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Top-Down Incremental Development of Agents' Architecture for Emergency

HID, CAMO Seminars Series. Top-Down Incremental Development of Agents' Architecture for Emergency Management Systems: TOGA methodology. Andrea Caputo, Adam Maria Gadomski, Franco Delli Priscoli May 2005. University of Rome “La Sapienza”. Italian National Research Agency ENEA.

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Top-Down Incremental Development of Agents' Architecture for Emergency

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  1. HID, CAMO Seminars Series Top-Down Incremental Development of Agents' Architecture for Emergency Management Systems: TOGA methodology Andrea Caputo, Adam Maria Gadomski, Franco Delli Priscoli May 2005 University of Rome “La Sapienza” Italian National Research Agency ENEA This activity is realized in cooperation between La Sapienza University and ENEA: F.Delli Priscoli (Univ. La Sapienza, Rome), A.M.Gadomski (CAMO, ENEA), A.Caputo - thesis (Univ. La Sapienza - Engineering Dep., ENEA scholarship 2002/0362)

  2. Top-Down Incremental Development of IntelligentAgents' Architecture Presentation outline • IntelligentAgents' Architecture: Problem Specification • Existing Design & Programming styles (short soa) • TOGA Theoretical Tool • Method: Top-Down incremental development • Emergency Management Test-Case • Conclusions • Prototype demonstration

  3. Contents of the Caputo’s Thesis • General request overiview • Contest of the simulation: Socio-Cognitive Engineering • A TOGA proposal • IPK monad • Universal Management Paradigms • Example showed at SCEF 2003 • Intelligent Decision Support System • Modelling Disaster Domain • Disaster Propagation • GEA

  4. Contest of the Simulation Socio-Cognitive Engineering Natural Sciences Artificial Intelligence Software Technology From the Socio-cognitive contest we will arrive at a ripetitive, incremental, ricorsive, distribuite INTELLIGENT ENTITY [ 1 ]

  5. IPK Informations ( I ) Preferences ( P ) Knowledges ( K ) I’ = Kx I I, I’  DD Kx K Kx = Ps (K, I) SOCIO-COGNITIVE ENGINEERING PARADIGMS A TOGA PROPOSAL [ 2 ] UMP Universal Management Paradigm (UMP) is a functional architecture of organizational High-Intelligence for every natural and artificial High- Intelligent agents’ organization. It is characterized by: I • Complete • Relative • Recursive • Incremental P K IPKparadigm and UMP describe essential functional properties of abstract highly intelligent entities, natural and artificial.

  6. TOGA Normative Meta-Assumptions  structural assumptions: -- Recursivity -- Iterativness -- Repetitivity -- Modularity They intend to minimize total axiomatic information employedby the theory. methodological assumptions, which require completeness and congruence of the problem conceptualization on every abstraction level. terminological assumption, to reduce the number of terms as is possible. The key TOGA paradigms (top assumptions/axioms) are divided on [ 3 ]: Conceptualization, Ontological, and Methodological

  7. Summarizing, what is it? • Complex-Knowledge Ordering Methodology (Meta-theory) • Problem Specification & Decision-Making Modelling Approach. (It has algebra property) TOGA Meta-Modeling Framework Three components: TAO :Basic conceptualization frame independent on represented domain ofinterest. KNOCS :Axioms system for the real-world problem representation MRUS :Methodological RUles Systems Non ordered observations, knowledge, values TAOConceptualizations KNOCS Conceptualization Goal-oriented Problem Model MRUS: Methodological Rules System They refers to an Abstract Intelligent Agent (AIA), his/her/its Domain-of-Activity and to the relations between them.

  8. I I LEVEL K P I I II META-LEVEL P K P K Personois: IPK Abstract Agent • Model Axioms • Repetivety • Modularity • Recursivity …

  9. Universal Management Paradigm Ref. [ 4 ] SUPERVISOR Based Structure: Subjective, Incremental, Recursive TASKS INFORMATION EXPERTISES COOPERATION ADVISOR MANAGER COOPERATING MANAGER TASKS INFORMATION INFORMER EXECUTOR DISASTER DOMAIN

  10. Disaster Manager: simple model example Infrastructure Network Real Emergency Domain Agent 1 Agent 2 Agent 3 Agent n I1 I2 I3 In - - - P K P K P K P K I : Information P : Preferences K : Knowledge I P K Agent Manager

  11. Objectives of experiment: why? Practical vefification of the methodology by the designing a series of agents with incremental complexity and functionality. The prototypes have been developed in Object oriented C++ language. As a test case, we assumed an emergency situation caused by An explosion in a chemical plant where its consequences cause An intoxication of the water in a neighboring city.

  12. Definition of the Experiment Architecture On the base of the TOGA paradigms, we built an evolution line of the incremental design of Intelligent Agents aimed at the development of the model of an Intelligent Entity The representation of the abstract world of the Agent is: WORLD ANIMATOR WORLD SIMULATOR PROTO- PERSONOID PERSONOID ANIMATOR ABSOLUTE OBSERVER In this image is showed the relations between the world of the Agent and the Human Utent. There are distinghished three different human roles, evidenced in the lighter boxes

  13. Decomposition of different fields of the Agent EXPERIMENT: Architecture incrementing To describe the World Simulator and the Proto-Personoid and the interaction between them, will be used the following symbolization DOMAIN SUPERVISOR ADVISOR COOPERATING MANAGER Constrain Environment INFORMER EXECUTOR I P K Domain Body World Animator Personoid Animator Absolute Observer The IPK structure is seen from the social prespective according to the UMP paradigm. Infact in the Domain we can see the other different components of the UMP paradigm.

  14. IDSS: Intelligent Decision Support Systems IDSS:“Software program that integrates human intellectual and computer capacities to improve decision making quality, in semi-structured problems situations”[Keen, Scott-Morton, 1996] Provides passive Informational Aid and Toolkits DSS Provides active, partially autonomous DecisionalAid which involve human-like computational intelligence. IDSS • When IDSS is important? • amount of information necessary for the management is so large, or its time density is so high, that the probability of human errors under time constrains is not negligible. • coping with unexpected situation requires remembering, mental elaboration and immediate application of complex professional knowledge, which if not properly used, causes fault decisions.

  15. Modelling Disaster Domain: Disaster Prop. Map

  16. Experiment Realization We created a general agent, which follows a simple set of rules. It represents a first interaction of the proto-personoid with the external world. Then, from this generic starting point, we decompose the various aspects of the agent, analysing the IPK monad which represent the core of the agent. The monad, as we said, is composed of three different parts (Information, Preferences and Knowledge), and in every new step of our decomposition, we increase the complexity of one of these parts. To focus this aspect of the analysis we introduce a scale of colours which represent the grade of the complexity of the analysed part of the system.

  17. RESULT S OF THE EXPERIMENT Proto-Personoids produced in the design experiment The main important results of the experiment are: • modular and reproducible decomposition of the Personoid has been realized. • it’s possible to obtain incrementally new specializations of the Personoid focalized on a more detailed problems • The complexity of the problem ( functionality and architecture) can growth infinitely.

  18. Test Case: Disaster Domain Application of Emergency/Disaster Propagation Framework Events: Explosion and fire in chemical factory, Fire in the forest Emision of toxical substances by tubes to the river Water in City Aqueduct is toxic Water users are in danger. EMERGENCY MANAGER: Identification of intervention/vulnerable objects, goal of intervention and possible actions

  19. Test Case: Disaster Propagation Map (DPM)

  20. TEST Case: Time Diagram without intervention PROPAGATION OF EMERGENCY WITHOUT INTERVENTION

  21. Forest Others Chicken Farm Factory Factory tubes Citizens River City Aqueduct Evolution of the DPM without intervention Combined together the DPM with the Time Diagram without intervention, this evolution in time will be obtained

  22. GEA: IPK Cognitive Agent

  23. Synthesis of the results of the work • Documentation and validation of the TOGA Theory • 25 Agents prototype realized • 30.000 code lines written • GEA prototype • User friendly interface

  24. GEA: Demo Click here for demonstration

  25. References 1. 2. 3. TOGA Meta-theory Web page: http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm 4.

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