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XML-based Genetic Programming Framework: Design Philosophy, Implementation and Applications

XML-based Genetic Programming Framework: Design Philosophy, Implementation and Applications. Outline. Introduction Objective Proposed approach Verification results Applications Conclusion. A) Promptly developed software models of the evolved artifacts

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XML-based Genetic Programming Framework: Design Philosophy, Implementation and Applications

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  1. XML-based Genetic Programming Framework: Design Philosophy, Implementation and Applications

  2. Outline • Introduction • Objective • Proposed approach • Verification results • Applications • Conclusion

  3. A) Promptly developed software models of the evolved artifacts B) Fast running offline (phylogenetic) learning via simulated evolution (e.g. GP) The Needs 1. Introduction: the Problem

  4. A) Promptly developed software models of the evolved artifacts B) Fast running offline (phylogenetic) learning via simulated evolution (e.g. GP) The Needs Discrepancy, Gap The Reality A) Slow development time of evolutionary systems (specific semantics) B) Notoriously poor performance of GP (populations, generations, independent runs) 1. Introduction: the Problem

  5. The Reality • Quicker development time GP • Better performance characteristics of GP 2. The Objective A) Promptly developed software agents B) Fast running offline (phylogenetic) learning via simulated evolution (e.g. GP) The Needs Discrepancy, Gap The Reality A) Slow development time of evolutionary systems (specific semantics) B) Notoriously poor performance of GP (populations, generations, independent runs)

  6. 3. The Approach Quicker development time of GP ? • History of “Reuse of Software Blocks” in Software Engineering: • loops, • procedures, functions (incl. recursions), • modules (units), • objects, • component objects • Component objects (CO): • appears to be an object of the IDE which incorporates them, • binary standard (language-independent)

  7. A) Standard DOM-parsing tree and XML text. B) CO: DOM-parser with built-in API for dealing with genetic programs. 3. The Approach Focusing on representation of genetic programs:

  8. 3. The Approach Advantages A) Significant reduction of the time consumption of software engineering of GP using build-in API for creating and manipulating genetic programs.

  9. 3. The Approach • Issue: • How to represent the allowed syntax (i.e. to reduce the search space) of GP? • In the program source of GP-system (modifications by expert, recompilation, etc…) ? • As an external text with well-known format? • Employing XML facilitates the second choice.

  10. 3. The Approach Advantages B) Increase of efficiency of execution of XGP: Reducing the computational effort as a result of generic support for the idea of pruning the solution space via strongly typed GP. How: XML-schema as a standard, generic way to represent the syntax of XGP.

  11. Fragment of XML Schema <xs:simpleType name="VAR_TSpeed"> <xs:restriction base="xs:string"> <xs:enumeration value=“Speed" /> </xs:restriction></xs:simpleType> <xs:simpleType name="OPER_TSpeed"> <xs:restriction base="xs:string"> <xs:enumeration value="GE" /> <xs:enumeration value="LE" /> </xs:restriction></xs:simpleType> <xs:simpleType name="CONST_TSpeed"> <xs:restriction base="xs:integer"> <xs:minInclusive value="0" /> <xs:maxInclusive value=“22" /> </xs:restriction></xs:simpleType> 3. The Approach • Relationship between tree nodes in XGP, • Data types associated with tree nodes

  12. 3. The Approach Advantages • B) Increase of efficiency of execution of XGP - parallelism: • Improving the computational performance: XML representation of both the schema and the genetic programs is a feasible format for migration of agents in parallel, distributed computer architectures. In-memory tree structures of GP cannot be transferred between computing units in parallel architectures.

  13. 3. The Approach Memory Structure (DOM) Text (XML) Straightforward Mapping

  14. 3. The Approach Structure of XGP-framework GP Manager (selection, crossover, and mutation) Domain Independent (only XML Schema need to be updated) • Implications: • Reuse of GP Manager across the applications, • Parallel Simulation Boards Simulation Boards (evaluation) Domain-specific

  15. Example – Evolution of Behavior of Agents in MAS • Parallel Implementation via Boss-Workers Model Genetic program (XML) Fitness GP Manager (selection, crossover, and mutation) Simulation Boards (evaluation) 3. The Approach

  16. 4. Verification Results • Development time for the initial prototype of XGP (from scratch): several [person*days]

  17. 4. Verification Results • Porting time (employing XGP for already developed simulation board): less than one hour XML Schema File

  18. 4. Verification Results • Computational Effort of XGP: Reducing the search Space (XML Schema) Probability of Success for Evolution of XGP with (STGP) and without (LP, LPA) strong types

  19. 5. Applications Evolution of Agents Behavior in MAS MAS Simulation Board Domain Specific GP Manager Domain Neutral

  20. 5. Applications Evolution of Agents Behavior in MAS XML representation of GP

  21. 5. Applications Evolution of Locomotion of Snakebot GP Manager Domain Neutral DOM representation of GP Simulation Board Domain Specific

  22. 5. Applications Evolution of Neural Networks GP Manager Domain Neutral Simulation Board Domain Specific XML representation of GP

  23. 5. Applications Evolution of Driving Agent PC (driving agent) Camera (perceptions of the agent) Control Loop, 100ms Car (1/24 Scale Model) Remote Control (agent’s actions)

  24. 5. Applications Evolution of Driving Agent GP Manager Domain Neutral Simulation Board Domain Specific DOM representation of GP

  25. 5. Applications Interactive Evolution of Postures of Aibo Robot GP Manager Domain Neutral DOM representation of GP Simulation Board Domain Specific

  26. 5. Applications Interactive Evolution of Room Colors GP Manager Domain Neutral Simulation Board Domain Specific DOM representation of GP

  27. 5. Applications Evolution of Human-Relation Networks Simulation Board Domain Specific GP Manager Domain Neutral

  28. 6. Conclusion Proposed DOM/XML-Based Portable Genetic Representation in XGP • Reduced Development Time • Managing genetic program via standard DOM parsers with built-in API • B) Easy Porting to New Applications • Reusing the very General, Domain-Independent GP Manager, • Modifying the XML-schema only.

  29. 6. Conclusion Proposed DOM/XML-Based Portable Genetic Representation in XGP • C) Improved Execution Time of XGP • Reducing Computational Effort: Limiting solution space using strongly typed GP and offering generic support via XML schema, • Improving Computational Performance: Generic support of distributed (web-compliant) implementation of GP. • Drawbacks? • Fitness evaluation – parsing of XML/DOM tree and navigating among the nodes…

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