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Extending the AAII methodology for programming agents in 3APL

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Extending the AAII methodology for programming agents in 3APL. Pierre-Yves ... Koen Hindriks & Steven Anker. 3APL = ' An Abstract Agent Programming Language ' ... – PowerPoint PPT presentation

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Title: Extending the AAII methodology for programming agents in 3APL


1
Extending the AAII methodology for programming
agents in 3APL
  • Pierre-Yves Schobbens
  • Jean-Christophe Trigaux
  • François Vermaut

2
  • Aim Provide a method to translate AAII models
    into 3APL agent specifications.
  • Plan
  • 1) Introduce the AAII methodology and the 3APL
    language
  • 2) Transform AAII model into 3APL structures
  • 3) Interaction model for the AAII methodology

3
AAII - Methodology
  • External viewpoint
  • Agent model
  • Interaction model
  • Internal viewpoint
  • Belief model
  • Goal model
  • Plan model

4
AAII Agent model
  • Based on UMLs class diagram notation
  • Types instances
  • Belief-state-set goal-state-set
  • Initial-belief-set initial-goal-set

5
AAII Interaction model
  • No standard notation
  • ? users choice
  • MSC HMSC notation from MAS-CommonKADS

6
AAII Belief model
7
AAII Goal model
  • Expressed with predicates of the FOL with modal
    operators (achieve(X), test(X), verify(X))
  • Directly linked to a belief
  • 3 Types
  • Achievement goals
  • Test goals
  • Verify goals

8
AAII Plan model
  • Based on UMLs statechart notation
  • Plan nodes transitions
  • 3 types of nodes
  • Start nodes
  • Internal nodes
  • End nodes (success, fail)
  • Transition triggered by an event, if a certain
    condition is satisfied

9
AAII Plan model example
10
3APL - language
  • Koen Hindriks Steven Anker
  • 3APL  An Abstract Agent
    Programming Language 
  • Based on BDI theory
  • Originalities
  • Combine logic and imperative programming
  • Pratical reasoning rules (PR-rules)

11
3APL-Agent
12
3APL Agent Specifications
  • Belief
  • ? Formula of the FOL
  • Basic Actions
  • ? ? ? ?
  • Goals
  • Bact ? Goal
  • Atom ? Goal
  • If ? ? Beliefs, then ?? ? Goal
  • If ?1, ?2 ? Goal, then (?1?2), (?1?2),
    (?1?2) ? Goal
  • PR-rules
  • head ? guard body

13
Beliefs goals derivation (1)
  • Beliefs Derivation
  • AAII Initial-belief-set ? 3APL beliefBase
  • Syntactic equivalence (predicate of the FOL)
  • Semantic difference
  • AAII beliefs use trivalent logic ltgt 3APL beliefs
    use boolean logic
  • Solution
  • Limit AAII beliefs to boolean logic
  • Goals Derivation
  • AAII achievement or test goals ? 3APL achievement
    or test goals
  • Syntactic differences
  • Modal operators in AAII goals
  • Only ? in 3APL test goals

14
Beliefs goals derivation (2)
  • Semantic differences
  • AAII goals make belief true ltgt 3APL goals
  • AAII achievement goals trigger a plan if
    associated belief is false
  • ltgt 3APL goals PR-rules
  • Solutions
  • In 3APL, explicitly assert corresponding belief
    of a goal when the activated plan succeeds.
  • In 3APL, abort the execution of a PR-rule if the
    associated belief is true.

15
Plan derivation(1)
  • AAII plans are based on UMLs statechart notation
  • AAII plans transitions ? 3APL PR-rule
  • AAII plans events (goals) ? 3APL goals in the
    head of
  • the PR-rule
  • AAII plans actions ? 3APL goals in the body
    of the PR-rule

16
Plan derivation(2)
  • 3APL PR-rules store less information than AAII
    plans
  • AAII plans are splitted into several PR-rules

17
Interaction modeling
  • No standard notation
  • MSC ? model simple communication between agents
  • HMSC ? model higher level protocols

18
Interaction model derivation(1)
  • Messages from MSC diagrams ? 3APL beliefs
  • Message events (received message) ? Waiting for
    the corresponding belief to become true
  • Sending a message ? Asserting a belief in
    receivers beliefBase

19
Interaction model derivation(2)
20
Contributions
  • Implement 3APL agents at a higher level of
    abstraction
  • Extend AAII methodology with MSC and HMSC as
    interaction model
  • Bridge the gap between agent systems modeling and
    agent systems programming.
  • Study case in the e-Business domain

Future works
  • Develop a tool based on this method
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