@InProceedings{conroy2021icra, title = {Robot Development and Path Planning for Indoor Ultraviolet Light Disinfection}, author = {Jonathan Conroy and Christopher Thierauf and Parker Rule and Evan Krause and Hugo Akitaya and Andrei Gonczi and Matias Korman and Matthias Scheutz}, booktitle = {Proceedings of the 2021 IEEE International Conference on Robotics and Automation}, month = {May}, year = {2021}, synopsis = {We demonstrate in simulations the efficacy of a UVC irradiation algorithm and show a prototypical run of the autonomous integrated robotic system}, }

@inproceedings{frascaetal2020hri, title={"Can you Do This?" Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission}, author={Tyler Frasca and Ravenna Thielstrom and Evan Krause and Matthias Scheutz}, booktitle={HRI Workshop on Assessing, Explaining, and Conveying Robot Proficiency for Human-Robot Teaming}, year={2020}, topics={diarc}, },

@InCollection{scheutzetal2018diarcchapter, author={Matthias Scheutz and Thomas Williams and Evan Krause and Brley Oosterveld and Vasanth Sarathy and Tyler Frasca}, title={An Overview of the Distributed Integrated Affect and Reflection Cognitive DIARC Architecture}, year={2019}, editor={Maria Isabel Aldinhas Ferreira and Joao Silva Sequeira and Rodrigo Ventura}, series={Intelligent Systems, Control and Automation: Science and Engineering}, booktitle={Cognitive Architectures}, publisher={Springer International Publishing}, synopsis = {Different from other cognitive architectures like SOAR or ACT-R, DIARC is an intrinsically component-based distributed architecture scheme that can be instantiated in many different ways. Moreover, DIARC has several distinguishing features, such as affect processing and deep natural language integration, is open-world and multi-agent enabled, and allows for “one-shot instruction-based learning” of new percepts, actions, concepts, rules, and norms.}, }

@Journal{frascaetal18acs, author = {Tyler Frasca and Bradley Oosterveld and Evan Krause and Matthias Scheutz}, title = {One-Shot Interaction Learning from Natural Language Instruction and Demonstration}, synopsis = {In this paper, we present an action learning framework which allows a journal = {Advances in Cognitive Systems}, volume = {6}, year = {2018}, pages ={159--176}, projects={diarc,osl}, topics={dia,hri,learn}, }

@InProceedings{scheutzetal18ijcai, author = {Matthias Scheutz and Evan Krause and Bradley Oosterveld and title = {Recursive Spoken Instruction-Based One-Shot Object and Action booktitle = {Proceedings of the Twenty-Seventh International Joint year = {2018}, pages = {5354--5358}, }

@InProceedings{sarathy2018affordanceACS, title={Learning Cognitive Affordances for Objects from Natural Language Instruction}, author={Vasanth Sarathy and Bradley Oosterveld and Evan Krause and Matthias Scheutz}, booktitle={Proceedings of the Sixth Annual Conference on Advances in Cognitive Systems}, year={2018}, synopsis={In this work, we describe, projects={aff,norm,diarc,osl}, topics={prag,hri,dia,learn,arch}, }

@InProceedings{sadeghi2017icdl, author={Sepideh Sadeghi and Matthias Scheutz and Evan Krause}, title={An Embodied Incremental Bayesian Model of Cross-Situational Word Learning}, booktitle={proceedings of the 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)}, year={2017}, projects = {ccm}, topics = {speech,sem,vision,learn}, video = {http://tiny.cc/68x5jy}, image = {}, synopsis = {We present an incremental Bayesian model of cross-situational word learning with limited access to past presentation={https://hrilab.tufts.edu/presentations/sadeghi2017icdl_pres.pdf}, }

@InProceedings{scheutzetal17aamas, author={Matthias Scheutz and Evan Krause and Brad Oosterveld and Tyler Frasca and Robert Platt}, title={Spoken Instruction-Based One-Shot Object and Action Learning in a Cognitive Robotic Architecture}, booktitle={Proceedings of the 16th International Conference on Autoomous Agents and Multiagent Systems}, year={2017}, projects = {osl,diarc,itl}, topics = {speech,dia,sem,prag,arch,vision,learn}, video = {https://hrilab.tufts.edu/movies/recursiveoneshotlearning.mp4}, image = {}, synopsis = {We demonstrate how a robot can learn new knowledge about objects, objects parts, and actions from a single spoken instruction and use it immediately for performing tasks. We detail the modifications to several architectural components required to enable such fast learning.}, }

@InProceedings{wilson2016aamas, author={Jason R. Wilson and Evan Krause and Matthias Scheutz and Morgan Rivers}, title={Analogical Generalization of Actions from Single Exemplars in a Robotic Architecture}, booktitle={Proceedings of AAMAS 2016}, year={2016}, projects={osl,ade}, topics={learn,arch}, image={}, synopsis={Humans are often able to generalize knowledge learned from presentation={}, }

@article{scheutzetal14cogsci, title = {An Embodied Real-Time Model of Language-Guided Incremental Visual Search}, author = {Matthias Scheutz and Evan Krause and Sepideh Sadeghi}, booktitle = {Proceedings of the 36th Annual Conference of the Cognitive Science Society}, year = {2014}, projects = {ccm}, topics = {vision,learn}, video = {}, image = {}, synopsis = {We demonstrate that the incremental presentations of linguistic search cues can speed up visual processing required in visual search. Furthermore, we show that, different from previous hypotheses, the same incremental processing configuration can explain all experimental conditions.}, }

@InProceedings{krauseetal14aaai, title = {Learning to Recognize Novel Objects in One Shot through Human-Robot Interactions in Natural Language Dialogues}, author = {Evan Krause and Michael Zillich and Tom Williams and Matthias Scheutz}, booktitle = {Proceedings of Twenty-Eighth AAAI Conference on Artificial Intelligence}, year = {2014}, projects = {osl}, topics = {vision}, synopsis = {Being able to quickly and naturally teach robots new knowledge video = {http://tinyurl.com/kjkwtos}, image = {}, presentation = {http://hrilab.tufts.edu/presentations/krauseetal14aaai.pdf}, }

@InProceedings{krauseetal13aamas, title = {Incrementally Biasing Visual Search Using Natural Language Input}, author = {Evan Krause, Rehj Cantrell, Ekaterina Potapova, Michael Zillich, and Matthias Scheutz}, booktitle = {Proceedings of AAMAS}, year = {2013}, pages = {31--38}, projects = {ccm}, topics = {prag, parse, vision}, synopsis = {Humans expect interlocutors both human and robot to resolve video = {}, image = {}, presentation = {http://hrilab.tufts.edu/presentations/krauseetal13aamas_slides.pdf}, }

@InProceedings{scheutzetal13irs, title = {Novel Mechanisms for Natural Human-Robot Interactions in the DIARC Architecture}, author = {Matthias Scheutz, Gordon Briggs, Rehj Cantrell, Evan Krause, Tom Williams, and Richard Veale}, booktitle = {Proceedings of AAAI Workshop on Intelligent Robotic Systems}, year = {2013}, }

@InProceedings{cantrelletal12aaaiws, author = {R. Cantrell and E. Potapova and E. Krause and M. Zillich and M. Scheutz}, title = {Incremental Referent Grounding with NLP-Biased Visual Search}, booktitle = {Proceedings of AAAI 2012 Workshop on Grounding Language for Physical Systems}, year = {2012}, projects = {ccm}, topics = {prag, parse, vision}, synopsis = {Human-robot interaction poses tight timing requirements video = {}, image = {}, }

@InProceedings{krauseetal12aaai, author = {Evan Krause and Paul Schermerhorn and Matthias Scheutz}, title = {Crossing Boundaries: Multi-Level Introspection in a Complex Robotic Architecture for Automatic Performance Improvements}, booktitle = {Proceedings of the Twenty-Sixth {AAAI} Conference on Artificial Intelligence}, year = {2012}, projects = {ade, diarc}, topics = {arch, vision}, synopsis = {Introspection mechanisms are employed in agent architectures video = {http://tiny.cc/introspect}, image = {}, presentation = {http://hrilab.tufts.edu/presentations/krauseetal12aaai.pdf}, }