This paper presents a graph-based backtracking algorithm designed to support constraintbased planning in data production domains. This algorithm performs backtracking at two nested levels: the outerbacktracking following the structure of the planning graph to select planner subgoals and actions to achieve them and the inner-backtracking inside a subproblem associated with a selected action to f...

RecentlyFtwo new backtracking algorithmsF dynamic backtracking (DB) and partial order dynamic backtracking (PDB) have been presented. These algorithms have the property to be additive on disjoint subproblems and yet use only polynomial space. Unlike DBFPDB only imposes a partial search order and therefore appears to have more freedom than DB to explore the search space. HoweverFboth algorithms ...

Percolation threshold of a network is the critical value such that when nodes or edges are randomly selected with probability below the value, the network is fragmented but when the probability is above the value, a giant component connecting a large portion of the network would emerge. Assessing the percolation threshold of networks has wide applications in network reliability, information spr...

We study the mixing rate of non-backtracking random walks on graphs by looking at non-backtracking walks as walks on the directed edges of a graph. A result known as Ihara’s Theorem relates the adjacency matrix of a graph to a matrix related to non-backtracking walks on the directed edges. We prove a weighted version of Ihara’s Theorem which relates the transition probability matrix of a non-ba...

Backtracking influence is influence that zigzags in time. For example, backtracking influence exists when an event E1 makes an event E2 more likely by way of a nomic connection that goes from E1 back in time to an event C and then forward in time to E2. I contend that backtracking influence is redundant in the sense that any existing backtracking influence exerted by E1 on E2 is equivalent to E...

During transcript elongation in vitro, backtracking of RNA polymerase II (RNAPII) is a frequent occurrence that can lead to transcriptional arrest. The polymerase active site can cleave the transcript during such backtracking, allowing transcription to resume. Transcript cleavage is either stimulated by elongation factor TFIIS or occurs much more slowly in its absence. However, whether backtrac...

Because of their occasional need to return to shallow points in a search tree, existing backtracking methods can sometimes erase meaningful progress toward solving a search problem. In this paper, we present a method by which backtrack points can be moved deeper in the search space, thereby avoiding this di culty. The technique developed is a variant of dependency-directed backtracking that use...

We present a runtime intelligent backtracking method for prolog programs to avoid redundant failures The method presented in this paper selects the best choice point as a backtracking point during the failure of a procedure call to avoid the same failure The chosen backtracking is the best choice point that can be determined in runtime during execution of a goal without a further analysis The m...

This paper describes a backtracking strategy for an incremental deterministic transitionbased parser for HPSG. The method could theoretically be implemented on any other transition-based parser with some adjustments. In this paper, the algorithm is evaluated on CuteForce, an efficient deterministic shiftreduce HPSG parser. The backtracking strategy may serve to improve existing parsers, or to a...

Emergence of localized eigenvectors can cause a failure of standard spectral method for graph partitioning. The spectral method using the non-backtracking matrix was proposed as a way to overcome this problem. The numerical experiments on several examples of real networks show that, indeed, the non-backtracking matrix does not exhibit localization of eigenvectors. We show that, however, localiz...