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What Happened in AI Since Quals?. Corin Anderson ([email protected]) Steve Wolfman ([email protected]) Tessa Lau ([email protected]). Applications. Games Chess: brute force search Backgammon: reinforcement learning Bridge: HTN, Monte Carlo simulation Crosswords: combination of many expert modules

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What happened in ai since quals

What Happened in AI Since Quals?

Corin Anderson ([email protected])

Steve Wolfman ([email protected])

Tessa Lau ([email protected])


Applications
Applications

  • Games

    • Chess: brute force search

    • Backgammon: reinforcement learning

    • Bridge: HTN, Monte Carlo simulation

    • Crosswords: combination of many expert modules

  • Deep Space One: Modeling, SAT-like planning

  • Automatic grading: Latent Semantic Indexing

  • RoboCup


Planning

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Planning

  • The last thing you remember: UCPOP

  • Graphplan

  • SATPLAN

    • Encode planning problem in Boolean Satisfiability (proposition logic)

    • Solve logic problem with general-purpose algorithms


Machine learning
Machine Learning

  • Overfitting

    • Extensive search in hypothesis space causes overfitting

    • Occam’s Razor is just one possible bias

  • Scaling up to handle huge training sets

    • Make intermediate decisions with subsamples

    • Produce less accurate predictors with subsamples and combine them into ensembles


Machine learning ensembles
Machine Learning: Ensembles

  • Bagging

    • create k training sets by sampling real input set

    • Learn k predictors for the task, vote among them

  • Boosting

    • Learn a predictor from weighted sample of real input

    • Change weights to emphasize misclassified points

    • Repeat

    • Vote resulting predictors according to accuracy


Intelligent agents
Intelligent Agents

  • Softbots

    • Combine traditional AI with new domains/techniques

  • Directions

    • Multiple agents and cooperation

      • Economic models: auctions

    • Learning about other agents

    • Learning about the environment

    • Human-agent interaction


Intelligent user interfaces
Intelligent User Interfaces

  • Programming by demonstration (PBD)

    • System learns program by watching user perform task

  • Bayesian networks

    • What’s the probability that the user wants to perform task X? Ex: MS Office Help facility


Text images
Text, Images

  • Text

    • Latent Semantic Indexing

    • Cross-language corpora

    • WordNet

  • Images

    • Segmentation

    • Face recognition

    • Sign language recognition


Ai and the web
AI and the Web

A rich environment for applications

  • Planning for information retrieval

  • Data extraction

    • Wrappers

    • Shopping on the web

    • Finding product price, description, etc.

  • Information agents

    • Collaborative filtering; sorting news; etc.

  • Data mining

  • Text understanding


Ai at the uw
AI at the UW

  • Planning

    • SGP - Graphplan-based planner

    • LPSAT - SATPLAN-based planner

  • Machine learning

    • RISE - Occam’s razor isn’t always sound advice


More ai at the uw
More AI at the UW

  • Web work

    • Adaptive web sites

    • Metacrawler, HuskySearch

    • Jango

  • Intelligent agents

    • PBD - learning macros


Startups from uw ai
Startups from UW/AI

  • NetBot (Weld, Etzioni)

    • Internet shopping agent (Jango project)

    • Purchased by Excite

  • Nimble.com (Weld, Levy)

    • XML data management (mumble, mumble)

  • Ad Relevance (Weld)

    • Target web advertising


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