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Heidi Newton Peter Andreae Artificial Intelligence
© Peter Andreae Overview Talk about three of the topics from the online book AI with language: Chatterbots AI for selling stuff: Association rules AI for games: Basic game search 2
© Peter Andreae AI with language Using language is one of the distinguishing features of human intelligence. Making computers use language well is hard! We have not solved this problem yet Would it be useful to have computers that could use human language? Where? 3
© Peter Andreae Chatterbots What are they? general vs domain specific fixed vs learning Let’s try some: Eliza: ALICE: Cleverbot: Work in pairs, chat with them, try at least two bots 4
© Peter Andreae Chatterbots Which was best? Were they any good? How could you tell it wasn’t a person? What were its limitations? 5
© Peter Andreae Turing Test Turing test: the most famous test for successful artificial intelligence Based on computers using language A Human and a Computer, each try to convince a judge that they are the human, communicating only over a typed chat session If the judge is fooled, then the computer must be intelligent. Book describes an activity for students to run a Turing test using one of the chatterbots (not time for us to do it here) 6
© Peter Andreae 2. Association Rules What does Amazon (and many online retailers) do when you click on an item? How do supermarkets decide where to place items? Note: Recommender Systems are closely related. 7
© Peter Andreae Association Rule Learning Machine learning algorithms look for patterns in purchasing data. If 30% of the people who buy an LED torch also buy rechargable batteries, then Whenever a person selects an LED torch, suggest that they might want to buy rechargable batteries. Should you recommend torches if they buy batteries? If 20% of people who buy corn chips also buy salsa dip, then put salsa dip on a shelf near the corn chips to increase sales If 80% of the people who buy milk also buy bread, then put them on opposite sides of the store to make people pass by as many other shelves as possible 8
© Peter Andreae Association Rule Learning How do you find the associations? How do you tell if they are “strong enough” We are planning an activity for the book involving searching for associations in supermarket reciepts 9
© Peter Andreae 3. AI for games Lots of different applications of AI in games Games were part of AI research from the beginning Modern computer games need even more AI. Min-Max search is a basic AI game playing strategy Applicable to 2-person board games Fundamental to the AI chess playing systems (eg Deep Blue) Paper and pencil activities to explore this. 10
© Peter Andreae Min Max search for O’s & X’s Suppose it is O’s turn and the board looks like this What should O do? 11
© Peter Andreae O’s choices X’s Choices win lose win It’s O’s turn: what should O do? Search forwards to explore all the options
© Peter Andreae O’s choice X’s Choice It’s O’s turn: what should O do? Work backwards to determine status of earlier positions X will try to make O lose
© Peter Andreae O’s choices O’s choice X’s Choice It’s O’s turn: what should O do? Work backwards to determine status of earlier positions O will try to win
© Peter Andreae O’s choice X’s Choices It’s O’s turn: what should O do? Work backwards to determine status of earlier positions X will try to make O lose
© Peter Andreae O’s choice It’s O’s turn: what should O do? Work backwards to determine status of earlier positions O will try to win
© Peter Andreae More Min Max Search What happens if you can’t search all the way to the end? Have to stop and measure how good the board looks. Eg, a piece count Work backwards with the minimum score (for opponent’s turn) maximum score (for player’s turn)
© Peter Andreae Black’s turn 0 advantage +1 +2
© Peter Andreae Black’s turn 0 advantage
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