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This paper describes the simulation of described autonomous robots for search and rescue operations. The simulation system is utilized to perform experiments with various control strategies for the robot and team organizations, evaluating the comparative performance of the strategies and organizations. The objective of the robot team is, once deployed in an environment (floor-plan) with multiple rooms, to cover as many rooms as possible. The simulated robots are capable of navigating through the environment, and can communicate using simple messages. The simulator maintains the world, provides each robot with sensory information, and carries out the actions of the robots. The simulator keeps track of the rooms visited by robots and the elapsed time, in order to evaluate the performance of the robot teams. The robot teams are composed of homogenous robots, i.e., identical control strategies are used to generate the behavior of each robot in the team. The ability to deploy autonomous robots, as opposed to humans, in hazardous search and rescue missions could provide immeasurable benefits [ABSTRACT FROM AUTHOR]

An on-line portfolio management algorithm using additive update rule is presented with consideration of proportional transaction costs. After establishing a relationship between transaction costs and the distance of two portfolio vectors, we solve an optimization problem making a balance between high wealth growth rate and low transaction costs. It is shown that the presented portfolio strategy is universal relative to the set of all buy-and-hold portfolios in the sense that it achieves the same asymptotic exponential growth rate of wealth as the best buy-and-hold portfolio determined with hindsight. The simulation examples using the real data from the London Stock Exchange show the efficiency and the computational simplicity of the algorithm. [ABSTRACT FROM AUTHOR]