Design and Implementation of a Replay Framework Based on a Partial Order Planner

Abstract

In this paper we describe the design and implementation of the derivation replay framework, dersnlp+ebl (Derivational snlp+ebl), which is based within a partial order planner. dersnlp+ebl replays previous plan derivations by first repeating its earlier decisions in the context of the new problem situation, then extending the replayed path to obtain a complete solution for the new problem. When the replayed path cannot be extended into a new solution, explanation-based learning (ebl) techniques are employed to identify the features of the new problem which prevent this extension. These features are then added as censors on the retrieval of the stored case. To keep retrieval costs low, dersnlp+ebl normally stores plan derivations for individual goals, and replays one or more of these derivations in solving multi-goal problems. Cases covering multiple goals are stored only when subplans for individual goals cannot be successfully merged. The aim in constructing the case library is to pr...

Cite

Text

Ihrig and Kambhampati. "Design and Implementation of a Replay Framework Based on a Partial Order Planner." AAAI Conference on Artificial Intelligence, 1996.

Markdown

[Ihrig and Kambhampati. "Design and Implementation of a Replay Framework Based on a Partial Order Planner." AAAI Conference on Artificial Intelligence, 1996.](https://mlanthology.org/aaai/1996/ihrig1996aaai-design/)

BibTeX

@inproceedings{ihrig1996aaai-design,
  title     = {{Design and Implementation of a Replay Framework Based on a Partial Order Planner}},
  author    = {Ihrig, Laurie H. and Kambhampati, Subbarao},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1996},
  pages     = {849-854},
  url       = {https://mlanthology.org/aaai/1996/ihrig1996aaai-design/}
}