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• What is Artificial Intelligence? – Depends on your perspective... • Philosophical: a method for modeling intelligence • Psychological: a method for studying human cognition • Engineering: a set of methodologies for building complex programs • Philosophical Perspective: a method for modeling intelligence – How do you define “intelligence”? • • • • • • ideal: syllogisms...laws of thought...logic need for embodiment? mind-body duality (Descartes) physical brain required? Chinese Room experiment Symbol Systems Hypothesis (Simon and Newell) grounding, mechanization, novelty, adaptiveness, free will? soul? animal intelligence? – operational definition: acting intelligent • Turing test; what is the correct measuring stick? – no contact, response characteristics, news, humor, gender... • Eliza, chatter bots, Loebner prize, Deep Blue • Psychological Perspective: a method for studying human cognition – strengths: • • • • perception, ambiguity, interpretation ill-formed problems; weighing multiple criteria judgement, common-sense, expertise “insight”, analogy, Eureka effect – weaknesses: • calculations • limited, selective, and maleable memory • confirmation bias; role of emotions? – behaviorism vs. info-processing metaphor (I/O, internal rep) – connection to language • Sapir-Whorf hypothesis (verbal representations) • concepts, intension/meaning, maps, skills, automation • Engineering Perspective: a method for building complex programs – need more than just C++ or java (or OOP) – search algorithms, inference techniques, methods for dealing with uncertainty... – knowledge-based programming • • • • Feigenbaum: “In the knowledge is the power” high-level programming languages, expressiveness expert systems, logic, McCarthy real-world knowledge bases, ontologies, Cyc – intelligent agents: decision-making – control theory, “cybernetics,” Kalman filters – decision theory: Bayes, Markov • Relationships of AI to other fields: – Economics • rational decision-making; satisficing (Simon) – Mathematics • computability; Godel’s Incompleteness Theorem; logic and number theory; Leibnitz – Neuroscience • neural networks, Minsky • connectionism, distributed representations, grounding