The Strategies for Simple One-Point Ko Situation of Computer Go

[[abstract]]Ko plays a very important role in Go, but most computer Go programs still cannot handle ko fights so far. Utilizing the principle of Minimax procedure, we obtain the best strategies for the simple one-point ko situation, enabling computer Go programs to gain maximum or loss minimum profit when dealing with the simple one-point ko situation. We also discuss in detail the strategies for using ko threats during the process of the ko fight.

A low-cost neural sorting network with O(1) time complexity

[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons and links to sort n data, var epsilon > 0. For large-size problems, it is desirable to have low-cost hardware solutions. In order to solve the sorting problem in constant time and with less hardware-cost, we adopt Leighton's column sort [5] as the main architecture. Then we use Chen and Hsieh's neural network [3] with O(n3) complexity as the lowest-level sub-networks. By using recursive techniques properly, we are able to explore constant-time, low-complexity neural sorting networks.

Optimal algorithms for constructing knight's tours on arbitrary n×m chessboards

AbstractThe knight's tour problem is an ancient puzzle whose goal is to find out how to construct a series of legal moves made by a knight so that it visits every square of a chessboard exactly once. In previous works, researchers have partially solved this problem by offering algorithms for subsets of chessboards. For example, among prior studies, Parberry proposed a divided-and-conquer algorithm that can build a closed knight's tour on an n×n, an n×(n+1) or an n×(n+2) chessboard in O(n2) (i.e., linear in area) time on a sequential processor. In this paper we completely solve this problem by presenting new methods that can construct a closed knight's tour or an open knight's tour on an arbitrary n×m chessboard if such a solution exists. Our algorithms also run in linear time (O(nm)) on a sequential processor

A general interconnection network with the consideration of locality in traffic

[[abstract]]A general interconnection network is proposed, taking into account locality of traffic. The network has log2N-log N maximum intercell delay, but when high locality occurs in the communications, the mean intercell delay decreases to O(1). The problem of how to map processors with a known traffic distribution onto the terminals of the network in order to minimize the mean intercell delay is analyzed and formulated as a quadratic assignment problem. The uses of this network as a partitioner, a permuter, a full switch and a generalized connection network is discussed.

A New Approach for Minimization of binary decision diagrams

[[abstract]]This paper proposes a new approach that successfully finds the optimal variable orderings for almost all reduced ordered binary decision diagrams (BDDs) in the LGSynth91 benchmark circuits with up to 500 variables. All previously known approaches can solve only functions with less than 64 variables. The progress of the new approach is attributable to the concept of randomized algorithms, which significantly reduce the influence of the initial variable ordering on the minimization performance. Furthermore, the features of different BDD minimization algorithms can also be measured as a result. The results are gradually refined during the minimization progress, such that valid approximate results can be derived before a time-consuming process terminates. The performance of the proposed approach is illustrated through its application on LGSynth91 benchmark circuits. Experimental results demonstrate that the randomized algorithm is properly incorporated; thus the performance remains consistent for a large set of benchmark circuits. In addition to providing a feasible BDD minimization algorithm, this paper presents statistical results and analyses that could be helpful for related research.