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Research Areas S. E. Shimony

Research Areas S. E. Shimony. Artificial intelligence and applications. Probabilistic reasoning. Knowledge discovery and data-mining. Meta-reasoning ( “ anytime algorithms ” ). Decision-making under uncertainty. Spatio-temporal data models and reasoning. Probabilistic Reasoning.

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Research Areas S. E. Shimony

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  1. Research AreasS. E. Shimony Artificial intelligence and applications. • Probabilistic reasoning. • Knowledge discovery and data-mining. • Meta-reasoning (“anytime algorithms”). • Decision-making under uncertainty. • Spatio-temporal data models and reasoning.

  2. Probabilistic Reasoning • Structured probabilistic models: Bayesian networks and Bayesian Knowledge Bases. • Reasoning in structured models: exact and anytime approximation algorithms. Example: linear-time algorithm for polytree+selector topology in Bayes networks. Application: prediction of ramifications of user actions in CP-net based systems.

  3. Decision-Making under Uncertainty • Structured Partially Observable Markov Decision Processes. • Special cases: Canadian Traveler Problem Given a weighted graph, where some edges can become blocked, find a policy that minimizes expected travel costs.

  4. Knowledge Discovery • Learning Bayesian Knowledge Bases from data. (Finding covering and disjoint set of probabilistic rules.) • Complexity of some disjoint-DNF problems.

  5. Meta-Reasoning • Search control using expected search utility, for: • constraint satisfaction problems. • interleaving game-tree search with planning. • Algorithm selection, control of algorithm portfolios.

  6. Spatio-Temporal Reasoning • Object-oriented spatio-temporal probabilistic data models. • Path planning in time-varying environments with uncertainty. • Applications in simulated and actual robotics. • AI in games (strategy and real-rime)

  7. Research Projects • Search in graphs under uncertainty (e.g. Canadian Traveller Problem – ISF) Past projects: • Inspection setup (IMG4): probabilistic reasoning, meta-reasoning, spatio-temporal models, data-mining. • Business-oriented knowledge discovery and representation (KITE, cVidya, DT): preference optimization, probabilistic reasoning, data-mining. • Multi-agent simulated robotics: meta-reasoning, probabilistic reasoning, spatio-temporal reasoning.

  8. Research Students • Dror Fried, Olga Maksin, Doron Zarchy (CTP) • David Tolpin (Meta-reasoning) Recently graduated students: • Ami Berler (Multi-agents POMDP) • Yan Radovilsky (Meta-reasoning) • Natalia Vanetik (Graphs: flows, mining) • Sivan Albagli (Interactive ontology matching) • Yan Virin (Decision-making under Uncertainty) • Maxim Binstok (Decision-making and preferences)

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