A picture of Bob Bob Givan

465 Northwestern Avenue, Rm. 313C
Electrical Engineering Building
School of Electrical & Computer Engineering
Purdue University
West Lafayette, IN 47907

The following information is backwards:

8609-494 (567)    (office, backwards)
7248-235 (567)    (mobile, backwards)
ude.eudrup@navig    (email, backwards)

Title: Associate Professor

To see me, send me email, or visit my Office Hours. If an email to me goes unanswered for a couple days, please repeat it.

I received my computer science Ph.D. from MIT in 1996, working with David McAllester.



My research is in several areas: machine planning, machine learning, knowledge representation, stochastic modelling, and automated reasoning. I am currently focusing on applying automated reasoning to AI planning domains. I have worked in the past applying AI techniques to the control of computer communications networks. I have also previously published in the areas of automated reasoning, formal methods, type inference, programming languages, and logic in computer science.


Publications

  • Reasoning About Planning Domains
  • with Rajesh Kalyanam and Tanji Hu
  • AAAI 2011 Workshop on Generalized Planning
  • PDF

  • Stochastic Enforced Hill-Climbing
  • with Jia-Hong Wu and Rajesh Kalyanam
  • JAIR 42:815-850, 2011
  • PDF, online appendix 1 (pdf), online appendix 2 (zip), online appendix 3 (pdf)

  • Automatic Induction of Bellman-Error Features for Probabilistic Planning
  • with Jia-Hong Wu
  • JAIR 38:687-755, 2010
  • PDF, online appendix

  • Stochastic Enforced Hill-Climbing
  • with Jia-Hong Wu and Rajesh Kalyanam
  • ICAPS '08
  • PDF

  • Probabilistic Planning via Determinization in Hindsight
  • with Sungwook Yoon, Alan Fern, and Subbarao Kambhampati
  • AAAI '08
  • PDF

  • FF-Replan: A Baseline for Probabilistic Planning
  • with Sungwook Yoon and Alan Fern
  • ICAPS '07
  • PDF

  • Using Learned Policies in Heuristic-Search Planning
  • with Sungwook Yoon and Alan Fern
  • IJCAI '07
  • pdf on request

  • Discovering relational domain features for probabilistic planning
  • with Jia-Hong Wu
  • ICAPS 2007
  • PDF

  • Approximate Policy Iteration with a Policy Language Bias: Learning to Solve Relational Markov Decision Processes
  • with Alan Fern and Sungwook Yoon
  • JAIR 25:85-118, 2006
  • PDF

  • Learning Heuristic Functions from Relaxed Plans
  • with Sungwook Yoon and Alan Fern
  • ICAPS '06
  • pdf on request

  • Learning Measures of Progresss for Planning Domains
  • with Sungwook Yoon and Alan Fern
  • AAAI '05
  • pdf on request

  • Feature-discovering Approximate Value Iteration Methods
  • with Jia-Hong Wu
  • SARA 2005
  • PDF

  • Simultaneous Heuristic Search for Conjunctive Subgoals
  • with Lin Zhu
  • AAAI 2005
  • PDF

  • Feature-discovering Approximate Value Iteration Methods
  • with Jia-Hong Wu
  • Purdue ECE Technical Report TR-ECE-04-06, November, 2004
  • PDF

  • Approximation Results on Sampling Techniques for Zero-sum, Discounted Markov Games
  • with Uday Savagaonkar and Edwin K. P. Chong
  • draft
  • PDF

  • Dynamic Feature Selection for Hardware Prediction
  • with Alan Fern, Babak Falsafi, and T. N. Vijaykumar
  • JSA 2005
  • PDF

  • Relational Sequential Inference with Reliable Observations
  • with Alan Fern
  • ICML 2004
  • PDF

  • Parallel Rollout for Online Solution of Partially Observable Markov Decision Processes
  • with Hyeong Soo Chang and Edwin K. P. Chong
  • Discrete Event Dynamic Systems, 2004
  • PDF

  • Learning Domain-Specific Control Knowledge from Random Walks
  • with Alan Fern and SungWook Yoon
  • ICAPS-04
  • PDF

  • Approximate Policy Iteration with a Policy Language Bias
  • with Alan Fern and SungWook Yoon
  • NIPS-2003
  • PDF

  • Online Pricing for Bandwidth Provisioning in Multi-class Networks
  • with Uday Savagaonkar and Edwin K. P. Chong
  • Computer Networks, April 2004
  • PDF

  • Online Ensemble Learning: An Empirical Study
  • with Alan Fern
  • Machine Learning, October 2003
  • PDF

  • Equivalence Notions and Model Minimization in Markov Decision Processes
  • with Tom Dean and Matt Greig
  • Artificial Intelligence, July 2003
  • PDF

  • Prediction-based Video Streaming
  • with Gang Wu and Edwin K. P. Chong
  • IEEE 2003 Global Communications Conference (GLOBECOM)

  • Congestion Control using Policy Rollout
  • with Gang Wu and Edwin K. P. Chong
  • IEEE 2003 Conference on Decision and Control

  • The Complexity of Decentralized Control of Markov Decision Processes
  • with Daniel Bernstein, Neil Immerman, and Shlomo Zilberstein
  • Mathematics of Operations Research, November, 2002
  • PDF

  • Streaming stored video over AIMD transport protocols
  • with Gang Wu and Edwin K. P. Chong
  • 2002 IEEE International Symposium on Multimedia Software Engineering
  • PDF

  • Sampling Techniques for Zero-sum, Discounted Markov Games
  • with Uday Savagaonkar and Edwin K. P. Chong
  • Allerton Conference on Control and Communications, 2002
  • PDF

  • Specific-to-General Learning for Temporal Events with Application to Video Event Recognition
  • with Alan Fern and Jeffrey Mark Siskind
  • Journal of Artificial Intelligence Research (JAIR), December, 2002
  • PDF

  • Inductive Policy Selection for First-Order Markov Decision Processes
  • with SungWook Yoon and Alan Fern
  • UAI-02
  • PDF

  • Specific-to-General Learning for Temporal Events
  • with Alan Fern and Jeffrey Mark Siskind
  • AAAI-02
  • PDF

  • Learning Temporal, Relational, Force-Dynamic Event Definitions from Video
  • with Alan Fern and Jeffrey Mark Siskind
  • AAAI-02
  • PDF

  • Scheduling Multiclass Packet Streams to Minimize Weighted Loss
  • with Hyeong Soo Chang and Edwin K. P. Chong
  • Queueing Systems (QUESTA), July 2002
  • PDF

  • Burst-level Congestion Control using Hindsight Optimization
  • with Gang Wu and Edwin K. P. Chong
  • IEEE Transactions on Automatic Control, June, 2002
  • PDF

  • Tarskian Set Constraints
  • with David McAllester, Carl Witty, and Dexter Kozen
  • Information and Computation, May, 2002
  • PDF

  • Dynamic Pricing for Bandwidth Provisioning
  • with Uday Savagaonkar and Edwin K. P. Chong
  • Conference on Information Sciences and Systems (CISS-02), 2002
  • PDF

  • Polynomial-time Computation via Local Inference Relations
  • with David McAllester
  • ACM Transactions on Computational Logic, October, 2002
  • PDF

  • Congestion Control via Online Sampling
  • with Gang Wu and Edwin K. P. Chong
  • Infocom 2001
  • PDF

  • A Framework for Simulation-based Network Control via Hindsight Optimization
  • with Edwin K. P. Chong and Hyeong Soo Chang
  • IEEE 2000 Conference on Decision and Control
  • PDF

  • Online Ensemble Learning: An Empirical Study
  • with Alan Fern
  • International Conference on Machine Learning, 2000 (ICML-2000)
  • PDF

  • Online Scheduling via Sampling
  • with Hyeong Soo Chang and Edwin K. P. Chong
  • Artificial Intelligence Planning and Scheduling, 2000 (AIPS-2000)
  • PDF

  • Bounded Parameter Markov Decision Processes
  • with Tom Dean and Sonia Leach
  • Artificial Intelligence, 2000
  • PDF

  • Solving Stochastic Planning Problems with Large State and Action Spaces
  • with Kee-Eung Kim and Tom Dean
  • AIPS-98
  • PDF

  • Obvious Properties of Computer Programs
  • AAAI-97
  • PDF

  • Model Minimization in Markov Decision Processes
  • with Tom Dean
  • AAAI-97
  • PDF

  • Model Minimization, Regression and Propositional STRIPS Planning
  • with Tom Dean
  • IJCAI-97
  • PDF

  • Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes
  • with Tom Dean and Sonia Leach
  • Uncertainty in AI, 1997
  • PDF

  • Bounded Parameter Markov Decision Processes
  • with Tom Dean and Sonia Leach
  • European Conference on Planning, 1997
  • PDF

  • Inferring Program Specifications in Polynomial-time
  • Static Analysis Symposium, 1996
  • PDF

  • Tarskian Set Constraints
  • with David McAllester, Carl Witty, and Dexter Kozen
  • Logic in Computer Science, 1996
  • PDF

  • Taxonomic Syntax for First Order Inference
  • with David McAllester
  • Journal of the ACM, 1993
  • PDF

  • Natural Language Syntax and First Order Inference
  • with David McAllester
  • Artificial Intelligence, 1992
  • PDF

  • New Results on Local Inference Relations
  • with David McAllester
  • Conference on Knowledge Representation, 1992
  • PDF

  • Natural Language Based Inference Procedures Applied to Schubert's Steamroller
  • with David McAllester and Shameer Shalaby
  • AAAI-91
  • PDF

  • Automatically Inferring Properties of Computer Programs
  • MIT PhD Thesis, June 1996
  • PDF


  • Some Talk Slides

  • Knowledge Representation Meets Stochastic Planning , Dagstuhl, May, 2003.
  • Sampling Techniques for Large Markov Decision Processes, Dagstuhl, November, 2001.
  • MDP Tutorial --- definitions and extensions, Dagstuhl, November, 2001.
  • Large State Space Techniques for Markov Decision Processes, Dagstuhl, November, 2001.



  • Acknowledgement: much of the research reported above was supported by NSF grants 9977981-IIS, 0093100-IIS, 0905372-IIS, and 0098089-ECS.
    Purdue University is an equal access/equal opportunity university. If you have trouble accessing this page because of a disability, please contact Bob Givan using the email address formed by his last name and purdue.edu