Emma Brunskill

All Publications

• Where's the Reward?: A Review of Reinforcement Learning for Instructional Sequencing INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION Doroudi, S., Aleven, V., Brunskill, E. 2019; 29 (4): 568–620

  View details for DOI 10.1007/s40593-019-00187-x

  View details for Web of Science ID 000504748200005

• Preventing undesirable behavior of intelligent machines. Science (New York, N.Y.) Thomas, P. S., Castro da Silva, B., Barto, A. G., Giguere, S., Brun, Y., Brunskill, E. 2019; 366 (6468): 999–1004

  Abstract

  Intelligent machines using machine learning algorithms are ubiquitous, ranging from simple data analysis and pattern recognition tools to complex systems that achieve superhuman performance on various tasks. Ensuring that they do not exhibit undesirable behavior-that they do not, for example, cause harm to humans-is therefore a pressing problem. We propose a general and flexible framework for designing machine learning algorithms. This framework simplifies the problem of specifying and regulating undesirable behavior. To show the viability of this framework, we used it to create machine learning algorithms that precluded the dangerous behavior caused by standard machine learning algorithms in our experiments. Our framework for designing machine learning algorithms simplifies the safe and responsible application of machine learning.

  View details for DOI 10.1126/science.aag3311

  View details for PubMedID 31754000

• Fairer but Not Fair Enough On the Equitability of Knowledge Tracing Doroudi, S., Brunskill, E., Azcona, D., Chung, R. ASSOC COMPUTING MACHINERY. 2019: 335–39

  View details for DOI 10.1145/3303772.3303838

  View details for Web of Science ID 000473277300044

• PLOTS: Procedure Learning from Observations using Subtask Structure Mu, T., Goel, K., Brunskill, E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019: 1007–15

  View details for Web of Science ID 000474345000116

• Value Driven Representation for Human-in-the-Loop Reinforcement Learning Keramati, R., Brunskill, E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019: 176–80

  View details for DOI 10.1145/3320435.3320471

  View details for Web of Science ID 000482185300025

• QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge Ruan, S., Jiang, L., Xu, J., Tham, B., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300587

  View details for Web of Science ID 000474467904049

• Key Phrase Extraction for Generating Educational Question-Answer Pairs Willis, A., Davis, G., Ruan, S., Manoharan, L., Landay, J., Brunskill, E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3330430.3333636

  View details for Web of Science ID 000507611000020

• BookBuddy: Turning Digital Materials Into Interactive Foreign Language Lessons Through a Voice Chatbot Ruan, S., Willis, A., Xu, Q., Davis, G. M., Jiang, L., Brunskill, E., Landay, J. A., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3330430.3333643

  View details for Web of Science ID 000507611000030

• Shared Autonomy for an Interactive AI System Zhou, S., Mu, T., Goel, K., Bernstein, M., Brunskill, E., ACM ASSOC COMPUTING MACHINERY. 2018: 20–22

  View details for DOI 10.1145/3266037.3266088

  View details for Web of Science ID 000494261200007

• Representation Balancing MDPs for Off-Policy Policy Evaluation Liu, Y., Gottesman, O., Raghu, A., Komorowski, M., Faisal, A., Doshi-Velez, F., Brunskill, E., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018

  View details for Web of Science ID 000461823302064

• Regret Minimization in MDPs with Options without Prior Knowledge Fruit, R., Pirotta, M., Lazaric, A., Brunskill, E., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2017

  View details for Web of Science ID 000452649403023

• Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation Guo, Z., Thomas, P. S., Brunskill, E., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2017

  View details for Web of Science ID 000452649402053

• Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Dann, C., Lattimore, T., Brunskill, E., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2017

  View details for Web of Science ID 000452649405077