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Tag: Multidisciplinary
Essentials of Game Theory: A Concise Multidisciplinary Introduction (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Price:$32.99– $30.31
(as of Jan 04,2025 10:43:42 UTC – Details)
Publisher : Springer; 1st edition (June 4, 2008)
Language : English
Paperback : 108 pages
ISBN-10 : 3031004175
ISBN-13 : 978-3031004179
Item Weight : 7.1 ounces
Dimensions : 7.52 x 0.25 x 9.25 inchesCustomers say
Customers find the book’s reading style thoughtful and pleasant. They describe it as a good, must-read for anyone looking for Gamification. However, opinions differ on clarity – some find the definitions and concepts clear, while others find explanations of complicated topics unclear and math notations challenging.
AI-generated from the text of customer reviews
Essentials of Game Theory: A Concise Multidisciplinary Introduction (Synthesis Lectures on Artificial Intelligence and Machine Learning)Game theory is a powerful tool used in various fields such as economics, political science, biology, and computer science. Understanding the fundamentals of game theory can provide insights into strategic decision-making and help in predicting outcomes in competitive situations.
In this concise and multidisciplinary introduction, the essentials of game theory are presented in a clear and accessible manner. This book is part of the Synthesis Lectures on Artificial Intelligence and Machine Learning series, making it a valuable resource for students, researchers, and practitioners in these fields.
Topics covered in this book include:
– The basics of game theory, including types of games and strategies
– Nash equilibrium and its applications
– Extensive-form games and imperfect information
– Cooperative games and bargaining
– Evolutionary game theory and its applicationsBy providing a comprehensive overview of game theory and its applications, this book serves as a valuable resource for anyone looking to enhance their understanding of strategic decision-making and competitive interactions. Whether you are a student, researcher, or practitioner, this book will deepen your knowledge and broaden your perspective on game theory.
#Essentials #Game #Theory #Concise #Multidisciplinary #Introduction #Synthesis #Lectures #Artificial #Intelligence #Machine #Learning,machine learning: an applied mathematics introduction
Multi-disciplinary Trends in Artificial Intelligence: 13th International Confere
Multi-disciplinary Trends in Artificial Intelligence: 13th International Confere
Price : 67.04
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nce on Artificial Intelligence and Computational IntelligenceThe 13th International Conference on Artificial Intelligence and Computational Intelligence (AICI 2022) is set to take place in Beijing, China from August 26-28, 2022. This conference will bring together researchers, scholars, and practitioners from around the world to discuss the latest trends and developments in the field of artificial intelligence and computational intelligence.
One of the key themes of this year’s conference is multi-disciplinary trends in artificial intelligence. As AI continues to advance and evolve, it is increasingly intersecting with other disciplines such as neuroscience, psychology, biology, and economics. This interdisciplinary approach is leading to exciting new possibilities and applications for AI technology.
Some of the topics that will be covered at AICI 2022 include:
– Neuro-inspired AI models
– AI and cognitive psychology
– AI and computational biology
– AI and behavioral economics
– AI and social sciencesResearchers and practitioners from a wide range of disciplines are invited to submit their research papers, posters, and demos to the conference. The goal is to foster collaboration and cross-pollination of ideas among different fields, ultimately leading to new breakthroughs and innovations in AI.
If you are interested in learning more about multi-disciplinary trends in artificial intelligence, be sure to mark your calendars for AICI 2022. Stay tuned for updates on keynote speakers, workshops, and special sessions as the conference approaches. We look forward to seeing you in Beijing!
#Multidisciplinary #Trends #Artificial #Intelligence #13th #International #Confere, artificial intelligence
Responsible Implementations of Generative AI for Multidisciplinary Use
Price: $365.00
(as of Dec 26,2024 19:08:33 UTC – Details)
ASIN : B0DHSYQR4H
Publisher : IGI Global (September 18, 2024)
Language : English
Hardcover : 472 pages
ISBN-13 : 979-8369391730
Item Weight : 2.27 pounds
Dimensions : 7 x 1 x 10 inches
Generative AI, also known as artificial intelligence that can generate creative outputs such as images, text, or music, has the potential to revolutionize various industries and fields. However, its implementation must be done responsibly to ensure ethical considerations are taken into account and to mitigate any potential negative consequences. In this post, we will discuss some key principles for the responsible implementation of generative AI for multidisciplinary use.1. Transparency and Accountability: Organizations utilizing generative AI should be transparent about how the technology is being used and be accountable for its outcomes. This includes disclosing the data used to train the AI, the algorithms being employed, and any biases or limitations present in the system.
2. Ethical Considerations: It is crucial to consider the ethical implications of using generative AI, especially in sensitive areas such as healthcare, finance, or law enforcement. Decision-makers should assess the potential impact on individuals, communities, and society as a whole, and take steps to minimize harm.
3. Data Privacy and Security: Generative AI systems often rely on vast amounts of data to function effectively. Organizations must prioritize data privacy and security to protect sensitive information and ensure compliance with regulations such as GDPR and HIPAA.
4. Human Oversight and Control: While generative AI can produce impressive results autonomously, human oversight is essential to ensure that the technology is used responsibly and ethically. Human experts should be involved in the design, implementation, and evaluation of generative AI systems.
5. Collaborative Approach: Multidisciplinary teams, including experts from various fields such as data science, ethics, law, and psychology, should collaborate to develop and deploy generative AI solutions. This interdisciplinary approach can help identify potential risks and ensure that the technology is used in a responsible manner.
By following these principles, organizations can harness the power of generative AI for multidisciplinary use while also upholding ethical standards and protecting the well-being of individuals and society. Responsible implementation of generative AI is essential to unlock its full potential and drive positive impact across diverse industries and fields.
#Responsible #Implementations #Generative #Multidisciplinary
Transfer of Learning from a Modern Multidisciplinary Perspective
Transfer of Learning from a Modern Multidisciplinary Perspective
Price : 19.99
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Transfer of learning is a crucial concept in education that involves applying knowledge and skills learned in one context to new situations. From a modern multidisciplinary perspective, it is essential to consider various factors that can influence the transfer of learning, such as cognitive psychology, neuroscience, and educational technology.Cognitive psychology plays a significant role in understanding how learning takes place and how knowledge is stored and retrieved in the brain. By examining cognitive processes such as memory, attention, and problem-solving, educators can design instructional strategies that facilitate the transfer of learning. For example, using spaced repetition and retrieval practice can enhance long-term retention and transfer of knowledge to new contexts.
Neuroscience research has also shed light on how the brain processes information and adapts to new learning experiences. By understanding the neural mechanisms involved in learning and memory, educators can optimize instructional practices to promote transfer of learning. For instance, providing feedback and reinforcement can strengthen neural connections and facilitate the transfer of skills from training to real-world situations.
Educational technology offers innovative tools and resources that can support the transfer of learning in diverse ways. Virtual reality simulations, gamified learning platforms, and online collaboration tools can provide authentic learning experiences that encourage students to apply their knowledge and skills in practical contexts. By integrating technology into the learning environment, educators can create opportunities for transfer of learning across different domains and disciplines.
In conclusion, the transfer of learning from a modern multidisciplinary perspective involves leveraging insights from cognitive psychology, neuroscience, and educational technology to enhance the effectiveness of education and training. By considering these factors and incorporating evidence-based practices into instructional design, educators can foster deep learning and support students in applying their knowledge and skills to solve real-world problems.
#Transfer #Learning #Modern #Multidisciplinary #Perspective
Responsible Implementations of Generative AI for Multidisciplinary Use by Lovele
Responsible Implementations of Generative AI for Multidisciplinary Use by Lovele
Price : 492.74
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Generative AI technology has revolutionized many industries, from art and music to healthcare and finance. However, with great power comes great responsibility. As a company that specializes in multidisciplinary applications of AI, Lovele is committed to implementing this technology in a responsible and ethical manner.Here are some key principles that guide our approach to using generative AI for multidisciplinary purposes:
1. Transparency: We believe in being transparent about the use of generative AI in our products and services. We clearly communicate how AI is being used and what data is being collected and used to train our models.
2. Privacy: Protecting the privacy of our users is paramount. We ensure that data is collected and used in compliance with data protection regulations and that user consent is obtained before using their data for AI training.
3. Bias mitigation: We are dedicated to mitigating bias in our AI models by ensuring diverse and representative training data, regular audits of our models, and ongoing monitoring for bias in our outputs.
4. Accountability: We take responsibility for the outcomes of our AI systems and are committed to addressing any issues that arise promptly and transparently.
5. Collaboration: We believe in working collaboratively with experts in various fields to ensure that our AI systems are used in ways that benefit society and minimize harm.
By following these principles, Lovele is able to harness the power of generative AI for multidisciplinary use in a responsible and ethical manner. We remain committed to upholding these values as we continue to innovate and develop new applications for this transformative technology.
#Responsible #Implementations #Generative #Multidisciplinary #Lovele
Responsible Implementations of Generative AI for Multidisciplinary Use by Lovele
Responsible Implementations of Generative AI for Multidisciplinary Use by Lovele
Price : 376.67
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Generative Artificial Intelligence (AI) has the potential to revolutionize various industries and fields through its ability to create realistic and innovative content. However, it is important to approach the implementation of generative AI with caution and responsibility, especially when considering its use in multidisciplinary settings.At Lovele, we believe in harnessing the power of generative AI for the greater good while ensuring ethical and responsible practices. Here are some key considerations for implementing generative AI in a multidisciplinary context:
1. Transparency: It is crucial to be transparent about the use of generative AI and the limitations of the technology. This includes clearly communicating how AI-generated content is created and the potential biases or errors that may arise.
2. Data privacy and security: Protecting sensitive data and ensuring user privacy should be a top priority when using generative AI. Implementing robust security measures and complying with data protection regulations is essential.
3. Ethical considerations: Consider the ethical implications of using generative AI, such as the potential impact on jobs, societal norms, and cultural sensitivity. It is important to proactively address any ethical concerns that may arise.
4. Collaboration and interdisciplinary approaches: To maximize the benefits of generative AI in a multidisciplinary setting, foster collaboration between experts from different fields. This can help ensure that AI-generated content meets the diverse needs and requirements of various disciplines.
5. Continuous monitoring and evaluation: Regularly monitor the performance of generative AI systems and evaluate their impact on multidisciplinary projects. This can help identify any issues or biases and make necessary adjustments to improve the technology.
By following these responsible implementation practices, Lovele aims to leverage generative AI for multidisciplinary use in a way that benefits society and respects ethical standards. We are committed to promoting the responsible and ethical use of AI for the betterment of all.
#Responsible #Implementations #Generative #Multidisciplinary #Lovele
