A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan non-intersecting parts of the global search space. Search processes are generated dynamically, started by the initializing agent, and by any number of agents during searc...

Beam searches are a very effective algorithm for solving problems that prove intractable to complete algorithms like weighted A* and greedy search. Unfortunately, the inadmissible pruning that is the hallmark of a beam search makes the algorithm incomplete. Existing complete extensions to beam search expand pruned nodes systematically according to generation order. Selecting pruned nodes to exp...

In this paper we consider the K-d tree-based backtracking search algorithm and study its performance in the context of vector quantization encoding of speech waveform. We discuss the basic algorithm in detail and highlight the features of optimization as observed from theoretical analysis and from the empirical performance of the backtracking search. It is seen that, despite the 2K dependence o...

A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan non-intersecting parts of the global search space. Each SP is represented by a unique data structure, containing a current partial assignment (CPA), that is circulated am...

This paper proposes the utilization of randomized backtracking within complete backtrack search algorithms for propositional satisfiability (SAT). In recent years, randomization has become pervasive in SAT algorithms. Incomplete algorithms for SAT, for example the ones based on local search, often resort to randomization. Complete algorithms also resort to randomization. These include state-of-...

Consider an infinite binary search tree in which the branches have independent random costs. Suppose that we must find an optimal (cheapest) or nearly optimal path from the root to a node at depth n. Karp and Pearl [1983] show that a bounded-lookahead backtracking algorithm A2 usually finds a nearly optimal path in linear expected time (when the costs take only the values 0 or 1). From this suc...