In large vocabulary continuous speech recognizers the search space needs to be constrained efficiently to make the recognition task feasible. Beam pruning and restricting the number of active paths are the most widely applied techniques for this. In this paper, we present three additional pruning criteria, which can be used to further limit the search space. These new criteria take into account...

Korf, R.E., Multi-player alpha-beta pruning (Research Note), Artificial Intelligence 48 (1991) 99-111. We consider the generalization of minimax search with alpha-beta pruning to non-cooperative, perfect-information games with more than two players. The minimax algorithm was generalized in [2] to the maxn algorithm applied to vectors of n-tuples representing the evaluations for each of the play...

Relative Entropy-based pruning has been shown to be efficient for pruning language models for more than a decade ago. Recently, this method has been applied to Phrase-based Machine Translation, and results suggest that this method is comparable the state-of-art pruning method based on significance tests. In this work, we show that these 2 methods are effective in pruning different types of phra...

Dots-And-Boxes is a well-known and widely-played combinatorial game. While the rules of play are very simple, the state space for even small games is extremely large, and finding the outcome under optimal play is correspondingly hard. In this paper we introduce a Dots-And-Boxes solver which is significantly faster than the current state-of-the-art: over an order-of-magnitude faster on several l...

This paper examines the potential of a neural network coupled with genetic algorithms to recognize the parameters that define the production curve of sheep milk, in which production is time-dependent, using solely the data registered in the animals’ first controls. This enables the productive capacity of the animal to be identified more rapidly and leads to a faster selection process in determi...

We focus on solving two-player zero-sum extensive-form games with perfect information and simultaneous moves. In these games, both players fully observe the current state of the game where they simultaneously make a move determining the next state of the game. We solve these games by a novel algorithm that relies on two components: (1) it iteratively solves the games that correspond to a single...

In this paper we outline a general approach to the study of problem-solving, in which search steps are considered decisions in the same sense as actions in the world. Unlike other metrics in the l i terature, the value of a search step is defined as a real u t i l i t y rather than as a quasiut i l i ty , and can therefore be computed directly f rom a model of the base-level problem-solver. We ...

Recently, rollout-based planning and search methods have emerged as an alternative to traditional tree-search methods. The fundamental operation in rollout-based tree search is the generation of trajectories in the search tree from root to leaf. Game-playing programs based on Monte-Carlo rollouts methods such as “UCT” have proven remarkably effective at using information from trajectories to ma...

Several early game-playing computer programs used forward pruning (i.e., the practice of deliberately ignoring nodes that are believed unlikely to affect a game tree’s minimax value), but this technique did not seem to result in good decision-making. The poor performance of forward pruning presents a major puzzle for AI research on game playing, because some version of forward pruning seems to ...

An eecient parallel algorithm FPM(Fast Parallel Mining) for mining association rules on a shared-nothing parallel system has been proposed. It adopts the count distribution approach and has incorporated two powerful candidate pruning techniques, i.e., distributed pruning and global pruning. It has a simple communication scheme which performs only one round of message exchange in each iteration....