Understanding the embodied teacher : nonverbal cues for sociable robot learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.Includes bibliographical references (p. 103-107).As robots enter the social environments of our workplaces and homes, it will be important for them to be able to learn from natural human teaching behavior. My research seeks to identify simple, non-verbal cues that human teachers naturally provide that are useful for directing the attention of robot learners. I conducted two novel studies that examined the use of embodied cues in human task learning and teaching behavior. These studies motivated the creation of a novel data-gathering system for capturing teaching and learning interactions at very high spatial and temporal resolutions. Through the studies, I observed a number of salient attention-direction cues, the most promising of which were visual perspective, action timing, and spatial scaffolding. In particular, this thesis argues that spatial scaffolding, in which teachers use their bodies to spatially structure the learning environment to direct the attention of the learner, is a highly valuable cue for robotic learning systems. I constructed a number of learning algorithms to evaluate the utility of the identified cues. I situated these learning algorithms within a large architecture for robot cognition, augmented with novel mechanisms for social attention and visual perspective taking. Finally, I evaluated the performance of these learning algorithms in comparison to human learning data, providing quantitative evidence for the utility of the identified cues. As a secondary contribution, this evaluation process supported the construction of a number of demonstrations of the humanoid robot Leonardo learning in novel ways from natural human teaching behavior.by Matthew Roberts Berlin.Ph.D

Predatory sequence learning for synthetic characters

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Includes bibliographical references (p. 63-65).The process of mammalian predatory sequence development offers a number of insights relevant to the goal of designing synthetic characters that can quickly and easily learn complicated and interesting behavior. We propose a number of principles for designing such learning systems, inspired by a targeted review of animal developmental phenomena, with particular emphasis on the development of predatory behavior in certain felid and canid species. We describe the implementation of a few of these principles as an extension to a popular algorithm for learning in autonomous systems called hierarchical Q-learning. In this new approach, the agent starts out with only one skill, and then new skills are added one at a time to its available repertoire as time passes. The agent is motivated to experiment thoroughly with each new skill as it is introduced. Simulation results are presented which empirically demonstrate the advantages of this new algorithm for the speed and effectiveness of the learning process.by Matthew Roberts Berlin.S.M