CS 621 Artificial Intelligence Lecture 15 - 06/09/05 Prof. Pushpak Bhattacharyya
Genetic Programming as a Tool for novel Creation CS 621 Seminar Sri Raj Paul(08305034) Course...
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Transcript of Genetic Programming as a Tool for novel Creation CS 621 Seminar Sri Raj Paul(08305034) Course...
Genetic Programming as a Tool for novel Creation
CS 621 Seminar
Sri Raj Paul(08305034) Course InstructorBalamurali(08405401) Prof. Pushpak Bhattacharyya
THE WAY WE GO…. Invention & Patent
AI & Invention
Genetic Algorithm
Genetic Programming
GP – Invention Machine
Conclusion
INVENTION What is it? a new form, composition of matter, device, or process What is a patent?
a set of exclusive rights granted by a state to an inventor or his assignee for a fixed period of time in exchange for a disclosure of an invention
IS EVERY INVENTION PATENTABLE?
Is an improvement over a patented invention
Result is equal to or better than a result that was placed .
Result is publishable in its own right as a new scientific result.
The result solves a problem of indisputable difficulty in its field.
AI & INVENTION A new idea that can be logically deduced from
facts that are known in a field, using transformations that are known in a field, is not considered to be inventive
Obtaining implication of given facts and rules -- Hallmark of intelligence ~ Prof. PB slides
Result: AI based on reasoning and logic cannot Invent !
GENETIC ALGORITHM• Inspired by evolutionary biology• A solution represented as a chromosome• Methodology
– Initialization– Selection– Reproduction
• Crossover • Mutation
– Termination
GENETIC PROGRAMMING GP applies the approach of the genetic algorithm
to the space of possible computer programs Computer programs are the basic way for
expressing the solutions to a wide variety of problems
Genetic programming now routinely delivers high-return human-competitive machine intelligence High -> high AI (“artificial-to-intelligence” ) ratio Routine -> repeating successfully on different set of
problems human-competitive -> is patentable in a sense
GP OPERATORS Reproduction Crossing over Mutation Architecture Alteration operation
GP FLOW CHART
Source: John Koza slides
PREPARATORY STEPS
Source: www.genetic-programming.com
• The human user communicates the high-level statement of the problem to the genetic programming using preparatory steps
FUNCTIONAL SET AND TERMINAL SET Alphabets of the programs to be made
The terminal set consists of the variables and constants of the programs
The functions are several mathematical functions and other more complex functions
FITNESS MEASURE• Specifies what needs to be done
• The primary mechanism for communicating the high-level statement of the problem’s requirements
• The first two preparatory steps define the search space whereas the fitness measure implicitly specifies the search’s desired goal.
CONTROL PARAMETERS AND TERMINATION• These steps are administrative• Control parameter:
– population size.– probabilities of performing the genetic operations– the maximum size for programs
• Termination criterion– maximum number of generations– may manually monitor and manually terminate
• Method of designating the result– single best-so-far individual
GP – INVENTION MACHINE Problem : To create a low pass filter without
patent infringement of Ladder filter. below 1,000 Hz – Pass band above 2,000 Hz – Stop Band
Ladder Filter
Source: Genetic Programming as a Darwinian Invention Machine
PROGRAM ARCHITECTURE Topology-modifying functions
– alter the circuit topology Component-creating functions
– insert components into the circuit Development-controlling functions
– control the development process Arithmetic-performing functions
– specify the numerical value of the component Automatically defined functions
– enable certain substructures of the circuit to be reused
PREPARATORY STEPS Initial Circuit Program Architecture Functions Terminals Fitness Control Parameters Termination
INITIAL CIRCUIT Test Fixture
– fixed substructure– provides access to the
circuit's external input– permits probing of the
circuit's output Embryo
– development occurs in the embryo
Source: Genetic Programming as a Darwinian Invention Machine
FUNCTIONS AND TERMINALS F= {C, L, SERIES, PARALLEL, FLIP, TVIA0, …,
TVIA7, NOOP}
Tccs = {END, CUT}– ccs- construction continuing sub-tree– END makes the modifiable component with which it is
associated non-modifiable– CUT causes the component to be removed from the
circuit
Taps = {R}– aps- arithmetic-performing sub-tree
FITNESS1. Measurement the circuit’s behavior in the
frequency domain 101 Signals from 1 Hz and 100,000 Hz divided using a
logarithmic scale is given Error measured using Formula
2. Circuit’s similarity to the to-be-avoided ladder filter sub graph of the given circuit that is matching to a sub
graph of a ladder filter3. Both are multiplied to get over all fitness4. Smaller the overall value of fitness is better
))()),((()(100
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CONTROL PARAMETERS AND TERMINATION Control Parameters
Population size, M is 1,950,000 Circuit constructing program tree size is 300
Termination Goal is to generate a variety of 100%-compliant
circuits Numerous 100%-compliant circuits were harvested Manually terminated
RESULTS Based on Matching factor & frequency response
more than 8 suitable offspring's were selected.
One of the result was elliptic filter(1927,Caur) Which is patented!
Source: Genetic Programming as a Darwinian Invention Machine
CONCLUSION GP can automatically create design that
satisfies new specification Avoids prior art
If a suitable fitness criteria can be found ,GP can be used in any field for invention
REFERENCE J.R. Koza, F.H. Bennett III, and O. Stiffelman. 1999
Genetic Programming as a Darwinian Invention Machine. EuroGP’99, LNCS 1598, pp. 93-108, Ó Springer-Verlag Berlin Heidelberg 1999
John R. Koza, Martin A. Keane, Matthew J. Streeter, "Routine High-Return Human-Competitive Evolvable Hardware," eh,pp.3, 2004 NASA/DoD Conference on Evolvable Hardware (EH'04), 2004
http://www.genetic-programming.com http://en.wikipedia.org/wiki/Genetic_programming Prof. Pushpak Bhattacharyya slides
Thank You
Source: www.genetic-programming.com
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Source: www.genetic-programming.com
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Source: www.genetic-programming.com
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