Introduction Artificial Intelligence For Everyone Class 11

A Textbook of Artificial Intelligence for Class 11

Artificial Intelligence (AI) is being widely recognized to be the power that will fuel the future global digital economy. AI in the past few years has gained geostrategic importance and a large number of countries are striving hard to stay ahead with their policy initiatives to get their country already. AI is a continually advancing and expanding field and AI readiness will lead to better opportunities and increased levels of understanding. It will help them visualize jobs of the future and prepare for them. Its multidisciplinary nature will help to make connections between all other subjects thereby adding value and giving a different perspective for all. The CBSE curriculum focuses on building AI readiness in young minds. The importance of skill-based education and the value of project-related work is clear in order to "effectively harness the potential of AI in a sustainable manner to make India's next-generation 'AI ready'. AB a beginning in this direction, CBSE introduced Artificial Intelligence starting from Class VI onward. Students should opt for this curriculum to become future-ready and become at par with their counterparts at a global level. The aim is to strive together to make our students future-ready and help they work on incorporating Artificial Intelligence to improve their learning experience. Goyal Brothers Prakashan

An Introduction to Universal Artificial Intelligence

An Introduction to Universal Artificial Intelligence provides the formal underpinning of what it means for an agent to act intelligently in an unknown environment. First presented in Universal Algorithmic Intelligence (Hutter, 2000), UAI offers a framework in which virtually all AI problems can be formulated, and a theory of how to solve them. UAI unifies ideas from sequential decision theory, Bayesian inference, and algorithmic information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI is the theoretical gold standard for intelligent behavior. The book covers both the theoretical and practical aspects of UAI. Bayesian updating can be done efficiently with context tree weighting, and planning can be approximated by sampling with Monte Carlo tree search. It provides algorithms for the reader to implement, and experimental results to compare against. These algorithms are used to approximate AIXI. The book ends with a philosophical discussion of Artificial General Intelligence: Can super-intelligent agents even be constructed? Is it inevitable that they will be constructed, and what are the potential consequences? This text is suitable for late undergraduate students. It provides an extensive chapter to fill in the required mathematics, probability, information, and computability theory background.

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