Planning and Learning by Analogical Reasoning

@inproceedings{Veloso1994PlanningAL,
  title={Planning and Learning by Analogical Reasoning},
  author={Manuela M. Veloso},
  booktitle={Lecture Notes in Computer Science},
  year={1994}
}
  • M. Veloso
  • Published in
    Lecture Notes in Computer…
     7 December 1994
  • Business
Overview.- The problem solver.- Generation of problem solving cases.- Case storage: Automated indexing.- Efficient case retrieval.- Analogical replay.- Empirical results.- Related work.- Conclusion. 
View on Springer
link.springer.com
370 Citations
Highly Influential Citations
45
Background Citations
151
Methods Citations
140
Results Citations
8

370 Citations

Solution-Relevant Abstractions Constrain Retrieval and Adaptation

For analogical theorem proving by induction, this work describes how a solution-relevant abstraction can restrict the retrieval of source cases and the mapping from the source problem to the target problem and how it can determine reformulations that further adapt the source solution.

SiN: Integrating Case-based Reasoning with Task Decomposition

Novel case-based planning algorithm that combines conversational case retrieval with generative planning that is provably correct, and can generate plans given an incomplete domain theory by using cases to extend that domain theory.

Implementation of an analogical reasoning system on a parallel recirculating computer architecture

An approach is described for implementing the SAGE™ analogical reasoning system on a parallel recirculating computer architecture to increase the efficiency of planning, infer missing structure in test cases, and classify cases across domains.

Reformulation in Case-Based Reasoning

The paper provides a definition of reformulation and shows how reformulation is linked to retrieval and adaptation in the case-based reasoning cycle.

Complete Eager Replay

An algorithm for completely replaying previous problem solving experiences for plan-space planners, where not only the solution trace is replayed, but also the explanations of failed attempts made by the first-principle planner are explained.

Learning Domain Structure in HGNs for Nondeterministic planning

This paper presents preliminary ideas of our work for automated learning of Hierarchical Goal Networks in nondeterministic domains. We are currently implementing the ideas expressed in this paper.

Case-Based Reasoning Applied to Planning

Planning means constructing a course of actions to achieve a specified set of goals when starting from an initial situation. For example, determining a sequence of actions (a plan) for transporting…

Design Simplification by Analogical Reasoning

This paper defines a “simplification problem”, then describes the approach to solving design simplification problems by analogical reasoning, and draws conclusions and proposes directions for future research.

Planning and Proof Planning

The paper describes some peculiarities of proof planning and discusses some possible cross-fertilization of planning and proof planning.

Explorer Planning and Proof Planning

The paper adresses proof planning as a specific AI planning. It describes some peculiarities of proof planning and discusses some possible cross-fertilization of planning and proof pl anning.
...