Digital Commons Network^™

Catgame: A Tool For Problem Solving In Complex Dynamic Systems Using Game Theoretic Knowledge Distribution In Cultural Algorithms, And Its Application (Catneuro) To The Deep Learning Of Game Controller, Faisal Waris

Wayne State University Dissertations

Cultural Algorithms (CA) are knowledge-intensive, population-based stochastic optimization methods that are modeled after human cultures and are suited to solving problems in complex environments. The CA Belief Space stores knowledge harvested from prior generations and re-distributes it to future generations via a knowledge distribution (KD) mechanism. Each of the population individuals is then guided through the search space via the associated knowledge. Previously, CA implementations have used only competitive KD mechanisms that have performed well for problems embedded in static environments. Relatively recently, CA research has evolved to encompass dynamic problem environments. Given increasing environmental complexity, a natural question arises …

The Use Of Cultural Algorithms To Learn The Impact Of Climate On Local Fishing Behavior In Cerro Azul, Peru, Khalid Kattan

Wayne State University Dissertations

Recently it has been found that the earth’s oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2019 has become the warmest year on record for the earth’s oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [40].

The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of …

Evolving Heterogeneous And Subcultured Social Networks For Optimization Problem Solving In Cultural Algorithms, Yousof Gawasmeh

Wayne State University Dissertations

Cultural Algorithms are computational models of social evolution based upon principle of Cultural Evolution. A Cultural Algorithm are composed of a Belief Space consisting of a network of active and passive knowledge sources and a Population Space of agents. The agents are connected via a social fabric over which information used in agent problem solving is passed. The knowledge sources in the Belief Space compete with each other in order to influence the decision making of agents in the Population Space. Likewise, the problem solving experiences of agents in the Population Space are sent back to the Belief Space and …