Recent papers from Yochan


Recent papers from YOCHAN:
The ASU Planning Group


Following is the list of papers organized by topic. The clickable index gives the topics. To view a paper, click on its title.

Contact Subbarao Kambhampati by email if you have questions or need further information.

Page accessed times since 2/17/96.


Index:

Most recent additions
Introductory and Overview materials
EBL and EBG for Planning
Replay, Reuse and Casebased Reasoning for planning
Frameworks for Comparison and Evaluation of planners
MTC--what is it good for?
Pruning strategies for planning
Multi-contributor causal links and Systematicity
Hybrid planning architectures and Manufacturing planning


Most recent additions:

  1. Winning by being Lazy: Hierarchy, Abstraction and Least-commitment in the new-age planning
    S. Kambhampati. Invited talk at NIPS-98 workshop on Abstraction and Hierarchy in Reinforcement Learning.

  2. Optimization Strategies for Information Gathering Plans
    E. Lambrecht and S. Kambhampati. November 98.
    ASU CSE TR 98-018

  3. Optimizing Recursive Information Gathering Plans
    E. Lambrecht. M.S. Thesis. September, 98. Here is the defense talk.

  4. Planning graph as a (Dynamic) CSP: Exploiting DDB, EBL and other CSP search techniques in Graphplan
    S. Kambhampati
    ASU CSE TR 98-008. August 98. (Major revision: July 1999).

  5. On the relations between intelligent backtracking and explanation based learning in Planning and CSP
    S. Kambhampati
    ASU CSE TR 97-018. To appear in Artificial Intelligence, Spring 1999

  6. Encoding HTN planning in propositional logic
    A. Mali and S. Kambhampati
    In Proc. AIPS-98. 1998.

  7. Hybrid planning for partially hierarchical domains
    S. Kambhampati, A. Mali and B. Srivastava.
    In Proc. AAAI-98. 1998. Here is the talk

  8. Frugal propositional encodings for planning
    A. Mali and S. Kambhampati.
    AIPS Workshop on Planning as Combinatorial Search. 1998.

  9. Refinement based planning as satisfiability
    A. Mali and S. Kambhampati.
    AIPS Workshop on Planning as Combinatorial Search. 1998.

  10. Distributed Planning
    A. Mali and S. Kambhampati.
    Survey paper to appear in Encyclopedia of Distributed Computer Science. 1998.

  11. Efficiently executing information gathering plans
    E. Lambrecht and S. Kambhampati.
    AAAI workshop on AI and Information Integration. 1998.

  12. Understanding and Extending Graphplan
    S. Kambhampati, E. Lambrecht and E. Parker
    To be presented at the 4th european conference on planning, 1997 Here is the talk

  13. Synthesizing customized planners from specifications
    B. Srivastava and S. Kambhampati
    Journal of Artificial Intelligence Research. Volume 8. pp 93-128. 1998.
    Reviewed in "The page of positive reviews"

  14. Storing and Indexing plan derivations through explanation-based analysis of retrieval failures
    L. Ihrig and S. Kambhampati
    Journal of Artificial Intelligence, Vol 7, pp. 161-198. 1997.

  15. A structured approach for synthesizing planners from specifications
    B. Srivastava, A. Mali and S. Kambhampati
    12th IEEE Intl. Conf. on Automated Software Engineering, 1997, Lake Tahoe. (To appear)

  16. Challenges in bridging plan-synthesis paradigms
    S. Kambhampati
    To appear as a Challenge paper at IJCAI-97. Here is the challenge homepage

  17. Planning for Information Gathering: A Tutorial Survey
    E. Lambrecht and S. Kambhampati
    ASU CSE TR 97-017, May 1997.

  18. Process Planner's Assistant: An incremental and interactive approach to automating process planning
    X. Li, S. Kambhampati, K. Hirode and J. Shah
    ASME Design Engineering Techical Conference, 1997 (To appear) Compressed version.

  19. Refinement planning as a unifying framework for plan synthesis
    S. Kambhampati
    AI Magazine, Vol 18. No. 2, Summer, 1997. Here is the pdf version of the article as it appears in AI Magazine.
    (Here is an independent survey of this stuff written by someone from Finland...)

  20. On the role of Disjunctive representations and Constraint Propagation in Refinement Planning
    S. Kambhampati and X. Yang
    Final version of a paper to appear in KRR-96.
    Here is the talk on the paper delivered at KR-96, November 5th, 1996 HTML versionPostscript Version

  21. Refinement planning: Status and Prospectus
    S. Kambhampati.
    AAAI-96 invited talk.
    Color slides (with commentary) ( HTML version or ( Postscript or Compressed Postscript)
    Black and white slides (with commentary) ( Postscript or Compressed Postscript)
    Proceedings paper (a bit dated; talk is more up to date) ( Postscript)

  22. Unifying Classical Planning Approaches
    S. Kambhampati and B. Srivastava
    ASU CSE Technical Report 96-006. (59 pages) (Submitted for publication)

  23. Using Disjunctive orderings instead of conflict resolution in partial order planning.
    S. Kambhampati
    ASU CSE TR 96-002. January 1996.

Frameworks for Comparison and Evaluation of Planners

  1. Unifying Classical Planning Approaches
    S. Kambhampati and B. Srivastava
    ASU CSE Technical Report 96-006. (59 pages) (Submitted for publication)

  2. A Candidate Set based analysis of subgoal interactions in conjunctive goal planning
    S. Kambhampati
    AIPS-96.

  3. Universal Classical Planner: An algorithm for unifying state-space and plan-space planning
    S. Kambhampati and B. Srivastava
    To appear in Proc. 3rd European Planning Workshop (EWSP-95). ASU CSE TR 94-002; January 1995.

  4. Planning as Refinement Search: A unified framework for evaluating design tradeoffs in partial order planning
    S. Kambhampati, C. Knoblock and Q. Yang
    ASU CSE TR 94-002, To appear in Artificial Intelligence Special Issue on Planning and Scheduling. Here is a Link to the code, data and results of the experiments reported in the paper.(~0.5 Meg)

  5. A comparative analysis of partial order planning and task reduction planning
    S. Kambhampati
    SIGART Bulletin, Special Section on Evaluating Plans, Planners and Planning agents, Vol. 6., No. 1, January, 1995.

  6. Refinement search as a unifying framework for analyzing plan space planners
    S. Kambhampati
    In Proceedings of 2nd Intl. Conf on Ppls. Knowledge Rep. and Reasoning, 1994

  7. Design Tradeoffs in partial order (plan space) planning
    S. Kambhampati
    In Proceedings of 2nd Intl. Conf on AI Planning Systems, 1994

  8. Comparing Partial order planning and Task Reduction planning: A preliminary report
    S. Kambhampati
    In Working notes of AAAI-94 workshop on Comparative analysis of planning algorithms
    (also ASU-CSE TR 94-001, March, 1994)

  9. Planning as Refinement Search: A unified framework for comparative analysis of search space size and performance
    S. Kambhampati
    ASU CSE TR 93-004 (an older version of ASU TR 94-002 above)
Back to Index

Modal Truth Criterion-- What is it good for?

  1. On the nature of modal truth criteria in planning
    S. Kambhampati and D.S. Nau
    In Proceedings of AAAI-94

  2. On the nature and role of modal truth criteria in planning
    S. Kambhampati & D.S. Nau
    Artificial Intelligence, 1995 (to appear)
    (also UMD Tech. Report ISR-TR-93-30)
Back to Index

EBL and EBG for Improving Planning Performance

  1. Formalizing Dependency Directed Backtracking and Explanation-based Learning in Refinement Search.
    S. Kambhampati,
    AAAI-96

  2. Failure Driven Dynamic Search Control for Partial Order Planners: An explanation-based approach
    S. Kambhampati, S. Katukam, Y. Qu
    To appear in Artificial Intelligence. ASU CSE TR-95-010.

  3. Learning Explanation-based search control rules for Partial-order planning
    S. Katukam and S. Kambhampati
    In Proceedings of AAAI-94

  4. Learning control rules for expressive plan-space planners: Factors influencing the performance
    Y. Qu and S. Kambhampati
    To appear in Proc. 3rd European Planning Workshop (EWSP-95). ASU CSE TR 95-006.

  5. A Unified framework for Explanation Based Generalization of Partially ordered and partially instantiated plans.
    S. Kambhampati and S. Kedar.
    Artificial Intelligence, Vol. 67, No. 1, May 1994

  6. Formalizing a spectrum of Plan Generalization based on Modal Truth Criteria
    S. Kambhampati
    Accepted to Canadian AI conf, 94

  7. Relative Utility of EBG based Plan Reuse in partial ordering vs. total ordering planning
    S. Kambhampati and J. Chen.
    In Proceedings of AAAI-93
(see also Replay and Reuse for planning).

Back to Index


Reuse and Replay for Improving planning performance

  1. Design and Implementation of a Replay Framework based on a Partial order Planner.
    L. Ihrig and S. Kambhampat
    AAAI-96

  2. Integrating Replay with EBL to improve planning performance
    L. Ihrig and S. Kambhampati
    To appear in Proc. 3rd European Planning Workshop (EWSP-95). ASU CSE TR 94-003; January 1995.

  3. Automatic storage and indexing of plan derivations based on replay failures.
    L. Ihrig and S. Kambhampati
    In Proc. of IJCAI Workshop on formal methods for reuse of plans, proofs and programs.

  4. Plan-space vs. State-space planning in reuse and replay
    L. Ihrig and S. Kambhampati
    ASU CSE TR 94-006, Revised December 1996

  5. Exploiting causal structure to control retrieval and refitting during plan reuse.
    S. Kambhampati
    Computational Intelligence, Vol 10, No 2, May 1994
    (available in hardcopy only)

  6. Relative Utility of EBG based Plan Reuse in partial ordering vs. total ordering planning
    S. Kambhampati and J. Chen.
    In Proceedings of AAAI-93

  7. Derivational replay for partial order planning
    L. Ihrig and S. Kambhampati
    In Proceedings of AAAI-94

  8. Evaluating the Effectiveness of Derivation Replay in Partial-Order vs. State-Space Planning
    L. Ihrig and S. Kambhampati
    In Proceedings of AAAI-94 Workshop on Case-Based Reasoning

  9. A Classification of Plan Modification Strategies Based on Coverage and Information Requirements
    S. Kambhampati
    In Working notes of AAAI 90 Spring Symposium on Case-Based Reasoning, 1990
Back to Index

Pruning strategies for planning

  1. Admissible pruning strategies based on plan minimality for plan space planning.
    S. Kambhampati
    Proc. of IJCAI-95.
    Here is an extended version with empirical results and proofs
Back to Index

Multi-contributor causal links and Systematicity

  1. Characterizing Multi-contributor causal structures for planning
    S. Kambhampati
    In Proceedings of 1st Intl. Conf. on AI Planning Systems, 1992

  2. Multi-Contributor Causal Structures for Planning: A formalization and Evaluation.
    S. Kambhampati
    Artificial Intelligence, Vol. 69, 1994

  3. On the utility of Systematicity: Understanding tradeoffs between redundancy and Commitment during partial order planning.
    S. Kambhampati
    In Proceedings of IJCAI-91
Back to Index

Hybrid Planning Architectures and Manufacturing Planning

  1. An Iterative and Interactive approach for Process Planning
    S. Bathcu, S. Kambhampati, H. Kartheek and J. Shah
    ASU CSE TR 95-023, September 1995.
  2. Integrating General Purpose Planners and Specialized Reasoners: Case Study of a Hybrid Planning Architecture.
    S. Kambhampati, M.R. Cutkoksy, J.M. Tenenbaum and S. Lee
    IEEE Trans. on Systems, Man and Cybernetics, Special issue on Planning, Scheduling and Control, Vol. 23, No. 6, November/December, 1993) An earlier version appears in Proc. AAAI-91.
    Here is a postscript version without figures. Full paper with figures is available only in hardcopy.

  3. Planning in Concurrent Domains
    S. Kambhampati, J.M. Tenenbaum.
    Proceedings of DARPA Workshop on Innovative approaches to planning, scheduling and control.
Back to Index

Introductory and Overview materials

  1. Planning Methods In Artificial Intelligence (Notes from the ASU Planning Seminar)
    Compiled by S. Kambhampati. ASU CSE TR 96-004

  2. A Candidate Set based analysis of subgoal interactions in conjunctive goal planning
    S. Kambhampati, L. Ihrig and B. Srivastava.
    3rd Intl. Conf. on AI Planning Systems, May 1996 (to appear).

  3. AI Planning: A prospectus on theory and applications
    S. Kambhampati
    ACM Computing Survyes: Symposium on Artificial Intelligence, Sept. 1995

  4. Planning and Scheduling
    T. Dean and S. Kambhampati
    CRC Handbook of Computer Science and Engineering (to appear),1995

  5. Classical Planning: Compilation of notes from a Seminar course held at ASU in Spring 93
    S. Kambhampati
    ASU CSE Working Notes 93-003
    (If you retrieve this file, please let me know by e-mail)

  6. Classical Planning: Compilation of notes from a Seminar course held at ASU in Spring 94
    S. Kambhampati
    ASU CSE Working Notes 94-008
Back to Index


Subbarao Kambhampati
Associate Professor
rao@asu.edu