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14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 GoF design patterns applied to artificial intelligence methods Assist. Prof. Dr. Dušanka Bošković University of Sarajevo Content Background: Integrating Software Engineering and Artificial Intelligence DP implementation cases Conclusion 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Background Benefits: Problems: Fuzzy inferencing is suitable for solving real world problems: operating with fuzzy and non-complete data. Adaptive systems development needs application of machine learning techniques. AI research focused to solving specific and particular problems, SE distrust black-box approach and complexity of AI methods Way to go: AI: need to elevate abstraction level of solutions from a particular problem to a strategy that solves a class of problems SE: It is not enough to embed AI method; integration of AI methods in SE processes and techniques 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Integrating AI and SE Building generic models for AI Agents and Multi-agent systems (MAS) Reasoning - Fuzzy inferencing system (FIS) Learning - Artificial neural networks (ANN) 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 FIS model Class diagram 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 FIS model Fuzzy set generalization FuzzyVariable FuzzySet OutputSet Singlton Gaussian TriangularSet TrapezoidSet LeftShoulderSet RightShoulderSet 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 ANN model Class diagram Feedforward NN with Backpropagation LarningAlgorithm DataSet NeuralNetwork BackPropagation * Variable ActivationFunction1 SigmoidActivation TanHActivation LinearActivation 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Design patterns Factory Client uses add fuzzy set <Creator> :FuzzyVariable <Abstract Product> FuzzySet +AddFuzzySet(int type, String name, double[] points) +createFuzzySet(String name, double[] points) <Concretet Product>TriangleFuzzySet <Concretet Product>TTrapezoidFuzzySet +createTriangleFuzzySet(String name, double[] points) +createTriangleFuzzySet(String name, double[] points) 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Design patterns Factory 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Design patterns Strategy NeuralNetwork +strategy ActivationFunction +double function(double net) +double deriv(double output) TanHActivation +double function(double net) +double deriv(double output) SigmoidActivation +double function(double net) +double deriv(double output) LinearActivation +double function(double net) +double deriv(double output) 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Design patterns Composition ClientClass FuzzyVariable +applyHedge() +addFuzzySet() +getFuzzySet() * FuzzySet +applyHedge() 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 JAVA - Design patterns Iterator Observer 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Conclusion Bridging AI and SE Making AI solutions understandible to SE Introducing new examples for students 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014 Thank you for your attention Questions? 14th Workshop on “Software Engineering Education and Reverse Engineering” Sinaia, Romania August 24th – 30th 2014