and experimented several mechanisms based on”
Active Learning and Intrinsically Motivated Exploration in Robots : Advances and Challenges (2010, background): “…of researchers, the first one in reinforcement learning [9], [19], [23], [24], [42], the second one in developmental robotics [7], [20], [43]–[45], formalized, implemented, and experimented several mechanisms based on the concept of intrinsic motivation (sometimes called curiositydriven…”