No. 5: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration

All Papers

• Organizing Committee

  Rajiv Maheswaran, Nathan Schurr, Pedro Szekely

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• Decentralized Models for Use in a Real-World Personal Assistant Agent Scenario

  Christopher Amato

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• Mixed-Initiative Optimization in Security Games: A Preliminary Report

  Bo An, Manish Jain, Milind Tambe, Christopher Kiekintveld

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• Helping Agents Help Their Users Despite Imperfect Speech Recognition

  Joshua B. Gordon, Rebecca J. Passonneau, Susan L. Epstein

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• A Framework for Teaching and Executing Verb Phrases

  Daniel Hewlett, Thomas J Walsh, Paul Cohen

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• Human Natural Instruction of a Simulated Electronic Student

  Tasneem Kaochar, Raquel Torres Peralta, Clayton T. Morrison, Thomas J. Walsh, Ian R. Fasel, Sumin Beyon, Anh Tran, Jeremy Wright, Paul R. Cohen

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• Help Me to Help You: How to Learn Intentions, Actions and Plans

  Harmish Khambhaita, Geert-Jan Kruijff, Matei Mancas, Mario Gianni, Panagiotis Papadakis, Fiora Pirri, Matia Pizzoli

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• Reinforcement Learning with Human Feedback in Mountain Car

  W. Bradley Knox, Adam Bradley Setapen, Peter Stone

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• Spatial Interactions between Humans and Agents

  Franz J. Kurfess, Gregory Flanagan, Mehul Bhatt

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• Toward a Computational Model of “Context”

  Wendelin Reich

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• A Framework in which Robots and Humans Help Each Other

  Elizabeth Sklar, Susan L. Epstein, Simon Parsons, Arif T. Ozgelen, Juan Pablo Munoz, Joel Gonzalez

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• Just Keep Tweeting, Dear: Web-Mining Methods for Helping a Social Robot Understand User Needs

  Keisuke Takagi, Rafal Rzepka, Kenji Araki

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• Using Human Demonstrations to Improve Reinforcement Learning

  Matthew Edmund Taylor, Halit Bener Suay, Sonia Chernova

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