Transcript Presentazione di PowerPoint
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)
Top-Down Incremental Development of Intelligent Agents' Architecture Presentation outline
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Intelligent Agents' Architecture: Problem Specification
•
Existing Design & Programming styles (short soa)
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TOGA Theoretical Tool
•
Method: Top-Down incremental development
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Emergency Management Test-Case
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Conclusions
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Prototype demonstration
Contents of the Caputo’s Thesis
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General request overiview
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Contest of the simulation: Socio-Cognitive Engineering
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A TOGA proposal
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IPK monad
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Universal Management Paradigms
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Example showed at SCEF 2003
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Intelligent Decision Support System
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Modelling Disaster Domain
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Disaster Propagation
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GEA
Contest of the Simulation Socio-Cognitive Engineering Natural Artificial Sciences Intelligence Software Technology
From the Socio-cognitive contest we will arrive at a
ripetitive, incremental, ricorsive, distribuite INTELLIGENT ENTITY [ 1 ]
SOCIO-COGNITIVE ENGINEERING PARADIGMS
IPK Informations Preferences Knowledges
I’ = K x I K x K K x = P s (K, I)
A TOGA PROPOSAL
[ 2 ]
( I ) ( P ) ( K )
I, I’ DD
P I K 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:
Complete
Relative
Recursive Incremental IPK paradigm
and
UMP
describe essential functional properties of abstract highly intelligent entities, natural and artificial.
TOGA Normative Meta-Assumptions
structural assumptions: -- Recursivity -- Iterativness -- Repetitivity -- Modularity They intend to minimize total axiomatic information employed by 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
TOGA Meta-Modeling Framework
Summarizing, what is it ?
• Complex-Knowledge Ordering Methodology (Meta-theory) • Problem Specification & Decision-Making Modelling Approach. (It has algebra property)
Three components:
TAO : Basic conceptualization frame independent on represented domain of interest.
KNOCS : Axioms system for the real-world problem representation MRUS : Methodological RUles Systems Non ordered observations, knowledge, values TAO Conceptualizations 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.
P P Personois: IPK Abstract Agent I I LEVEL K
•
Model Axioms Repetivety Modularity Recursivity … II META-LEVEL K P K
Ref. [ 4 ] Universal Management Paradigm
TASKS
SUPERVISOR
INFORMATION
Based Structure: Subjective, Incremental, Recursive ADVISOR
EXPERTISES
MANAGER
COOPERATION
COOPERATING MANAGER
INFORMATION TASKS
INFORMER EXECUTOR DISASTER DOMAIN
Disaster Manager: simple model example Infrastructure Network
Real Emergency Domain Agent 1
I 1 P K
Agent 2
P I 2 K
Agent 3
P I 3 K - - -
Agent n
P I n K I I : Information P : Preferences K : Knowledge
Agent Manager
P K
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.
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
EXPERIMENT: Architecture incrementing
To describe the World Simulator and the Proto-Personoid and the interaction between them, will be used the following symbolization ADVISOR
DOMAIN
SUPERVISOR COOPERATING MANAGER Constrain Environment INFORMER Domain Body World Animator I P Personoid Animator Absolute Observer Decomposition of different fields of the Agent 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.
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]
DSS IDSS
Provides passive
Informational
Aid and Toolkits Provides active, partially autonomous
Decisional
which involve human-like computational intelligence.
Aid
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
.
Modelling Disaster Domain: Disaster Prop. Map
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.
0 1 2 3 4 5
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.
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
Test Case: Disaster Propagation Map (DPM)
TEST Case: Time Diagram without intervention PROPAGATION OF EMERGENCY WITHOUT INTERVENTION
Evolution of the DPM without intervention Forest Others Factory Factory tubes Chicken Farm Citizens River City Aqueduct Combined together the DPM with the Time Diagram without intervention, this evolution in time will be obtained
GEA: IPK Cognitive Agent
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
GEA: Demo
Click here for demonstration
References 1.
2.
3. TOGA Meta-theory Web page: http://erg4146.casaccia.enea.it/wwwerg26701/Gad toga.htm
4.