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The Computational Support of Scientific Discovery
, 2000
"... In this paper, we review AI research on computational discovery and its recent application to the discovery of new scientific knowledge. We characterize five historical stages of the scientific discovery process, which we use as an organizational framework in describing applications. We also identif ..."
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Cited by 24 (2 self)
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In this paper, we review AI research on computational discovery and its recent application to the discovery of new scientific knowledge. We characterize five historical stages of the scientific discovery process, which we use as an organizational framework in describing applications. We also identify five distinct steps during which developers or users can influence the behavior of a computational discovery system. Rather than criticizing such intervention, as done in the past, we recommend it as the preferred approach to using discovery software. As evidence for the advantages of such humancomputer cooperation, we report seven examples of novel, computeraided discoveries that have appeared in the scientific literature. We consider briefly the role that humans played in each case, then examine one such interaction in more detail. We close by recommending that future systems provide more explicit support for human intervention in the discovery process. Running head: Computational Sci...
The ComputerAided Discovery of Scientific Knowledge
 In Proceedings of the first international conference on discovery science
, 1998
"... . In this paper, we review AI research on computational discovery and its recent application to the discovery of new scientific knowledge. We characterize five historical stages of the scientific discovery process, which we use as an organizational framework in describing applications. We also ident ..."
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Cited by 20 (2 self)
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. In this paper, we review AI research on computational discovery and its recent application to the discovery of new scientific knowledge. We characterize five historical stages of the scientific discovery process, which we use as an organizational framework in describing applications. We also identify five distinct steps during which developers or users can influence the behavior of a computational discovery system. Rather than criticizing such intervention, as done in the past, we recommend it as the preferred approach to using discovery software. As evidence for the advantages of such humancomputer cooperation, we report seven examples of novel, computeraided discoveries that have appeared in the scientific literature, along with the role that humans played in each case. We close by recommending that future systems provide more explicit support for human intervention in the discovery process. 1 Introduction The process of scientific discovery has long been viewed as the pinnacle ...
Toward Fully Automated Fragments of Graph Theory, Graph Theory Notes of New York XLII
 C. E. LARSON
, 2002
"... Abstract. We continue the discussion of three topics initiated in the first part of this paper starting with mathematical aspects of the machine intelligence debate initiated in the books of Roger Penrose. Stability Sorting Patterns are byproducts of Minuteman, a fullerene version of Graffiti which ..."
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Abstract. We continue the discussion of three topics initiated in the first part of this paper starting with mathematical aspects of the machine intelligence debate initiated in the books of Roger Penrose. Stability Sorting Patterns are byproducts of Minuteman, a fullerene version of Graffiti which led to the discovery of a new representation and characterization of the icosahedral C60. Some of the conjectures of Minuteman postulate new properties of stable fullerenes and possibly other materials. We discuss here in greater detail two interpretations of one of the conjectures of Minuteman, one of which was incorrectly claimed to be refuted and the other one, which in spite of being refuted, presumably is approximately correct, suggesting that stable fullerenes tend to have very large separators. Red Burton is a new implementation of Graffiti to teach mathematics Texas style, i.e., by the process of selfdiscovery. This version and particularly its offshoot, Little Red Riding Hood, are suitable for using the program in an almost fully automated manner. Twas brillig, and the slighty toves Did gyre and gimble in the wabe: All mimsy were the borogoves. And the mome raths outgrabe.
Computers and Discovery in Algebraic Graph Theory
 Edinburgh, 2001), Linear Algebra Appl
, 2001
"... We survey computers systems which help to obtain and sometimes provide automatically conjectures and refutations in algebraic graph theory. ..."
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We survey computers systems which help to obtain and sometimes provide automatically conjectures and refutations in algebraic graph theory.
Spanning Trees with Many Leaves and Average Distance
"... In this paper we prove several new lower bounds on the maximum number of leaves of a spanning tree of a graph related to its order, independence number, local independence number, and the maximum order of a bipartite subgraph. These new lower bounds were conjectured by the program Graffiti.pc, a var ..."
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In this paper we prove several new lower bounds on the maximum number of leaves of a spanning tree of a graph related to its order, independence number, local independence number, and the maximum order of a bipartite subgraph. These new lower bounds were conjectured by the program Graffiti.pc, a variant of the program Graffiti. We use two of these results to give two partial resolutions of conjecture 747 of Graffiti (circa 1992), which states that the average distance of a graph is not more than half the maximum order of an induced bipartite subgraph. If correct, this conjecture would generalize conjecture number 2 of Graffiti, which states that the average distance is not more than the independence number. Conjecture number 2 was first proved by F. Chung. In particular, we show that the average distance is less than half the maximum order of a bipartite subgraph, plus onehalf; we also show that if the local independence number is at least five, then the average distance is less than half the maximum order of a bipartite subgraph. In conclusion, we give some open problems related to average distance or the maximum number of leaves