Antonio de Padua A. Oliveira

1
Integrating Scenarios, i, and AspectT in the
Context of Multi-Agent Systems

• Antonio de Padua A. Oliveira
• Eduardo Magno L. Figueiredo
• Luiz Marcio Cysneiros
• Carlos Jose P. Lucena
• Julio Cesar Sampaio do Prado Leite
• padua_at_ime.uerj.br
• padua, emagno, lucena, julio_at_inf.puc-rio.br
• apadua, cysneiros_at_yorku.ca

2
Work at a glance

• Introduction
• Scenarios technique
• The i Model - Expert Committee
• The Strategic Dependency Model
• The Strategic Rationale Model
• Aspect-oriented technology
• The Framework Structure
• A High-Level View
• Conclusions and Future Works

3
Motivation

• The MAS Development Life Cicle
• We use the traditional
• (1) understand the problem and (2) solve.

(1) Inception Elaboration Requirements
(2) Construction Implementation

• The MAS Modelling needs concepts and metaphors
  that reflect the way we understand the world
• MAS involves a large number of intentional actors
  with opportunities and vulnerabilities Cysneiros
  and Yu.

4
Motivation

• Manage and control the complexity
• MAS modeling process faces 3 additional types of
  interactions compared with the traditional
  software modeling Jennings, Silva et all.
• Traditional systems Actor System
• MAS Actor System
• Actor Agent, Agent System, and Agent
  Agent
• MAS deals with agenthood properties (Autonomy,
  Adaptation, and Interaction) as well as aditional
  properties (Collaboration, Learning, and
  Mobility) Wooldridge.
• Each property apears for all the agents.

5
MAS organization agents and environment
The problem Manage the complexity
6
What do we propose? Why?

• Emphasize feedback
• Emphasis in the use of feedbacks in order to make
  the verification and the validation of the
  system.
• The MAS Modelling needs concepts and metaphors
  that reflect the way which we understand the
  world
• Use i framework for modelling
• Link i to scenarios

7
What do we propose? Why?

• Addressing complexity
• Model each important interaction in a dedicated
  diagram.
• Deal with agency properties
• Use one implementation tool that is
  agent-oriented.
• AspectT was chosen because most of the agency
  properties may be classified as cross-cutting
  concerns, therefore suitable to be deal with
  using an aspect-oriented approach.
• Give more attention on the representation of the
  elements reflecting these properties when
  modeling with i.

8
The exemplar The Expert Committee (EC) System

• EC System is a classical example of application
  based on software agents
• EC is a conference management system.
• Software agents can be introduced to the EC
  System in order to assist researchers (members)
  with time-consuming activities in the paper
  submission and reviewing processes.
• EC agents are software assistants, who represent
  actors in different roles of the conference such
  as paper authors, reviewers, committee members,
  chairs and coordinators.

9
The Proposed Integration Process ( SADT )
10
The Scenario Technique Leite

• A scenario is a structured description
• of one situation that uses
• the language of the problem (user domain).
• These situations occur in the real world and the
  construction of scenarios, based on situations,
  needs the peculiar and most used words or phrases
  used in user domain.
• Scenarios are supported by LEL Lexicon Extended
  Language.
• Situations have the following characteristics
• they are concretes and have goals
• they involve actors and resources are used they
  happen at a defined time and place
• they may have constrains, they are individually
  independent, interrelated and they have
  alternative course.

11
(1) DEFINE SCENARIOS, the steps

• Elaborate the LEL
• Make the identification of symbols (words or
  sentences) that are peculiar to the social
  environment.
• Use one or more technique for fact gathering
  (e.g. interviews, observation, document
  reading)
• Classify symbols in LEL as object, subject,
  verb, and state
• Obey (1) the principle of circularity (also
  called closure principle) and the (2) principle
  of minimal vocabulary
• Write the scenarios
• Use the symbols of LEL when describing each
  scenario.
• Describe actors, goals, resources, episodes, and
  constrains.
• Emphasize agency properties (autonomy,
  adaptation, interaction, collaboration, learning,
  and mobility).
• Bring to first level episodes (tasks) that
  implement these properties.

12
Example The scenario Designate articles
First version
13
Example The scenario Designate articles

• resources

• A goal is a condition or state of affairs in the
  world that the actor would like to achieve. E.
  Yu

Last version

• Autonomy

• Learning

• Interaction

• Interaction

• pro-activeness

• Softgoals

14
Intentional Modeling with i E. Yu

• The i framework proposes an agent-oriented
  approach to requirements engineering centering on
  the intentional characteristics of the agent.
  Agents attribute intentional properties (such as
  goals, beliefs, abilities, commitments) to each
  other and reason about strategic relationships.
• Dependencies between agents give rise to
  opportunities as well as vulnerabilities. 
  Networks of dependencies are analyzed using a
  qualitative reasoning approach.
• The framework is used in contexts in which there
  are multiple parties (or autonomous units) with
  strategic interests which may be reinforcing or
  conflicting in relation to each other.

15
Addressing elements from scenarios to i
SCENARIO SCENARIO I MODELING I MODELING
Element multiplicity multiplicity Element
goal 1 .. N 1 goal
context 1
1 resources n 1 1 resource
1 episodes n 1 1 tasks/goals
0 exceptions n 1 1 tasks/softgoal
0 restrictions n 1 1 softgoal/tasks
1 actors n 1 1 actor
() most commom
16
(2) MODEL ITENTIONALITY, the steps

• Pick up actors from scenarios definition. (Who?)
• An actor represented in one scenario will be
  mapped to an actor in i SD model, later we will
  refine the actor representation.
• Model interdependencies between actors. (Why?)
• Use the SD model to express intentional
  relationships. Pick up goals, tasks, resources
  and softgoals from scenarios definition.
• Only one goal dependency can be mapped using the
  goal of the scenario. The scenario goal has a
  functional conception, although the goal in i
  modeling means the intentional agreement between
  two actors.
• Each resource will be mapped either as a resource
  dependency or as a task dependency depending on
  the direction of the dependency and if the actor
  can perform the task needed by the other actor.
• One or more episodes presented in Scenarios
  should be modeled by one task in i model.
• The actor representation can be refined into more
  detailed representation such as roles played and
  positions occupied.

17
(2) MODEL ITENTIONALITY, the steps

• Model, each interaction, the internal
  rationale. (How? How else?)
• Use the SR model to express intentional
  relationships.
• Pick up goals, tasks, resources and softgoals
  from scenarios definition, show elements inside
  of the boundary of the actor (dot-dashed circle).
• Connect the elements using intentional links
  (means-ends link, decomposition, and
  contribution).
• Identify the internal main goal for each actor.
  One actor can have more than one goal. Often one
  actor has one or more intermediary goals.
• High level episodes will map tasks and they will
  be mapped as means-ends links to the goal.
• Alternative episodes will be mapped as
  alternatives in the SR model, if there is more
  than one way to achieve a goal (means-ends link
  to a goal).
• Low level episodes will be sub-tasks connected
  using a decomposition link.
• Resources used in one episode will be mapped
  either as a resource needed by the task or as a
  resource dependency.
• NFRs (quality attributes, such as performance)
  will be softgoals.

18
(2) MODEL ITENTIONALITY, the steps

• Model the intentional delegation
• Use the SR model to express intentional
  relationships.
• Prepare one SR model for each relationship
  between one actor and the agent that will
  represent the actor in the environment.
• It must be decided which duties the actor wants
  to delegate to the agent.
• For each goal (that the agent will support the
  actor), use the similar goal of the actor
  including the word support in the name of the
  agent goal.
• Emphasize MAS properties (autonomy, adaptation,
  interaction, collaboration, learning, and
  mobility).
• Model the intentional relationships among agents.
• Use the SR model to express intentional
  relationships.
• Prepare one model for each relationship between
  two agentes that will be representing actors in
  the environment.
• Emphasize MAS properties (autonomy, adaptation,
  interaction, collaboration, learning, and
  mobility).

• Reasons Validation, verification and to mitigate
  the complexity.

19
Tabel of Symbols the standard
20
Strategic Dependency (SD) Model
21
Components Yu 95

• An actor is an active entity that carries out
  activities to achieve goals by exercising his
  know-how.
• An agent (can be a person) is an actor with
  concrete physical manifestations, such as a
  human.
• Agent, Role, and Position are specializations of
  generic Actor.
• An agent occupies positions.
• Agents play roles.
• A position covers a role (A position is a set of
  roles typically played by one agent).
• A role is an abstrat characterization of the
  behavior of a social actor.
• Roles, positions and agents can each have
  subparts.

22
Components
23
EC i Models
Chair ChairAgent

• Strategic Dependency (SD) Model
• Strategic Rationale (SR) Models
• (3 diagrams for each couple actors ? 34 1 13
  diagrams)
• Reviewer ?? Chair
• Reviewer ?? ReviewerAgent
• ReviewerAgent ?? ChairAgent
• SR Models Author Chair
• SR Models Reviewer Chair
• SR Models Coordinator Chair
• SR Models Committee Member Chair

24
SR Model Author Chair
25
Detailed in another SR model
SR Model Reviewer Chair
26
SR Model Reviewer ReviewerAgent
27
SR Model ReviewerAgent ChairAgent
28
AspectT Garcia
Component

• In the AspectT approach, an agent is an object
  with added features and aspect notion is used to
  enrich objects with the agents properties in a
  transparent way.
• Objects can be considered the basic structure for
  building agents. However, a single agent is a
  much richer abstraction than an object, and then
  the approach emphasizes separation of agency
  concerns in order to reason about the agent
  behavior from different perspectives.

29
AspectT Garcia
Component

• AspectT software framework supports modeling
  agency properties in a modular way.
• Each of the agents properties should be modeled
  as an aspect due to their crosscutting nature.
• Supports the OO programming of
• Agents, goals, plans, actions, and beliefs.
• Supports the AO modularization and programming
  of
• Interaction, Adaptation, and Autonomy
• Collaboration, Learning, and Mobility.
• Supports the integration with other MAS
  platforms
• JADE, TSpaces

30
AspectT
Component
AspectT
AspectAd (adaptation)
AspectCo (collaboration)
AspectL (learning)
Kernel
AspectInt (interaction)
AspectAut (autonomy)
AspectM (mobility)
31
High-Level View
Knowledge Adaptation
Behavior Adaptation
Learning
Adaptation
Information Gathering
Learning Knowledge
IKnowledge
IServices
Message Reception
Traveling
Message Sending
Interaction
Mobility
Kernel
Extrinsic Knowledge
Collaboration Protocol
Role Binding
Execution Autonomy
Goal Creation
Autonomy
Legend
Collaboration
aspectual component
component
crosscutting interface
normal interface
32
Flexible Composition

• Expert Committee

• learning component
• sensing behavior

33
Addressing elements from i to AspectT
I model AspectT framework
actor agent role
agent agent role
dependency message / event
goal goal
softgoal aspect
task plan
resource belief
34
Heuristics used to derive elements in AspectT

1. Actors and Agents in SR models will be mapped as
   Agent and Roles class in AspectT.
2. Because agents play roles, AspectT Framework
   permits specializations of roles (e.g. Author,
   Reviewer, Chair, and so on). Agents can play one
   or more roles in this platform. Agents must be
   linked with the correspondent role.
3. Both dependency between two agents and between an
   agent and an actor will be mapped using either
   class Message or class Event (depends on the
   direction of the dependency). If the element
   (goal, softgoal, task, or resource) is sent it
   will be mapped as a class Message. If the element
   is received it will be mapped as a class Event.
4. A Goal will be mapped to a ReactiveGoal.

35
Heuristics used to derive elements in AspectT

1. A Task will be mapped to a ReactivePlan. Tasks
   can be specialized if there are alternatives.
2. A Resource will be mapped as a belief.
3. After having mapped goals, tasks, and resources,
   the attributes of these elements should be
   created.
4. A ReactivePlan must be linked with the
   correspondent ReactiveGoal.
5. Each ReactivePlan should be created and linked
   with the correspondent class of agency property
   interaction, adaptation, autonomy, collaboration,
   learning, and mobility.
6. For each Softgoal (NFR) one new aspect must be
   created the same way as well as agency properties
   has been created previously into the framework.

36
Mapping elements of Reviewer- Agent using the SR
model Reviewer Reviewer-Agent.
From i to AspectT
37
(3) BUILD MAS, the steps
Directions of design

1. Refine component Kernel
2. Refine component Interaction
3. Refine component Adaptation
4. Refine component Autonomy
5. Refine component Mobility
6. Refine component Learning
7. Refine component Collaboration

38
User interface to show the system implementation
- 1
39
User interface to show the system implementation
- 2
40
Advantages and Results

• Scenarios
• Scenarios prior to start modeling helped us to
  get a good understanding of the problem.
• The heuristics to derive i models were also very
  useful for us, allowing us to get to initial
  versions of the i models very easily and fast.
• AspectT
• The programming became straightforward because
  AspectT was implemented, and the heuristics to
  use the i models as a front-end to AspectT were
  simple to use.
• The framework is still limited for supporting
  NFRs.
• Produtivity
• Team (two software engineers) spent around 35
  hours describing scenarios and 55 hours
  developing i models.
• The example used one very well trained programmer
  in the AspectT. He spent only 40 hours. The team
  spent 18 hours on testing and fixing bugs.

41
Conclusions and Future Works

• Evaluate the framework using another example.
• Can it be improved?
• And to evaluate, more accurately, the adequacy of
  the approach.
• Integrating the approaches was an easy task and
  the time spent to develop the resultant
  application is encouraging.
• Future work point to investigate more detailed
  backward traceability from i models to
  scenarios
• i.e. how can we pinpoint the scenario that will
  be affected by any new feature we may want to add
  while developing and evaluating i models.
• We also intend to develop heuristics to allow
  scenarios to represent and deal with
  intentionality
• bringing the use of intentionality to very early
  stages of the software development process.

42
References
01 AspectJ The AspectJ Programming Guide.
online http//eclipse.org/aspectj/, December de
2004. 02 Castro, J. Kolp, M. Mylopoulos, J.
(2002) "Towards Requirements-Driven Information
Systems Engineering The Tropos Project." In The
13th international conference on advanced
information systems engineering, Oxford Elsevier
Science Ltd, v.27, n.6. p. 365-389. 03 L.M.
Cysneiros and E. Yu. Requirements Engineering for
Large-Scale Multi-Agent Systems Book chapter in
Software Engineering for Large-Scale Multi-Agent
Systems Research Issues and Practical
Applications.  A. Garcia, C. Lucena, F.
Zambonelli, A. Omicini and J. Castro (eds.) LNCS
2603, Springer Verlag. 2003.  (revised and
extended version of  SELMAS02) 04 Deloach, S.
et al. Multiagent Systems Engineering.
International. In Journal of Software
Engineering and Knowledge Engineering,
11(3)231--258, 2001. 05 Garcia, A. F. From
Objects to Agents An Aspect-Oriented Approach.
PhD Tese, PUC-Rio, 2004. 06 Garcia, A. F.
Lucena, C. J. P. Cowan, D. D. Agents in
Object-Oriented Software Engineering In
Software, Practice Experience, Elsevier, vol.
34, Issue 5, pp. 489-521, May 2004. 07
Jennings, N., An Agent-Based Approach for
Building Complex Software Systems Communications
of The ACM, April 2001, Vol. No 4.
43
References
08 Leite, J.C.S.P., Hadad, G., Doorn, J.,
Kaplan, G. A Scenario Construction Process -
Requirements Engineering Journal Vol. 5, N. 1,
Pags. 38 -- 61, (2000), Springer-Verlag London
Limited. 09 Leite, J. C. S. P. Doorn, J. H.
Hadad, G. D. S. and Kaplan, G. N. Scenario
Inspections - Requirements Engineering Journal
10.1007/s00766-003-0186-9 Springer Verlag -
London Limited 2004. 10 Ross, D. T.
"Structured Analysis (SA) A Language for
Communicating Ideas", IEEE Transactions on
Software Engineering Vol. SE-3 NO. 1, 1977. 11
Silva, V. Lucena, C. "From a Conceptual
Framework for Agents and Objects to a Multi-Agent
System Modeling Language", In Sycara, K.,
Wooldridge, M. (Edts.), Journal of Autonomous
Agents and Multi-Agent Systems, Kluwer Academic
Publishers, 2004. 12 Wooldridge, Michael, An
Introduction to Multi-Agent Systems, John Wiley
and Sons Limited Chichester, 2002, ISBN
047149691X 13 Yu, E. Modeling Strategic
Relationships for Process Reengineering. PhD
Thesis, Graduate Department of Computer Science,
University of Toronto, Toronto, Canada, 1995, pp.
124. 14 E. Yu Agent Orientation as a Modeling
Paradigm  Wirtschaftsinformatik. 43(2) April
2001. pp. 123-132. 15 Yu, E., Agent-Oriented
Modeling Software Versus the World In
Agent-Oriented Software Engineering AOSE-2001
Workshop Proceedings, Montreal, Canada - May 29th
2001. LNCS 2222.
44
Bibliography

• AspectJ The AspectJ Programming Guide. online
  http//eclipse.org/aspectj/, Dezembro de 2004.
• Paolo Bresciani, Anna Perini, Paolo Giorgini,
  Fausto Giunchiglia, J. Mylopoulos, Tropos An
  Agent-Oriented Software Development Methodology,,
  In Journal of Autonomous Agents and Multi-Agent
  Systems, v8, i3, pp. 203-236, 2004.
• Jaelson Castro. Manuel Kolp. John Mylopoulos.
  Tropos Toward Agent-Oriented Information Systems
  Engineering. In Position Paper _at_ the Second
  International Bi-Conference Workshop on
  Agent-Oriented Information Systems AOIS2000.
  2000. Stockolm, Sweden, June 5-6.
• Castro, J. Kolp, M. Mylopoulos, J. (2002)
  "Towards Requirements-Driven Information Systems
  Engineering The Tropos Project." In The 13th
  international conference on advanced information
  systems engineering, Oxford Elsevier Science
  Ltd, v.27, n.6. p. 365-389.
• Cysneiros and Yu
• Garcia, A. F. Lucena, C. J. P. Cowan, D. D.
  Agents in Object-Oriented Software Engineering
  In Software, Practice Experience, Elsevier,
  vol. 34, Issue 5, pp. 489-521, May 2004.
• Garcia, A. F. From Objects to Agents An
  Aspect-Oriented Approach. PhD Tese, PUC-Rio,
  2004.
• Jennings, N. R. and Wooldridge, M. (2000)
  Agent-oriented software engineering. In Bradshaw,
  J. (Ed.) Handbook of Agent Technology, AAAI/MIT
  Press.
• Jennings, N., An Agent-Based Approach for
  Building Complex Software Systems Communications
  of The ACM, April 2001, Vol. No 4.

45
Bibliography

• Leite, Julio C. S. P. Oliveira, A de Padua A
  Client Oriented Requirements Baseline,
  Proceedings of the Second Interantional Symposium
  on Requirements Engineering, RE95, IEEE Computer
  Society Press, 1995, pp. 108-115.
• Leite, J. C. S. P. Doorn, J. H. Hadad, G. D. S.
  and Kaplan, G. N. Scenario Inspections -
  Requirements Engineering Journal
  10.1007/s00766-003-0186-9 Springer Verlag -
  London Limited 2004.
• Luck, M. d'Inverno, M. A conceptual framework
  for agent definition and development. The
  Computer Journal, 44(1)1--20, 2001.
• Mulopoulos, J., Kolps, M., Casro, J. (2001) "UML
  for Agent-Oriented Software Development the
  Tropos Proposal." In Proceedings of the Fourth
  International Conference on the Unified Modeling
  Language, Canada.
• Potts, C Using schematic scenarios to
  understand user needs In Proceedings of DIS95
  - symposium on designing interactive systems
  processes, practices and techniques. ACM Press,
  University of Michigan, pp 247256 1995.
• Ross, D. T. "Structured Analysis (SA) A
  Language for Communicating Ideas", IEEE
  Transactions on Software Engineering Vol. SE-3
  NO. 1, 1977.
• Silva, V., Garcia, A., Brandao, A., Chavez, C.,
  Lucena C., and Alencar, P. Taming Agents and
  Objects in Software Engineering, In Software
  Engineering for Large-Scale Multi-Agent System,
  Garcia, A., Lucena, C., Zamboneli, F., Omicini,
  A, and Castro, J., Eds., LNCS, Springer-Verlag,
  2003.Silva, V. Lucena, C. "From a Conceptual
  Framework for Agents and Objects to a Multi-Agent
  System Modeling Language", In Sycara, K.,
  Wooldridge, M. (Edts.), Journal of Autonomous
  Agents and Multi-Agent Systems, Kluwer Academic
  Publishers, 2004.

46
Bibliography

• Silva, V., Garcia, A., Brandao, A., Chavez, C.,
  Lucena C., and Alencar, P. Taming Agents and
  Objects in Software Engineering, In Software
  Engineering for Large-Scale Multi-Agent System,
  Garcia, A., Lucena, C., Zamboneli, F., Omicini,
  A, and Castro, J., Eds., LNCS, Springer-Verlag,
  2003.
• Weiss, Gerhard, Multi-Agent Systems A Modern
  Approach to Distributed Artificial Intelligence,
  MIT Press, 1999. ISBN 0-262-23203-0
• Wooldridge, Michael, An Introduction to
  Multi-Agent Systems, John Wiley and Sons Limited
  Chichester, 2002, ISBN 047149691X
• Yu, E. Modelling Strategic Relationships for
  Process Reengineering. PhD Thesis, Graduate
  Department of Computer Science, University of
  Toronto, Toronto, Canada, 1995, pp. 124.
• Yu, E. Towards Modeling ad Reasoning Support for
  Early-Phase Requirements Engineering,
  Proceedings of the 3rd IEEE International
  Symposium on Requirements Engineering, Washington
  D.C., USA, Jan. 1997, pp. 226-235.
• Yu, E., Agent-Oriented Modelling Software Versus
  the World In Agent-Oriented Software Engineering
  AOSE-2001 Workshop Proceedings, Montreal, Canada
  - May 29th 2001. LNCS 2222.
• Zorman, L., Requirements envisaging by utilizing
  scenarios (rebus). PhD dissertation, University
  of Southern California - 1995.
• Zheng You, Julio Cesar Leite, Eric Yu, An
  Assessment of i Modeling and Evaluation Using
  the London Ambulance Service Case Study,
  Department of Computer Science, University of
  Toronto.