The determination of the helium discharge detector response to fixed gases

The Beckman Helium Discharge Detector has been found to be sensitive to the fixed gases oxygen, nitrogen, and hydrogen at detection levels 10-100 times more sensitive than possible with a Bow-Mac Thermal Conductivity Detector. Detection levels o~ approximately 1.9 E-4 ~ v/v oxygen, 3.1 E-4 ~ v/v nitrogen, and 3.0 E-3 ~ v/v hydrogen are estimated. Response of the Helium Discharge Detector was not linear, but is useable for quantitation over limited ranges of concentration using suitably prepared working standards. Cleanliness of the detector discharge electrodes and purity of the helium carrier and discharge gas were found to be critical to the operation of the detector. Higher sensitivities of the Helium Discharge Detector may be possible by the design and installation of a sensitive, solid-state electrometer.

Genetic programming for the RoboCup Rescue Simulation System

The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting.