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Ashish Sabharwal,
an Indian American mathematician, computer scientist, and senior research scientist at the Allen Institute for Artificial Intelligence (AI2) [1], exploring new avenues in probabilistic inference, combinatorial reasoning, and discrete optimization. Before, he spent at Thomas J. Watson Research Center and Cornell University. He defended his Ph.D. in 2005 from University of Washington, Seattle on algorithmic applications of propositional proof complexity, SAT solvers, after graduating from the Indian Institute of Technology, Kanpur. Along with Raghuram Ramanujan and Bart Selman, Ashish Sabharwal researched on properties of adversarial search spaces that play a key role in the success or failure of UCT and similar sampling-based approaches [2].
Ashish Sabharwal [3]

Selected Publications

[4]

External Links


References

  1. ^ Allen Institute for Artificial Intelligence
  2. ^ Raghuram Ramanujan, Ashish Sabharwal, Bart Selman (2010). On Adversarial Search Spaces and Sampling-Based Planning. ICAPS 2010
  3. ^ Ashish Sabharwal
  4. ^ dblp: Ashish Sabharwal
  5. ^ Search traps in MCTS and chess by Daniel Shawul, CCC, December 25, 2017

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