02-chapt2 - CSE630: BriefHistory AgentsandEnvironments...

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CSE 630: Brief History Agents and Environments Prof. Naeem Shareef
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History of AI: Brief Overview Early to mid 50s Alan Turing, Marvin Minsky (student of von Neumann), John McCarthy, Alan Newell, Herbert Simon 1952-1969 … Great Successes Solving hard math problems Game playing LISP was invented by McCarthy (1958) second oldest language in existence could accept new axioms at runtime McCarthy went to MIT and Marvin Minsky started lab at Stanford Both powerhouses in AI to this day
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History of AI: Brief Overview 1966-1973 … A dose of reality – Overhyped Systems fail to play chess and translate Russian Computers were ignorant to the context of their logic Problems were intractable Algorithms that work in principle may not work in practice Combinatorial Explosion / Curse of Dimensionality Fatal flaw in neural networks was exposed Though flaw was first resolved in 1969, neural networks did not return to vogue until late 1980s
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History of AI: Brief Overview 1969-1979 … Knowledge-based Systems (Expert systems) Problem: General logical algorithms could not be applied to realistic problems Solution: accumulate specific logical algorithms DENDRAL – infer chemical structure knowledge of scientists boiled down to cookbook logic large number of special purpose rules worked well 1980 – present … Let the good times roll The demonstrated success of AI invited investments from millions to billions of dollars in 10 years Extravagant AI promises again led to “AI Winter” when investments in technology dropped (1988) Neural Networks came back from the dead (1986)
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History of AI: Brief Overview 1987 – present … AI becomes a science More repeatability of experiments More development of mathematical underpinnings Reuse of time-tested models Intelligent Agents (1994) AI systems exist in real environments with real sensory inputs Niches of AI need to be reorganized
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environment percepts actions ? agent sensors effectors An Agent and its Environment An agent perceives its environment via sensors and acts in that environment with its effectors (actuators). Environment: Agent’s world
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Perception and Action Perception: Sensors receive input from environment Keyboard clicks Camera data Thermostat Percept : The state of all perceptual inputs at an instant Precept sequence : Complete history of all prior percepts Action: Actuators impact the environment Move a robotic arm Generate output for computer display Turn on the furnace
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8 Agents Air-conditioning agent Sensors: thermostat Actuators: furnace Human agent Sensors: eyes, ears, nose, etc Actuators: hands, legs, mouth, and other body parts An artificial agent may have sensors and actuators that a human doesn’t have laser range finder sonars touch sensors
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9 Agents Robotic agent: Part-picking robot
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This note was uploaded on 04/13/2010 for the course CSE 630 taught by Professor Naeemshareef during the Spring '10 term at Ohio State.

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02-chapt2 - CSE630: BriefHistory AgentsandEnvironments...

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