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The Theory of Objects and the automatic generation of Intelligent Agents

The Theory of Objects and the automatic generation of Intelligent Agents. Sergio Pissanetzky 2009. What is an object, anyway?. Our minds make objects all the time. We think, communicate, even dream in terms of objects. An object is anything that: has information (attributes)

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The Theory of Objects and the automatic generation of Intelligent Agents

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  1. The Theory of Objects and the automatic generation ofIntelligent Agents Sergio Pissanetzky 2009

  2. What is an object, anyway? Our minds make objects all the time. We think, communicate, even dream in terms of objects. An object is anything that: • has information (attributes) • can use it to do something (behavior) • can share it with other objects (interaction). What do they do? • organize information and reduce complexity. • fundamental structural element of information. • there can be no AI without a mastery of objects.

  3. But ... where do they come from? • Computer program. • behavior • structure • refactoring transformation • any system can be refactored

  4. The Matrix Theory of Objects establishes that: • Any finite system can be perfectly represented by a matrix of services in canonical form. • Under a deterministic, dissipative and chaotic dynamics, the structure of the system evolves towards its stable attractors. • The attractors are partitioned into submatrices that remain invariant under the dynamics. • The attractors represent the structure of the system. • The attractors also represent the equivalent logical circuit for the system. • The submatrices represent the objects present in the system, and their relationships represent the system’s ontology.

  5. The Matrix Model Any system SCA ORA canonical matrix objects circuit learning ontology

  6. The Wumpus World

  7. ● Collect knowledge into the Learning Matrix. ● Organize the knowledge into canonical form. ● Minimize the profile to generate objects. CNF Resol

  8. Information obtained by the Learning Matrix may be incoherent, disorganized.

  9. The Sorter organizes the information into a canonical form Profile = 40 But there there are still no objects

  10. SCA has automatically refactored the matrix and has generated the following attractor Profile = 23 But objects are still difficult to discern

  11. Based on a statistical sample of attractors, ORA has automatically generated two objects X Y Profile = 23 The two objects are intelligent agents

  12. The ontology of the system generated by SCA/ORA inference rules biconditional elimination implication elimination De Morgan distributivity resolution X(CNF) Y (reason)

  13. The equivalent logical circuit of the system generated by SCA/ORA S1 S3 S4 S5 S6 S2 S7 S8

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