Sequential Minimax Search for Multi-Layer Gene Grouping

Sequential Minimax Search for a Maximum

The problem formulated below was motivated by that of determining an interval containing the point at which a unimodal function on the unit interval possesses a maximum, without postulating regularity conditions involving continuity, derivatives, etc. Our solution is to give, for every e > 0 and every specified number N of values of the argument at which the function may be observed, a procedur...

Sequential Minimax Search for a Zero of a Convex Function

Multi-domain Topology-Aware Grouping for Application-Layer Multicast

Application-layer multicast (ALM) can solve most of the problems of IP-based multicast. Topology-aware approach of ALM is more attractive because it exploits underlying network topology data to construct multicast overlay networks. In this paper, a novel mechanism of overlay construction called Multi-domain Topology-Aware Grouping (MTAG) is introduced. MTAG manages nodes in the same domain by a...

Best-First Minimax Search

We describe a very simple selective search algorithm for two-player games, called best-first minimax. It always expands next the node at the end of the expected line of play, which determines the minimax value of the root. It uses the same information as alpha-beta minimax, and takes roughly the same time per node generation. We present an implementation of the algorithm that reduces its space ...

Monte Carlo *-Minimax Search

This paper introduces Monte Carlo *-Minimax Search (MCMS), a Monte Carlo search algorithm for turned-based, stochastic, two-player, zero-sum games of perfect information. The algorithm is designed for the class of densely stochastic games; that is, games where one would rarely expect to sample the same successor state multiple times at any particular chance node. Our approach combines sparse sa...