Artificial Intelligence. Shobhanjana Kalita Dept. of Computer Science & Engineering Tezpur University
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1 Artificial Intelligence Shobhanjana Kalita Dept. of Computer Science & Engineering Tezpur University
2 What is AI? What is Intelligence? The ability to acquire and apply knowledge and skills (definition by Google) Eg: learn the vocabulary and grammar of a language; speak/write in that language Intelligent Behavior Perception Thinking/ reasoning Learning Acting Communicating
3 Artificial Intelligence Artificial Intelligence, broadly defined, is concerned with intelligent behaviour in artifacts Nils J Nilsson Artificial Intelligence is the study of the computations that make it possible to perceive, reason and act Patrick H Winston Four approaches to AI Russell and Norvig Four approaches to AI Russell and Norvig Systems that think like humans Systems that think rationally Systems that act like humans Systems that act rationally
4 Thinking like humans The cognitive modelling approach How does the human mind work Introspection Psychological Experiments Design programs that follow the theory of the human mind Design programs that follow the theory of the human mind Cognitive science
5 Acting like humans The Turing test approach Can machines think? Are there imaginable digital computers which would do well in the imitation game? Design programs that are smart enough to fool a human Design programs that are smart enough to fool a human Natural Language Processing Knowledge Representation Automated Reasoning Machine Learning
6 Acting like humans ELIZA a Rogerian psychotherapist chat designed in Loebner Prize for conversational intelligence : chatterbots Winner of Loebner Prize 2016 Mitsuku
7 Thinking rationally The laws of thought approach Aristotle s reasoning processes Logic Define the laws of thought in formal logic design programs that can reason and solve problems formulated in such logical notation. Socrates is man. All men are mortal. Therefore, Socrates is mortal Difficulty in stating informal knowledge in formal terms in presence of uncertainties Theoretical solution is not the same as practically solving the problem
8 Acting Rationally The rational agent approach Acting rationally is to act so as to achieve one s goals given one s beliefs AI is study and construction of rational agents that perceives and acts Thinking rationally + Acting humanly More general + clearly defined
9 A brief history Started with the Dartmouth Summer Project in 1956 organized by John McCarthy a 10 man study of artificial intelligence Began with building systems designed to refute claims of the form No machine could ever do X! Small systems that achieve X in a microworld Prove theorems: Machines can only think numerically ELIZA- impersonate a Rogerian psychotherapist Compose music Drive cars STANDUP Crack original jokes! (2007) Q:What do you get when you cross an optic with a mental object? A: Eye-dea
10 A brief history AI resurged with proliferation of expert systems Rule based programs that made simple inferences from a knowledge of facts Knowledge base is elicited from human domain experts and painstakingly hand-coded in formal language Support tools for decision makers First successful form of AI software Medical diagnosis Design of CPU Logic Disadvantage: knowledge acquisition
11 A brief history Neural networks and genetic algorithms Machine learning Decision trees Logistic regression models Support Vector Machines k-nearest Neighbour regression
12 State of the art AI outperforms human intelligence in Game-playing Chess: Deep Blue 1997 Heuristic search rather than strategy making Go: Until 2012 only strong-amateur levels could be acieved In 2017, Google s (DeepMind) AlphGo defeats World No. In 2017, Google s (DeepMind) AlphGo defeats World No. 1 Go player in a 3 match-series Poker: Until recently computers have been regarded bad at poker. In 2017, DeepStack beat professional poker players.
13 State of the art Progress in other fields have been slow and solutions are more complicated Analyzing visual scenes Recognizing objects Robot interaction in natural environment Commonsense Natural Language Understanding It is now often thought that achieving a fully human level performance on these tasks is an AI-complete problem, meaning that the difficulty of solving these problems is essentially equivalent to the difficulty of building generally human-level intelligent machines Nick Bostrom, Superintelligence
14 State of the art Some fields where AI has made sufficient progress Speech Recognition : Google Now, Apple s Siri Machine translation : Google translator Face Recognition : Automated border crossings in Europe and Australia Theorem proving and equation solving Intelligent scheduling Google s Search engine Not a very sharp demarcation between software and AI systems If components involve classifiers, search algorithms, planners, solvers, representational frameworks etc. that can be used for future general aritificial intelligence
15 Dreams and Dreamers The quest for artificial intelligence (AI) begins with dreams as all quests do. People have long imagined machines with human abilities automata that move and devices that reason. Humanlike machines are described in many stories and are pictured in sculptures, paintings, and drawings The quest for artificial intelligence, quixotic or not, begins with dreams like these. But to turn dreams into reality requires usable clues about how to proceed. Fortunately, there were many such clues, as we shall see. - Nils J. Nilsson, Quest for Artificial Intelligence : A History of Ideas and Achievements
16 References Artificial Intelligence: A new synthesis. Nils J Nilsson Artificial Intelligence: A modern approach. Russell and Norvig Superintelligence: Paths Dangers and Strategies. Nick Bostrom planets-best-human-go-player-ke-jie/
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