In tree search, depth-first search (DFS) often uses ordering successor heuristics. If the heuristic makes a mistake ordering a bad successor (without goals in its subtree) before good ones (wi th goals in their subtrees), DFS has to unsuccessfully traverse the whole bad subtree before f inding a goal. To prevent this useless work, we present a new strategy called interleaved depthfirst search (...

We can make this algorithm slightly faster (in practice) by checking whether a node is marked before we recursively explore it. This modification ensures that we call DFS(v) only once for each vertex v. We can further modify the algorithm to define parent pointers and other useful information about the vertices. This additional information is computed by two black-box subroutines PREVISIT and P...

Depth-first search of a graph is formalized with function. It is shown that it visits all of the reachable nodes from a given list of nodes. Executable ML code of depth-first search is obtained with code generation feature of Isabelle/HOL. The formalization contains two implementations of depth-first search: one by stack and one by nested recursion. They are shown to be equivalent. The terminat...

Almost ten years ago, Ralf Hinze has written a functional pearl on how to derive backtracking functionality for the purely functional programming language Haskell. In these notes, we show how to arrive at the efficient, two-continuation based backtracking monad derived by Hinze starting from an intuitive inefficient implementation that we subsequently refine using well known program transformat...

The ET* algorithm is a complete evaluation strategy for Datalog programs, which are logic programs without function symbols. The ET* algorithm uses extension tables and depth-first iterative deepening to provide the evaluation of pure function-free logic programs as declarative specifications. Extension tables are a memo facility that the algorithm uses both to cut infinite derivation paths for...

Let K be a set of n non-intersecting objects in 3-space. A depth order of K, if exists, is a linear order < of the objects in K such that if K; L 2 K and K lies vertically below L then K < L. We present a new technique for computing depth orders, and apply it to several special classes of objects. Our results include: (i) If K is a set of n triangles whose xy-projections are alìfat', then a dep...

The two best known and most frequently referenced minimax search methods for game trees are Alpha-Beta [2] and SSS* [6]. The algorithms are quite dissimilar in structure and properties. Alpha-Beta is a depth-first recursive procedure that needs little memory to execute. Although it evaluates more terminal nodes than SSS*, it generally runs considerably faster owing to its low overhead. In contr...

We show how combinatorial search strategies including depth-first, breadth-first and depth-bounded search can be viewed as different implementations of a common algebraic specification that emphasises the compositionality of the strategies. This specification is placed in a categorical setting that combines algebraic specifications and monads. This article appeared in Workshop on Mathematically...

Although dynamic backtracking usually outperforms depth rst search, its performance can be degraded by holding on to partial variable assignments. Although GSAT has diiculties with some asymmetric problems, it typically outperforms minimum connicts.

AI efforts to solve problems with computers which humans routinely handle by employing innate cognitive abilities, pattern recognition, perception and experience, invariably must turn to considerations of search. This Chapter explores search methods in AI, including both blind exhaustive methods and informed heuristic and optimal methods, along with some more recent findings. The search methods...