Presentazione di PowerPoint

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 Intelligent
Agents' Architecture
Presentation outline

• Intelligent Agents' 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 Caputos 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
SOCIO-COGNITIVE ENGINEERING PARADIGMS
A TOGA PROPOSAL 2

• IPK
• Informations ( I )
• Preferences ( P )
• Knowledges ( K )
• I Kx I I, I ? DD
• Kx ? K
• Kx Ps (K, I)

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

K
P
IPK paradigm 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 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
7
TOGA Meta-Modeling Framework
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.
8
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
COOPERATING MANAGER
MANAGER
ADVISOR
INFORMATION
TASKS
EXECUTOR
INFORMER
DISASTER DOMAIN
10
Disaster Manager simple model example
Infrastructure Network Real Emergency Domain
Agent 1
Agent 2
Agent 3
Agent n
In
I1
I2
I3
- - -
K
P
K
P
K
P
K
P
I Information P Preferences K Knowledge
I
K
P
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
PERSONOID ANIMATOR
WORLD SIMULATOR
PROTO- PERSONOID
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
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
Body
Domain
World Animator
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.
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 Decisional
Aid 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.
• its 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
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-to
ga.htm 4.