On most accounts of expertise, as agents increase their skill, they are assumed to make fewer mistakes and to take fewer redundant or backtracking actions. Contrary to such accounts, in this paper we present data collected from people learning to play the videogame Tetris which show that as skill increases,the proportion of game actions that are later undone by backtracking also increases. Neve...

We propose a new backtracking method called constraint-directed backtracking (CDBT) for solving constraint-satisfaction problems (CSPs). CDBT and chronological back-tracking (BT) share a similar style of instantiating variables (forward) and re-instantiating variables (backward). They diier in that CDBT searches instantiations of variables in a variable set from a given constraint posed on that...

Beam search (BS) is used as a heuristic to solve various combinatorial optimization problems, ranging from scheduling to assembly line balancing. In this paper, we develop a backtracking and an exchange-of-information (EOI) procedure to enhance the traditional beam search method. The backtracking enables us to return to previous solution states in the search process with the expectation of obta...

Backtracking search is a standard mechanism for solving constraint satisfaction problems (CSPs). Over the years a wide range of improvements of generic backtracking have been developed. These improvements have employed a seemingly wide range of insights, each accompanied by its own algorithmic techniques and data structures. In this paper we demonstrate that despite this seeming variety there i...

Pathological dependency cycles occur in state-space planners when control structures cannot efficiently determine a maximal matching for a bipartite operator/binding graph. Without proper search control, the planner will require many computationally expensive backtracks to arrive at a solution. We present a method for improving planning efficiency in the midst of pathological dependency cycles ...

Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that a technique called randomization and restarts can dramatically improve the performance of a backtracking algorithm on some instances. We consider the commonly occurring scenario where one is to solve an ensemble of instances using a backtracking algorith...

Backtracking search is often the method of choice for solving constraint satisfaction and propositional satisfiability problems. Previous studies have shown that portfolios of backtracking algorithms—a selection of one or more algorithms plus a schedule for executing the algorithms—can dramatically improve performance on some instances. In this paper, we consider a setting that often arises in ...

Reconstruct a new route for network services during the handoff process is a fundamental issue of wireless communication. This paper proposes a new rerouting algorithm to achieve a fast handoff based on k-hop backtracking mechanism. The algorithm can dynamically decide the backtracking hops according to the velocity of wireless devices and the current network bandwidth through iterative strateg...

A major drawback of backpropagation through time (BPTT) is the difficulty of learning long-term dependencies, coming from having to propagate credit information backwards through every single step of the forward computation. This makes BPTT both computationally impractical and biologically implausible. For this reason, full backpropagation through time is rarely used on long sequences, and trun...

This is a short note inspired by some ideas and results from [3,6–8]. It is about Parsing Expression Grammars (PEGs) introduced by Ford in [1]. PEG specifies a language by defining for it a parser with limited backtracking. All of the quoted papers contain a detailed introduction to PEG, so it is not repeated here. Backtracking means that if e1 in a choice expression e1/e2 fails, the parser ret...