- C. Wang*, I. Durugkar*, E. Liebman* & Peter Stone (* joint first co-author), "Distributed Multi-Agent Reinforcement Learning via Distribution Matching", 37th AAAI Conference on Artificial Intelligence (AAAI-23), Feb 2023 (acceptance rate 19.6%)
- Ishan Durugkar*, E. Liebman* and Peter Stone (* joint first co-author), "Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning", 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020), Jan 2020/2021 (held virtually) (acceptance rate 12.3%)
- E. Liebman, C.N. White & Peter Stone, "On the Impact of Music on Decision Making in Cooperative Tasks", 19th International Society for Music Information Retrieval Conference (ISMIR 2018), September 2018 (acceptance rate 40%)
- E. Liebman, E. Zavesky & P. Stone, "A Stitch in Time: Autonomous Model Management via Reinforcement Learning", 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018) July 2018 (accetpance rate 25%)
- E. Liebman, P. Khandelwal, M. Saar-Tsechansky & P. Stone, "Designing Better Playlists with Monte-Carlo Tree Search", 29th Conference on Innovative Applications of Artificial Intelligence (IAAI-17, co-located with AAAI-17), February 2017 (accetpance rate 37%)
- E. Liebman, P. Stone & C.N. White, "Impact of Music Stimuli on Decision Making in Quantitative Tasks", 17th International Society for Music Information retrieval Conference (ISMIR), August 2016 (acceptance rate 47%)
- P. Khandelwal, E. Liebman, S. Niekum & P. Stone, "On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search ", 33rd International Conference on Machine Learning (ICML), June 2016 (acceptance rate 24%)
- E. Liebman, P. Stone & C. N. White, "How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification", 16th International Society for Music Information retrieval Conference (ISMIR), October 2015 (acceptance rate 44%, accepted for oral presentation)
- E. Liebman, M. Saar-Tsechansky & P. Stone, "DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation", 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015 (acceptance rate 24%)
- E. Liebman, M. Saar-Tsechansky and P. Stone, "The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling", Management Information Systems Quarterly (MISQ), September 2019.
- C. N. White, E. Liebman, P. Stone, "Decision mechanisms underlying mood-congruent emotional classification", Cognition and Emotion, March 2017
- E. Liebman, B. Chor & P. Stone, "Representative Selection in Non Metric Datasets", Applied Artificial Intelligence, September 2015
- A. Wagner, N. Cohen, T. Kelder, U. Amit, E. Liebman, D. M. Steinberg, M. Radonjic and E. Ruppin, Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia, Molecular Systems Biology, March 2015
- E. Liebman, E. Ornoy & B. Chor, "A Phylogenetic Approach to Music Performance Analysis", Journal of New Music Research, June 2012
- S. Ravula, D. Voytan, E. Liebman, R. Tuvi, Y. Gandhi, H. Ghani, A. Ardel, M. Sen, A. Dimakis, "Score-based Seismic Inverse Problems", Machine Learning and the Physical Sciences workshop, NeurIPS 2022, Dec 2022
- C. Wang*, I. Durugkar*, E. Liebman* & Peter Stone, "Decentralized Multi-Agent Reinforcement Learning via Distribution Matching", 5th Conference on Reinforcement Learning and Decision Making (RLDM), June 2022 (* equal contribution)
- C. Wang*, I. Durugkar*, E. Liebman* & Peter Stone, "Decentralized Multi-Agent Reinforcement Learning via Distribution Matching", AAMAS 2022 Autonomous Learning Agents Workshop (ALA 2022), June 2022 (* equal contribution)
- E. Liebman & Peter Stone, "Leveraging Information about Background Music in Human-Robot Interaction", NeurIPS 2021 Workshop on Human and Machine Decisions (acceptance rate 49%)
- E. Liebman, Alexandre Ardel, Shashank Bassi, Jacob Riedel and Edgars Vitolins, "Autonomous Multiagent Aviation: Challenges and Opportunities", 1st AAAI Spring Symposium on Challenges and Opportunities in Multiagent Reinforcement Learning (AAAI SSS-COMARL 2020-2021)
- E. Liebman & P. Stone, "Utilizing Mood-Inducing Background Information in User-Agent Interaction: a Music Case Study", 4th Conference on Reinforcement Learning and Decision Making (RLDM), June 2019
- Ishan Durugkar, E. Liebman & P. Stone, "Balancing Individualized Preferences with Shared Objectives in Multiagent Cooperation", 4th Conference on Reinforcement Learning and Decision Making (RLDM), June 2019
- E. Liebman, "Sequential Decision Making in Artificial Musical Intelligence", AAAI Doctoral Consortium, February 2018
- E. Liebman, E. Zavesky & P. Stone, "Autonomous Model Management via Reinforcement Learning", AAAI Engineering Dependable and Secure Machine Learning Systems Workshop, February 2018
- E. Liebman, E. Zavesky & P. Stone, "Autonomous Model Management via Reinforcement Learning - Extended Abstract", 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017) May 2017 (extended abstract)
- P. MacAlpine, E. Liebman & P. Stone, "Adaptation of Surrogate Tasks for Bipedal Walk Optimization", GECCO Surrogate-Assisted Optimization (SAE-Opt) Workshop, July 2016
- E. Liebman, P. Stone and C. N. White, "Decision Mechanisms Underlying Mood-Congruent Emotional Classification", 2nd Conference on Reinforcement Learning and Decision Making (RLDM), June 2015
- E. Liebman, "Intelligent Learning Agents for Music-Based Interaction and Analysis", AAMAS Doctoral Consortium, May 2015
- E. Liebman & P. Stone, "DJ-MC: A Reinforcement-Learning Framework for a Music Playlist Recommender System", 1st Conference on Reinforcement Learning and Decision Making (RLDM), October 2013
- P. MacAlpine, E. Liebman & P. Stone, "Simultaneous Learning and Reshaping of an Approximated Optimization Task", AAMAS Autonomous Learning Agents (ALA) Workshop, May 2013
Book Chapters
Magazine Articles
Talks and Poster Presentations
- Talk, "Sequential Decision Making in Music Understanding and Recommendation", feature speaker, Big Data AI Meetup, Capital Factory, 2019
- Talk, "Sequential Decision Making in Music Understanding and Recommendation", feature speaker, Austin AI Developers Group, UT Austin, 2019
- Talk, "A Reinforcement-Learning Approach for Music Playlist Recommendation", Amazon, 2018
- Talk, "Towards Artificial Musical Intelligence", ARM Research, 2018
- Talk, "Intelligent Learning Agents for Music-Based Interaction and Analysis", invited talk, IBM Research, 2016
- Talk, "DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation", The 13th Bar-Ilan Symposium on the Foundations of Artificial Intelligence, 2015
- Talk, "A Phylogenetic Approach to Music Performance Analysis", CMPCP Performance Studies Network, Third International Conference, 2014
- Poster Presentation, "A Phylogenetic Approach to Music Performance Analysis", The 14th Israeli Bioinformatics Symposium, 2012
- Talk, "Bioinformatic Approaches to Music Analysis", Seventh Edmond J. Safra Bioinformatics Retreat, 2012
- Poster presentation, "A Phylogenetic Approach to Music Performance Analysis", Sixth Edmond J. Safra Bioinformatics Retreat, 2011
- Poster presentation, "Algorithmic Approaches to Deciphering the Geneaology of Music Performances",The Computer Science Department Competition for Exceptional Projects, Tel Aviv University, 2009
