Protein secondary structure prediction using logic-based machine learning
Protein Engineering 5(7), pp. 647-657
The convergence of TD(lambda) for general lambda
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Hard and Easy SAT Problems
Mitchell, David | Selman, Bart
"We report results from large-scale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Our results provide a benchmark for the evaluation of satisfiability-testing procedures." Proc. AAAI-92.
From knowledge bases to decision models
Wellman, M. P. | Breese, J. S. | Goldman, R.
Knowledge Engineering Review, 7 (1), 35-53.
The CLP language and system
Jaffar, J. | Michaylov, S. | Stuckey, P. J. | Yap, R. H. C.
ACM Transactions on Programming Languages and Systems, 14 (3), , 339–395.
Randomized incremental construction of Delaunay and Voronoi diagrams
Guibas, L. J. | Knuth, D. E. | Sharir, M.
Algorithmica, 7, 381–413. See also 17th Int. Coll. on Automata, Languages and Programming, 1990, pp. 414–431.
SETHEO: A high-performance theorem prover
Letz, R. | Schumann, J. | Bayerl, S. | Bibel, W.
JAR, 8 (2), 183-212.
Conditional nonlinear planning
"Work-in-progress on the design of a conditional nonlinear planner is described. CNLP is a nonlinear planner that develops plans that account for foreseen uncertainties. CNLP represents an extension of the conditional planning technique of Warren [75] to the domain of nonlinear planning." In ICAPS-92, pp. 189–197.