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Susan L. Epstein

The CUNY Graduate School, Department of Computer Science and

 Hunter College, Department of Computer Science

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Ariadne

Ariadne is a FORR-based program that learns to travel through grid world mazes. Its premise is that agreement among varying heuristic viewpoints is a valid decision-making principle. Ariadne minimizes search, focusing instead upon reasonable rationales and multiple learning methods. Ariadne learns during travel, and demonstrates substantial, learned expertise after relatively little training. Work with Ariadne has pioneered the ability to do situation-based search in FORR.

Key references

Epstein, S. L. 1998. Pragmatic Navigation: Reactivity, Heuristics, and Search. Artificial Intelligence, 100 (1-2): 275-322.

Epstein, S. L. 1997. Spatial Representation for Pragmatic Navigation. In Proceedings of the Conference on Spatial Information Theory - COSIT '97, 373-388. Laurel Highlands, PA: Springer Verlag.

Epstein, S. L. 1995. On Heuristic Reasoning, Reactivity, and Search. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 454-461. Montreal: Morgan Kaufmann.

Additional references

Epstein, S. L. 1997. Representation and Reasoning for Pragmatic Navigation. In Proceedings of the AAAI Workshop on Spatial and Temporal Reasoning, Providence: AAAI.

Epstein, S. L. 1996. Spatial Representation for Pragmatic Navigation. In Proceedings of the AAAI Spring Symposium on Spatial Reasoning, Stanford, CA: AAAI.

Araidne was the daughter of King Minos of Crete. It was she who told Theseus how to find his way through the labyrinth containing the kingdom's treasure.

This material is based upon work supported by the National Science Foundation under Grant Nos. 9423085, #IRI-9703475, 9222720, and #9001936, by the New York State Technological Development Graduate Research and Technology Initiative, and by the PSC-CUNY Research Foundation.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, New York State, or PSC-CUNY.

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