Artificial Intelligence CSB2104 Past Paper PDF

# Artificial Intelligence CSB2104 ## **BADR UNIVERSITY IN ASSIUT** ## **جامعة بدر بأسيوط** ### Prof. Abdel-Rahman Hedar # Introduction Chapter 1 ## **Contents** - What is AI? - What tasks require AI? - How to achieve AI? - Branches of AI - AI Foundations - AI History ## **What is AI?** A diag...

# Artificial Intelligence CSB2104 ## **BADR UNIVERSITY IN ASSIUT** ## **جامعة بدر بأسيوط** ### Prof. Abdel-Rahman Hedar # Introduction Chapter 1 ## **Contents** - What is AI? - What tasks require AI? - How to achieve AI? - Branches of AI - AI Foundations - AI History ## **What is AI?** A diagram showing a four-quadrant chart with "Thinking Humanly" and "Thinking Rationally" along the top and "Acting Humanly" and "Acting Rationally" along the bottom: The top axis is labelled Thinking Humanly and Thinking Rationally. The left axis is labelled Acting Humanly and the bottom is labelled Acting Rationally. ## **Acting Humanly: The Turing Test** - Alan Turing's 1950 article Computing Machinery and Intelligence discussed conditions for considering a machine to be intelligent. - "Can machines think?" *or* "Can machines behave intelligently?" - The Turing test (The Imitation Game) is an operational definition of intelligence. - Computer needs: Natural language processing, knowledge representation, automated reasoning, and machine learning. ## **Other AI Perspectives** - Thinking Humanly: Cognitive Science - Thinking Rationally: Laws of Thought - Acting Rationally: The Rational Agent ## **AI** AI is the science and engineering of making intelligent machines which can perform tasks that require intelligence when performed by humans. ## **What tasks require AI?** ## **Tasks that require AI** - Solving a differential equation - Brain surgery - Inventing stuff - Playing Wheel of Fortune - What about walking? - What about pulling your hand away from fire? - What about watching TV? - What about day dreaming? ## **How to achieve AI?** ## **How to achieve AI?** - How is AI research done? - AI research has both theoretical and experimental sides. - The experimental side has both basic and applied aspects. - There are two main lines of research: - **Biological:** Based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. - **Phenomenal:** Based on studying and formalizing common sense facts about the world and the problems that the world presents to the achievement of goals. - The two approaches interact to some extent, and both should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] ## **Branches of AI** ## **Branches of AI** - Logical AI - Search - Natural language processing - Pattern recognition - Knowledge representation - Inference - From some facts, others can be inferred. - Automated reasoning - Learning from experience - Planning: To generate a strategy for achieving some goal - Ontology: The study of the kinds of things that exist. - *In AI, the programs and sentences deal with various kinds of objects, and we study what these kinds are and what their basic properties are.* - Genetic programming - Emotions! ## **AI Foundations** ## **The foundations of artificial intelligence – Part I** - **Philosophy** - Can formal rules be used to draw valid conclusions? - How does the mind arise from a physical brain? - Where does knowledge come from? - How does knowledge lead to action? - **Mathematics** - What are the formal rules to draw valid conclusions? - What can be computed? - How do we reason with uncertain information? ## **The foundations of artificial intelligence – Part II** - **Economics** - How should we make decisions to maximize the payoff? - How should we do this when others may not go along? - How should we do this when the payoff may be far in the future? - **Neuroscience** - How do brains process information? - **Psychology** - How do humans and animals think and act? ## **The foundations of artificial intelligence – Part III** - **Computer engineering** - How can we build an efficient computer? - **Control theory and cybernetics** - How can artifacts operate under their own control? - **Linguistics** - How does language relate to thought? ## **AI History** ## **The history of artificial intelligence** - The history of AI has had cycles of success, misplaced optimism, and resulting cutbacks in enthusiasm and funding. - There have also been cycles of introducing new creative approaches and systematically refining the best ones. - AI has advanced more rapidly in the past decade because of greater use of the scientific method in experimenting with and comparing approaches. - Recent progress in understanding the theoretical basis for intelligence has gone hand in hand with improvements in the capabilities of real systems. - The subfields of AI have become more integrated, and AI has found common ground with other disciplines. ## **Potted history of AI – Part I** - **1943:** McCulloch & Pitts: Boolean circuit model of brain - **1950:** Turing's "Computing Machinery and Intelligence" and Neural network - **1952-69:** Look, Ma, no hands! - **1950s:** Early AI programs, including Samuel's checkers program - **1956:** Dartmouth meeting: "Artificial Intelligence" adopted ## **Potted history of AI – Part II** - **1965:** Robinson's complete algorithm for logical reasoning - **1966-74:** AI discovers computational complexity and Neural network research almost disappears - **1969-79:** Knowledge-based systems - **1980-88:** Expert systems industry booms - **1988-93:** Expert systems industry busts: "AI Winter" ## **Potted history of AI – Part III** - **1985-95:** Neural networks return to popularity - **1988:** Probability, ALife, GAs, soft computing, and Machine learning - **1995:** Agents, agents, everywhere - **2003:** Human-level AI back on the agenda - **2001-:** Big data - **2011-:** Deep Learning ## **Conclusion** - Different people approach AI with different goals in mind. Two important questions to ask are: - Are you concerned with thinking or behaviour? - Do you want to model humans or work from an ideal standard? - In this course, we adopt the view that intelligence is concerned mainly with rational action. - Ideally, an intelligent agent takes the best possible action in a situation. - We study the problem of building agents that are intelligent in this sense. ## **Questions & Comments** - **Abdel-Rahman Hedar** - **[email protected]** - **https://shorturl.at/ntl2x**