artificial intelligence john ross yuki yabushita sharon pieloch steven smith
Post on 21-Dec-2015
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8 Types of AI Robotics
Fuzzy Logic
Expert Systems
Intelligent Agents
Natural Language Processing
Artificial Vision
Neural Networks
Genetic Algorithms
Expert Systems “An Expert System is a system that employs human
knowledge captured in a computer to solve problems that ordinarily require human expertise”.
In the early 1960’s, the General-purpose Problem Solver was introduced (GPS). This machine helped solve some basic problems.
Source: (www.usfca.edu).
Source: www.growinglifestyle.com
Over the past 10 years, expert systems have replaced human workers in fields such as industrial, science and research, and even for recreational purposes such as mowing your lawn. ES’s will eventually be able to solve complex solutions such as the traveler who wants the fastest route for 10 cities.
The Future of Expert Systems
The i-Mow from Toro
Natural Language Processing
NLP has become very popular over the last decade. Speech recognition can make work a bit easier if implemented in the right places. One of the drawbacks has been the difference in languages and syllables. Computers must be trained to adapt to individual voice patterns which takes time. “It is clear that for applications that are eye-busy, hand-busy, a trainer that incorporates NLP technology is very useful” (www.cs.duke.edu).
Fig. 1: Examples of typical documents used: a) Chinese, b) English, c) Greek, d) Korean, e) Malayalam, f) Persian, g)
Russian.
Natural Language Processing: The Multiple Languages Barrier
Source: www.bmva.ac.uk
Breaking the Language Barrier
To incorporate ES units that can be translated in most common languages.
To bypass syllable irregularities between different languages (such as Japanese characters that use two symbols).
NLP systems that can comprehend the intended use of certain words. Fuzzy logic can give computers protocols of how certain words are used in certain cultures.
Integrating Global NLPOne future challenge is to create cells
(nodes) that will comprehend all major languages.
In the future, robots will recognize multiple voice patterns in multiple languages.
Genetic Algorithms
Use simulated populat ion of “art if icial life” to solve complex problems
Reach opt imal solut ion faster than other methods
May create solut ion humans never thought of
Genetic Algorithms Design “chromosome” which is a problem
solut ion
Randomly generate a populat ion
Test for f itness & select the best
“Reproduce” using the best
Start over with the new populat ion
http://cs.felk.cvut.cz/~xobitko/ga/
Applicat ions of GA
Genetic programming—computers write their own code Robotic ants collect food Bots playing soccer game
www.lalena.com
Elect rical circuit design Students required two
weeks, GA designed in 30 minutes
University of Idaho
Intelligent Agents
Software programs that: Sense their environment
Act independently
Can interact with other agents (including humans)
Intelligent Agents
Examples: Web search agents
(web crawlers)
Web server maintenance bots
Personal assistants
Chatter bots (talking agents)
www.agentland.com
Intelligent Agents
Future uses for agents: Network maintenance
Agent-oriented programming
Mobile, physical agents (intelligent robots)
Fuzzy logic
Similar processes to those of neural networks.
It is designed with specific formulas or rules.
Gives a clear output by having a calculation.
Usually used for “fuzzy” things (unclear estimations).
Fuzzy logic
General idea/rules If service is poor, good, excellent..? If food is rancid, or delicious..?We can combine these two categories to
to one list. If service is poor or the food is
rancid..? If service is excellent or food is
delicious…?
The MathWorks, http://www.mathworks.com/access/helpdesk/help/toolbox/fuzzy/fuzzy.shtml
Neural Network Inputs: all facts Hidden layer: finding
the possible ways to predict
Outputs: final decision of prediction
Neural Network
Different paradigm for computing.Operates similar to our human brain.Takes inputted data, and predict some
actions based on these data.Learns new ways of solving by adding
some more facts.
Neural Network
Business ApplicationFinance; credit risk decision support,
predicting bad debtors, preventing application fraud
Marketing; customer attrition, analyzing consumer-spending patterns
Forecasting sea surface temperature
Fuzzy logic
Business ApplicationCruise control for carPDASubway systemPrediction system for early recognition
of earthquakesAir conditioning system
www.ai.mit.edu
Robotics• Definition: A
programmable, self controlled device consisting of electronic, electrical, or mechanical units
• It is a machine that functions in place of a living agent
History of Robotics
Joseph Engelberger & George Devol were the first to develop a commercially successful robot known as Unimate
Unimate was an assembly line arm used to extract die castings and perform spot welding on auto body assembly lines
Began industrial robot revolution by selling to General Motors in 1962
Advantages of Robotics
Perform highly repetitive tasks more efficiently and accurately
Ability to perform tasks that would otherwise be considered dangerous
Improved management control
Greater productivity
Higher quality
Can reduce costs of manufactured goods
Give countries an economic advantage on the world market.
Current Applications
Exploration Space
Ocean
Volcanoes
Military/Police Destroy/Locate
bombs
Espionage
Medical Operations
Productions of medicines
Development of prosthetic (bionic) limbs
Artificial Vision
The ability of a machine to see its environment, to make choices about its action based on what it sees and to recognize visual input according to general patterns.