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CS 357 – Intro to Artificial Intelligence Text: “Artificial Intelligence: A Modern Approach” Russell and Norvig. Course Goals Learn about AI, search techniques, planning, optimization of choice, logic, Bayesian probability theory, learning, etc. Learn skills applicable to other fields of computer science Have fun. What is (Artificial) Intelligence? No agreed upon scientific definition, except that intelligence is demonstrated by people AI has traditionally been a field trying to solve problems that people are good at (and that other things are not good at). Should we try to do it the same way as people? Can we do better than people? Can a Machine Be Intelligent? Ongoing Argument Weak AI – Machines can be made to act as if they were intelligent Strong AI – Machines that act intelligently, have real, conscious minds. Does computation = intelligence? Is a spider intelligent? Are the genes of a human intelligent? Biological Naturalism (phisicalism, materialism) - "Brains Cause Minds" p.819 The Turing test. Acting Humanly: The Turing test (1950) “Computing machinery and intelligence”: Can machine’s think? or Can machines behave intelligently? An operational test for intelligent behavior: the Imitation Game Predicted that by the year 2000, a machine would have a 30% chance of fooling a lay person for 5 minutes Anticipated all major arguments against AI in the following 50 years Suggested major components of AI: knowledge, reasoning, language, understanding, learning. Problem: Turing test is not reproducible, constructive, or amenable to mathematical analysis. Intelligence not determinable by surface behavior alone. The test is not sufficient since the behaviors under adjudication are too limited. As a sufficient condition for intelligence, the test is so difficult as to be uninteresting. Philosophy – Mind over matter OR mind is matter? Biological Naturalism (phisicalism, materialism) - "Brains Cause Minds“: Mental states, such as being in pain, knowing that one is driving a car, or thinking that your mother neglected you as a child, are a direct result of brain states. Some brain states = the same mental state. Avoids speculation about nonphysical processes beyond the ken of science. What about free will? Is everyone a deterministic machine? What about consciousness? How does consciousness arise from a certain organization of matter? What is consciousness? Why? Sentience: 1. The quality or state of being sentient; consciousness. 2. Feeling as distinguished from perception or thought. 3. A sense of one's own personal thoughts, including the attitudes, beliefs, and sensitivities held by or considered characteristic of an individual. Mind is spiritual: However, physical changes in mind affect it. Damage to certain areas of brain can change behavior. Dualism: There is a part of mind that lies outside of nature, is not physical. Rene Descartes: first clear discussion of the distinction between mind and matter. A proponent of dualism. Held that only man (not animals) posses this dualist quality – animals can be viewed as machines. Alternative to dualism: mind is purely physical but cannot be completely explained by a reduction to ordinary physical processes. Perhaps mind could be an “emergent” property of the physical characteristics of your brain, for example. Consciousness - The Chinese Room Experiment – Does running the right program generate consciousness? • • • • • • • 1. 2. 3. 4. Human – only understands English Rule book – written in english Stacks of paper – some blank, some with indecipherable symbols on them Small opening to outside world Pieces of paper with symbols on them are passed through the opening The human follows the instructions in the rule book Eventually the human hands a piece of paper with symbols on it through the opening Certain kinds of objects are incapable of conscious understanding The human, paper, and rule book are objects of this kind If each object is incapable, the entire whole is incapable Therefore there is no conscious understanding in the room The Brain Prosthesis Experiment Replace neurons in your brain one at a time with artificial neurons that *exactly* replicate the behavior of the original neurons (then reverse the process). By definition, the subjects external behavior must remain unchanged. What happens? We have two choices, either 1. The causal mechanisms involved in consciousness in the electronic brain are still functioning, and it is therefore conscious. 2. Conscious mental events in the normal brain have no effect on behavior. If neuron replacement is conscious, replacing brain with a circuit/lookup table that mapped inputs to outputs *must* also be conscious. Current definitions of AI Current definitions of AI vary along two main dimensions (page 5). • Dimension 1a. Concerned with thought processes and reasoning. Systems that think like humans. • Dimension 1b.. Concerned with behavior. Systems that think rationally. • Dimension2a. Measure success in terms of human performance. Systems that act like humans. • Dimensions2b. Measure success in terms of "rationality" (an ideal measure of performance). Systems that act rationally. 1. Acting humanly - the Turing test 2. Thinking humanly - cognitive science 3. Thinking rationally - the "laws of thought" approach. The emphasis is on making (and being able to trace) correct, logical inferences. 4. Acting rationally - the "rational agent" approach. Does not require that a "correct inference" be made, rather places emphasis on good behavior. Correct inference is thus only a useful, but not necessary, mechanism for generating "rational" (or good) behavior. This is the most general approach, since the behavior need not be humanlike, it just needs to be good/right. This is the definition of intelligence emphasized in this book. Potted history of AI 1943 McCulloch & Pitts: Boolean circuit model of brain 1950 Turing's ``Computing Machinery and Intelligence'' 1952--69 Look, Ma, no hands! 1950s Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine 1956 Dartmouth meeting: ``Artificial Intelligence'' adopted 1965 Robinson's complete algorithm for logical reasoning 1966--74 AI discovers computational complexity Neural network research almost disappears 1969--79 Early development of knowledge-based systems 1980--88 Expert systems industry booms 1988--93 Expert systems industry busts: ``AI Winter'' 1985--95 Neural networks return to popularity 1988-Resurgence of probabilistic and decision-theoretic methods Rapid increase in technical depth of mainstream AI ``Nouvelle AI'': ALife, GAs, soft computing Agents Anything which can be viewed as perceiving environment through sensors, etc. and then acting in the environment Current hot buzz-word Looks like the basic computational box Abstractly, an agent is a function from percept histories to actions: f : P* A For any given class of environments and tasks, we seek the agent (or class of agents) with the best (possible) performance (a rational agent). Intelligent Agents Intelligent (rational) agent seeks to maximize its performance measure for any given sequence of percepts Look up table? Text uses intelligent agent approach to bring all aspects of AI into one. What should an intelligent agent have? An intelligent agent should have knowledge, infer, plan, reason with uncertainty, learn, perceive, communicate, etc. What is rational for an agent? It depends on: 1. 2. 3. 4. The performance measure What it has perceived Its current store of knowledge The actions the agent can perform Agent Types Reflex Agent - Actions based only on current percepts (no state memory), condition-action rules Agents with Memory - keep track of internal state, past actions (or their effects), and the dynamically changing environment Goal-Based Agents - Actions driven by overall goal, easy if one step, multi-action sequences (subgoals) often supported by search and planning mechanisms Utility-Based Agents - Best actions All of the above agents can be turned into learning agents. - Multiple ways to reach goals - Conflicting Goals - Actions with uncertainty - which approach gives best chance of fulfilling goals Automated taxi driver: Percepts? Actions? Goals? Environment? Internet shopping agent Percepts? Actions? Goals? Environment? Environment Issues Accessibility - can agent detect all relevant percepts Determinism - is next state completely determined by current state plus the agent action - if inaccessible, then may appear nondeterministic regardless Episodic - Is environment neatly divided into independent episodes Static vs. Dynamic - Does environment remain static in between agent actions Discrete vs. Continuous - Are there limited distinct percept and action possibilities