In this paper, MAZCS – a MultiAgent system that learns using ZCS – is used for social modelling on the “El Farol” Bar problem. Experiments with ten agents and different goal settings for the problem show that MAZCS is always able to solve it and emergent behaviour derives from the autonomous control of each agent. The results are divided into two different analysis scopes: macro and micro-level...

As a genetics-based machine learning technique, zeroth-level classifier system (ZCS) is based on a discounted reward reinforcement learning algorithm, bucket-brigade algorithm, which optimizes the discounted total reward received by an agent but is not suitable for all multi-step problems, especially large-size ones. There are some undiscounted reinforcement learning methods available, such as ...

An Isolated ZVS/ZCS bidirectional DC-DC converter for DC Uninterruptable Power supplies is presented in this paper. The usual way to avoid a computer shutdown during the mains failure is to connect an ac uninterruptible power supply (UPS). Alternatively, in this paper, a simple and high efficiency dc UPS is presented by an isolated bidirectional soft-switching dc-dc converter. The bidirectional...

Learning Classifier Systems use reinforcement learning, evolutionary computing and/or heuristics to develop adaptive systems. This paper extends the ZCS Learning Classifier System to improve its internal modelling capabilities. Initially, results are presented which show performance in a traditional reinforcement learning task incorporating lookahead within the rule structure. Then a mechanism ...

Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because...

Learning Classifier Systems use reinforcement learning, evolutionary computing and/or heuristics to develop adaptive systems. This paper extends the ZCS Learning Classifier System to improve its internal modelling capabilities. Initially, results are presented which show performance in a traditional reinforcement learning task incorporating lookahead within the rule structure. Then a mechanism ...

LLC (Inductor-inductor-capacitor) resonant converter has lots of advantages over other type of resonant converters which include high efficiency, more reliable and have high power density. This paper presents the design and analysis of a full bridge LLC resonant converter. In addition to the operational principle, the ZVS and ZCS conditions are also explained with the DC characteristics. Simula...

The analysis for a given Soft-Switching DC-DC converter family can be generalized using the switching-cell of that family leading to a number of generalized equations with a Transformation Table. In this paper, the concept of generalization and step by step procedure for the generalized process are discussed and applied to selected soft-switching families such as ZVS-QRC, ZCS-QRC, ZCS-CC QSW,ZV...

The development of low-cost semiconductor photocatalysts for highly efficient and durable photocatalytic H2 evolution under visible light is very challenging. In this study, we combine metallic Ni3C cocatalysts with twin nanocrystal Zn0.5Cd0.5S (ZCS) solid solution homojunctions an visible-light-driven production by a simple approach. As-synthesized Zn0.5Cd0.5S-1% (ZCS-1) heterojunction/homojun...

This paper proposes a novel phase-shifted zerovoltage and zero-current-switching (ZVZCS) pulsewidth modulation full-bridge converter, which realizes ZVS for the leading leg and ZCS for the lagging leg. A blocking capacitor is added in series with the primary winding of the transformer to make the primary current decay to zero during zero state to ensure ZCS for the lagging leg. In order to prev...