Shlomo Zilberstein (Hebrew: שלמה זילברשטיין; born 1960) is an Israeli-American computer scientist.

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.

[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).

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.

[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).