If we knew what it was we were doing, it would not be called research, would it?
-- Albert Einstein

Current Projects

  • Formal Inference in Translation Graph: Developing probabilistic inference techniques to formalize inference in translation graphs, a graph that is formed by combining all available dictionaries between all possible languages in the world. An efficient and high quality inference procedure will enable the system to produce good translations from a sense in one language to several languages, even when there is no available dictionary between the exact pair of languages. More details on the Panimages website.

  • Large-scale Probabilistic Planning: Exploiting the availability of external memory to solve large Markov Decision Processes. We hope to alleviate the memory bottleneck in solving the large MDPs and scale to large, industry sized probabilistic planning problems. A recent paper on this work.

    • Past Projects

  • Hybridizing Planners: A fast but suboptimal planner may be hybridized with a slow but optimal one to yield a high-quality, anytime planner that solves the problems in intermediate times. We developed HybPlan, a planner that hybridized GPT and MBP for probabilistic planning.

  • Concurrent Probabilistic Temporal Planning: Developing high-quality and efficient techniques to solve MDPs that formulate probabilistic planning problems involving durative and concurrent actions.

    • Publications

    A complete list of publications can be found here.

    Service

  • PC Member: ICAPS'08, AAAI'08, ICAPS'07, AAAI'05.
  • Reviewer: JAIR, JMLR, AAMAS, IJCAI, UbiComp.
  • Tutorial: Probabilistic Temporal Planning at ICAPS'07.
  • Workshop: A Reality Check for Planning and Scheduling Under Uncertainty at ICAPS'08.

    • Presentations in the AI group (grad school times)

    1. Introduction to Semantic Web (Fall 2001)
    2. PGRAPHPLAN : A planner for probabilistic domains (Spring 2002)
    3. Nursebot : Robot assistants for the elderly (Spring 2002)
    4. SPUDD : A planner for probabilistic domains (Fall 2002)
    5. A survey of Relational MDP approaches (Fall 2003)
    6. Introduction to Markov Decision Processes (Fall 2003)
    7. A survey of Hierarchical Reinforcement Learning Techniques (Spring 2005)