AgentOriented Software Engineering

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Agent-Oriented Software Engineering

• Extension of traditional software Engineering
• - Presenter
  
• Purnima Devu

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Why AOSE ???

• 1.To cope up with open and dynamic environments.
• 2.To reach the realm of real-world of software
  development, leaving artificial intelligence
  laboratories.

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Basis for AOSL

• The possibility to model a software system at the
  agent level of abstraction.
• Agent-oriented analysis and development is based
  on object oriented methodologies enhanced with
  some agent-based concepts.

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Multi-agent system

• A multi-agent system is represented through both
  internal and external models.
• The external models mainly described
• the interactions between agents.
• The internal models is entirely dedicated to
  the description of the internal of the different
  agents in term of their beliefs, desires and
  intentions.

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Definition of software Agent

• An agent is a software system that is
• 1. situated in some environment,
• 2. capable of autonomous actions in
• order to meet its objectives and
• 3. capable of communicating with
• other agents.

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Important characteristics of an agent

• 1.The ability to act in complete autonomy
• 2.Social ability, the possibility that agents
  have to communicate with other agents.

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Agent Versus Object

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1st Difference

• Agents interact with the environment to get the
  essential information to work

• Objects are not intended to interact with the
  environment.

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2nd Difference

• An agent is explicitly associated with a goal.

• An object is NOT explicitly associated with a
  goal.

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Necessity of Autonomy

• To deal with dynamic environments to allow
  software systems adapting to unpredictable
  situations.
• To cope up with all possible courses of events
  that may occur in the Web.
• To achieve Inter-operability.
• To avoid waiting for developers to evolve new
  products to face WWW.

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ACL

• ACL - Agent Communication Language - is a
  language for the communication between agents.
• ACL is very close to KQML (Knowledge Query
  Manipulation Language), which is
• probably, the most known agent communication
  language.

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ACL Message

• Structured in two parts
• 1) Communication and 2) Content
• The communication part carries the
  identification of the sender and the receiver.
• The content part bares the meaning of the
  message and it is structured as a performative
  and a domain content.
• The performative is a domain-independent verb
  that specifies the meaning that the sender of the
  message wanted to associate with the domain
  content.

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ACL Message

• NO prescribed language for expressing domain
• contents.
• Agent learns the language and onotology as it
  receives a message.
• The structure of a ACL message causes overhead
  due to redundancy in some cases.
• ADVANTAGE- message processing is simpler
• may be easily used for
  the interaction
• of heterogeneous
  agents.

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ACL Message

• Performatives-
• inform
• request
• query,
• used by agents to communicate.
• The domain content of the message is
• a sentence expressed in some language and
  following some ontology that actually bares the
  meaning of the message.

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Agent-Oriented diagrams

• These diagrams support
• 1.The architecture of the multi-agent system
• 2 The ontology followed by the agents
• 3.The interaction protocols used
• to coordinate agents

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Ontology Diagrams

• allow defining a model of the environment
  composed of entities and relations.
• used to specify the predicates that agents can
  use to communicate.

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Example of ontology diagram for a CD shop
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Architecture diagram of the CD shop example.
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Cassioperia Methodology

• Cassiopeia methodology is based on a bottom up
  development process.

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Methodology Steps

• The methodology proposes three steps.
• 1- identifies the elementary behaviors that are
  implied by the overall system task.
• 2- identifies the relationships between
  elementary behaviors.
• 3- identifies the organizational behaviors of
  the system representing the way in which agents
  form themselves into groups.

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MAS-CommonKADS Methodology

• MAS-CommonKADS methodology adds technologies from
  object-oriented methodologies and from protocol
  engineering for describing the agent protocols.
• starts with a conceptualisation phase

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Models

• agent model -- describing the main
  features
• of agents
• task model -- describing the tasks
  carried out
• by agents
  
• expertise model -- describing the
  knowledge
• that
  agents need to carry
• out the
  tasks
• coordination model -- describing
• 
  interactions between agents.

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Models

• organization model -- describing the
  organization of the agent society,
• communication model -- describing the
  interaction between humans and agents
• design model -- that collects
• the previous
  models.

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GAIA Methodology

• The Gaia methodology tries to build a multi agent
  system
• through a process of organizational design.
• This methodology borrows some terminology and
  notation from object-oriented analysis and design
  and, in particular, from FUSION.
• No one-to-one mapping between roles
• and agents, but often an individual can take
  on many roles.

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Objective of GAIA

• Objective -- to capture the system organization
  as a collection of roles.

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Definition ROLE

• A role is defined by 4 attributes
• 1. Responsibilities to determine
  functionality and are the key
• role attributes
• 2. Permissions, are the right associated
  with a role.
• 3. Activities are computations associated
  with a role that an
• agent can take without interacting with
  other agents
• 4. Protocols, define the way that a role
  interact with other roles

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Using UML for developing Agent Systems

• This research led to the extension of UML.
• But are not completely accepted because they
  are not yet supported by CASE tools.
• AOS do not need extensions to the usual UML
  diagrams and any off-the-shelf CASE tool can
  support it.
• .

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Advantage

• Advantage- allow architects use notations
  without either
• -- the need for agent-enabled CASE
• tools or,
• -- when the CASE tool support UML extensions
  the need for extending the CASE tool with new
  diagrams

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Agent-Oriented Analysis

• Intended to examine the domain of the problem to
  specify what the software system is intended to
  do.
• Is independent from the technology used to
  develop the system
• The system itself should be seen as a black box
  interacting with its environment.

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Agent-Oriented use case diagram

• Agent is used to ease the implementation of
  tools managing such diagrams.
• Agents as treated as actors.

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Agent-Oriented Design

• Requires modeling the architecture of the
  multi-agent system and the interactions between
  agents.
• Such elements can be modeled using some UML class
  diagrams,
• Each role is associated with an agent class.
• we introduce the stereotype agent to tag such
  classes because they equals the ones used in
  agent-oriented use case diagrams.
• Associations between agent classes describe
  possible associations between agents playing
  different roles.

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Agent-Oriented Design

• stereotype agent is used to tag agent classes
  coz, they equal the ones used in agent-oriented
  use case diagrams.
• Associations between agent classes describe
  possible associations between agents playing
  different roles

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Agent-Oriented Design

• An agent class can be used to associate a set of
  actions with a role.
• Actions are represented as public methods of the
  class..

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Problems with application-specific interaction
protocols

• A run-time description of a protocol is
  insufficient
• Explicit help from the developer is needed.
• Result- Agents may not be able to run in open
  systems where third-party agents join and leave
  the system dynamically.

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Need for Agent-Oriented support

• To enable the development
• of Intelligence business agents
• for adaptive, reusable software.
• Examples of Agent-Oriented programming languages
  are
• Agent0 and Telescript.

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Agent-Oriented Implementation

• Implemented in Java taking advantage of one of
  the available agent platforms.
• DEF Agent platforms are run-time environments
  that manage the lifecycle of agents and provide
  the necessary communication resources means for
  sending and receiving messages.

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Agent-Oriented Implementation

• The communications reach either agents within the
  same platform or agents on different platforms
  transparently to the developer.
• This is a fundamental characteristic of agent
  platforms as it allows supporting open systems
  where agents join and leave dynamically.

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Toolkit for AOSE - ParADE

• A set of development tools supporting the
  developer at the agent level and at the object
  level.
• The agent level allows describing agents in terms
  of their characteristics such as beliefs, goals
  and social organization.
• At this level of abstraction, the developer can
  produce UML models to generate code for agents.

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Toolkit -ParADE

• ParADE does not integrate any CASE tool because
  the code generator works with XMI files that any
  off-the-shelf CASE tool should be able to
  produce.
• The code generated from agent-level models is
  only a skeleton.

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Components of ParADE

• The components of ParADE are
• 1. knowledge base and
• 2.the planning engine.
• These components have access to the ParADE
  development library. production of code from UML
  models at
• These components also help the production of code
  from the UML models at the agent level without
  taking implementation details into account.

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Conclusions

• Software engineering is founded on the
  possibility to model a system at different levels
  of abstraction.
• Agent-oriented software engineering introduces a
  new level, called agent level, to allow the
  software architect describing a system in terms
  of interacting agents.
• At this level of abstraction, an agent is
  considered as an atomic entity that communicates
  with other agents to
• implement the functionality of the system.

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Conclusions

• Agent-oriented use case diagrams are simple
  extensions of usual use case diagrams
• These allow introducing agents and modeling
  their interactions with the user, with the
  environment and with the rest of the system.
• Architecture diagrams allow modeling the
  architecture of the multi-agent system

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Acknowledgements

• This work is partially supported by
• CSELT and by the European Commission through the
  contracts IST-1999-12217, CoMMA Corporate
  Memory Management through Agents and
• IST-1999-10211, LEAP Lightweight Extensible
  Agent Platform.

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References

• Agent-oriented Software Construction with UML
• Name Federico Bergenti and
• Agostino Poggi
• Italy
• E-mail bergenti,poggi_at_ce.unipr.it
• Most of the information is taken from
• this reference

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Thank You