national chiao tung university chun-jen tsai...
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Artificial Intelligence
National Chiao Tung University
Chun-Jen Tsai
6/8/2012
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Intelligent Agent
� In AI, researchers try to build a device (an agent) that can sense-and-change its environment
sensor
robot
manipulator
Where is the brain?
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Levels of Intelligent Behaviors
� Reflex
� actions are predetermined responses to the input data
� Intelligent response
� actions affected by knowledge of the environment
� Goal seeking
� Learning
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Approaches in Artificial Intelligence
� Performance-oriented
� Researcher tries to maximize the performance of the agents; the techniques used may not be “intelligent” by nature, but are effective in producing “intelligent” results
� Simulation-oriented
� Researcher tries to derive theories about how a biological agent produce intelligent responses to the environment and try to build an artificial agent that use the theories to simulate the behaviors
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Turing Test
� Proposed by Alan Turing in 1950, a benchmark for progress in artificial intelligence
� Test setup: human interrogator communicates with test subject by typewriter.
� Test goal: can the human interrogator distinguish whether the test subject is human or machine?
� Examples
� The DOCTOR program created by Joseph Weizenbaum in 1960s may fool some naive human interrogator; similar to today’s MSN robots
� Today, CAPTCHA are used to stop web-bots
CAPTCHA – Completely Automated Public Turing test to tell Computer and Human Apart
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Perception – Understanding the Input
� Image Understanding
� Template matching
� Image processing techniques
� edge enhancement
� region finding
� smoothing
� Image analysis
� Language Processing
� Syntactic Analysis
� Semantic Analysis
� Contextual Analysis
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Example: A Semantic Net
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Reasoning Ability
� Some AI researchers think that the ability to reason can be isolated in an abstract entity known as a
production system:
� Collection of states
� Collection of productions (rules or actions)
� Control system:decides which production to apply next given current states
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Reasoning by Searching
� State graph
� a graph that representing all the states and productions
� Search tree
� a record of state transitions explored while searching for a goal state
� Breadth-first search
� Depth-first search
� Example: the 8-puzzle problem
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Partial State Graph of 8-Puzzle Problem
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8-Puzzle Problem Search Tree
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Deductive Reasoning
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Heuristic Strategies
� Heuristic
� A “quantitative estimate” of the distance to a goal
� Not all reasons can be quantified, but with heuristic, we can “compute” our goal
� Requirements for good heuristics
� Must be much easier to compute than a complete solution
� Must provide a reasonable estimate of proximity to a goal
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Eight-Puzzle Heuristic
� How do we quantify the distance to our goal in an 8-puzzle problem?
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Heuristic Search of 8-Puzzle Prob.
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Key Issues in Intelligent Behavior
� Representation and storage of knowledge
� How to access a piece of related information effectively?
� Meta-reasoning and closed-world assumption enable us to access not only related but also relevant information
� Frame problem: in a dynamic environment, how to update the stored knowledge due to the occurrence of some events?
� Learning
� Imitation
� Supervised training
� Reinforcement
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Artificial Neural Networks
� A biological neuron:
� Artificial neural network:
� Use electronic devices to simulate a biological neuron
� Connecting multiple neurons to form a computing system
inputoutput
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Artificial Neurons
� The activities within a processing unit (an artificial neuron)
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Artificial Neural Network Topology
� The topology describes how individual neurons are connected together; for example, a two-neuron
network:
� Question: can we compute the XOR function using
this artificial neural network?
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Training of an Artificial Neural Net.
� To compute XOR, we have to train it!
a. The network performs correctly for input 1, 1
b. The network performs incorrectly for input 1, 0
c. The upper weight in the 2nd processing unit is adjusted
d. But, the network no longer handles input 1, 1 correctly!
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Automatic Vehicle Navigation
� ALVINN†:Autonomous
Land Vehicle
In A Neural Network
† Pomerleau, D. A. Neural Network Perception for Mobile Robot Guidance. Ph.D. dissertation, Carnegie Mellon Univ., Feb. 1992.
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Associative Memory
� Associative memory
� The retrieval of information that is most relevant to the information at hand
� One direction of research seeks to build associative memory using neural networks that when given a
partial pattern, will transit it into a completed pattern
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Robotics
� Truly autonomous robots require progress in perception and reasoning.
� Major advances being made in mobility
� Plan development versus reactive responses
� Evolutionary robotics
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Issues with Artificial Intelligence
� When should a computer’s decision be trusted over a
human’s?
� If a computer can do a job better than a human, when should a human do the job anyway?
� What would be the social impact if computer
“intelligence” surpasses that of many humans?