M. M. Veloso. PRODIGY/ANALOGY: Analogical Reasoning in General Problem Solving. In: S. Wess, K. D. Altho, M. M. Richter (eds). Topics on Case-Based Reasoning, Selected Papers from the First European Workshop on Case-Based Reasoning|EWCBR'93, Vol. 837 of Lecture Notes in Articial Intelligence, Springer-Verlag, pp. 33-50, 1994.

@inproceedings{Veloso93,
    author = "Manuela M. Veloso",
    title = "Prodigy/Analogy: Analogical Reasoning in General Problem Solving",
    booktitle = "{EWCBR}",
    pages = "33-52",
    year = "1993",
    url = "citeseer.ist.psu.edu/veloso94prodigyanalogy.html" }
}

Author of the summary: Jim Davies, 2004, jim@jimdavies.org

Cite this paper for:

• SYSTEM: Prodigy/Analogy
• USES-SUBSYSTEM: NOLIMIT

• accumulate episodic problem solving experiences
• define and decide when 2 problem solving situations are similar
• how to organize a large library of cases
• how to transfer chains of problem solving decisions from past experience to new when only a partial match exists.

The NOLIMIT finds solutions through search, but the case saved in memory only contains the decision nodes of the final successful path. [38]

"In Prodigy, a problem is defined by the goal statement and the initial state of the problem situation." [39]

Prodigy can handle multiple goals. It takes a complex initial state and focuses on the relevent attributes for a single given goal, and finds the weakest preconditions needed for that goal.

Summary author's notes:

• The domain for this paper is a trucking/logistics domain, where no new objects are created.