Shlomo Zilberstein (Hebrew: שלמה זילברשטיין; born 1960) is an Israeli-American computer scientist. He is a Professor of Computer Science and Associate Dean for Research and Engagement in the College of Information and Computer Sciences at the University of Massachusetts, Amherst.[1] He graduated with a B.A. in Computer Science summa cum laude from Technion – Israel Institute of Technology in 1982, and received a Ph.D. in Computer Science from University of California at Berkeley in 1993, advised by Stuart J. Russell.[2][3] He is known for his contributions to artificial intelligence, anytime algorithms, multi-agent systems, and automated planning and scheduling algorithms, notably within the context of Markov decision processes (MDPs), Partially Observable MDPs (POMDPs), and Decentralized POMDPs (Dec-POMDPs).
Research
His research is in the area of artificial intelligence, specifically automated planning, in addition to decision theory, reasoning under uncertainty, heuristic search, automated coordination and communication, and reinforcement learning.[4]
He directs the Resource-Bounded Reasoning Laboratory[5] at the University of Massachusetts, Amherst.[6] In 2002, Daniel S. Bernstein, Robert Givan, Neil Immerman, and Shlomo Zilberstein introduced the Decentralized POMDP which extends the widely used single-agent POMDP model to a multi-agent scenario (Dec-POMDP).[7] He has also developed AI algorithms for semi-autonomous systems with potential applications to semi-autonomous cars.[8][9][10][11]
Service and awards
He served as editor-in-chief of the Journal of Artificial Intelligence Research and associate editor of the Journal of Autonomous Agents and Multi-Agent Systems.[12] Additionally, he served as chair of the conference committee for both the Twenty-Ninth and Thirtieth AAAI Conference on Artificial Intelligence.[13][14] The National Science Foundation awarded Dr. Zilberstein with the RIA, CAREER, and ITR awards.[15] He was elected as a fellow of the Association for the Advancement of Artificial Intelligence[16] in 2011 and of the Association for Computing Machinery[17] in 2021.
Selected publications
- Srivastava, Siddharth; Immerman, Neil; Zilberstein, Shlomo (2012). "Applicability Conditions for Plans with Loops: Computability Results and Algorithms" (PDF). Artificial Intelligence. 191 (1–2): 1–19. doi:10.1016/j.artint.2012.07.005.
- Amato, Christopher; Bernstein, Daniel S.; Zilberstein, Shlomo (2010). "Optimizing Fixed-Size Stochastic Controllers for POMDPs and Decentralized POMDPs" (PDF). Autonomous Agents and Multi-Agent Systems. 21 (3): 293–320. doi:10.1007/s10458-009-9103-z. S2CID 12915662.
- Seuken, Sven; Zilberstein, Shlomo (2008). "Formal Models and Algorithms for Decentralized Decision Making under Uncertainty" (PDF). Autonomous Agents and Multi-Agent Systems. 17 (1): 190–250. doi:10.1007/s10458-007-9026-5. S2CID 12707282.
- Goldman, Claudia V.; Zilberstein, Shlomo (2004). "Decentralized Control of Cooperative Systems: Categorization and Complexity Analysis" (PDF). Journal of Artificial Intelligence Research. 22: 143–174. doi:10.1613/jair.1427.
- Hansen, Eric A.; Bernstein, Daniel S.; Zilberstein, Shlomo (2004). "Dynamic Programming for Partially Observable Stochastic Games" (PDF). Proceedings of the 19th National Conference on Artificial Intelligence. AAAI. pp. 709–715.
- Bernstein, Daniel S.; Givan, Robert; Immerman, Neil; Zilberstein, Shlomo (2002). "The Complexity of Decentralized Control of Markov Decision Processes" (PDF). Mathematics of Operations Research. 27 (4): 819–840. arXiv:1301.3836. doi:10.1287/moor.27.4.819.297. S2CID 1195261.
References
External links
