Building-Block Supply in Genetic Programming

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This paper analyzes building block supply in the initial population for genetic programming. Facetwise models for the supply of a single schema as well as for the supply of all schemas in a partition are developed. An estimate for the population size, given the size (or size distribution) of trees, that ensures the presence of all raw building blocks with a given error is derived using these facetwise models. The facetwise models and the population sizing estimate are verified with empirical results.

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

Building-Block Supply in Genetic Programming

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Increase engagement and revenue with Muvi Live Paywall! In this presentation, we will explore the five key benefits of using Muvi Live Paywall to monetize your live streams. You'll learn how Muvi Live Paywall can help you: Monetize your live content easily: Set up pay-per-view access to your live streams and start generating revenue from your content. Increase audience engagement: Provide exclusive, premium content behind the paywall to keep your viewers engaged. Gain valuable viewer insights: Track viewer data and analytics to better understand your audience and tailor your content accordingly. Reduce content piracy: Muvi Live Paywall's security features help protect your content from unauthorized distribution. Streamline your workflow: The all-in-one platform simplifies the process of managing and monetizing your live streams. With Muvi Live Paywall, you can take control of your live stream monetization and create a sustainable business model for your content. Learn more about Muvi Live Paywall and start generating revenue from your live streams today!

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Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

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