uimp: sistema multiagente cbr para turismo de salamanca
TRANSCRIPT
Development of CBR-BDI Agents: A Tourist Guide Application
http://gsii.usal.es
Juan M. Corchado
Departamento de Informática y Automática
Universidad de Salamanca
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Development of CBR-BDI Agents
Index: Introduction
Technology review
Proposal
motivation
goals
agents
agents and cbr systems
aplication
demo
conclusions
wireless implementation
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Motivation
The telecommunication industry expects a new expansion with the development of UMTS and third generation phone systems.
The new challenges of this field require new technology that facilitate the construction of more dynamic, intelligent, flexible and open applications, capable of working in a real time environments.
Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
The development of efficient wireless
distributed systems.
Composed of autonomous elements
with reasoning capabilities.
Multiagent technology
JADE-LEAP
Autonomousagent
CBR-BDI system
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Goal– The development of an agent based architecture that
facilitate the construction of:Deliberative agents
– Autonomous– With reasoning capabilities– With communication capabilities– With adaptation capabilities
BDI agents– Believes
– Desires
– Intentions
Case study– tourism guide system– Wireless devices
Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion Cases, Variables, past
experiences, Expected solutions
Plans
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Reactive agents– Autonomous application with response capabilities
Deliberative agents– Autonomous– With reasoning capabilities– With communication capabilities– With adaptation capabilities
BDI Agents: believes, desires and intentions
Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
Agents
PerceptionSensors
ActionsActuators
Environment
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
BDI agent (beliefs, desires , intentions)Belief: stateDesire: set of <final_state>Intention: sequence of <action>
Case: <Problem, Solution, Result> Problem: initial_stateSolution: sequence of <action, [intermediate_state]>Result: final_state
Agent plans the solution strategy
Agent stars to solve a new problem
New CBR reasoning cycle
Agent achieves its goal
CBR solution achieved
Agent updates knowledge
Case retain - learning
Case retrieval Case reuse Case revise
Agent knowledge base-
Case-base
Believes…Desires…Intentions…
Cases
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Operative SystemJAVA j2se, j2me
JADE-LEAP 3.0
Agent (customised)Agent Interaction
Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
JADE - LEAP
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
User [us001]
User [us002]
User [us003]
User [us00X]
………
Tracker agentPerformer agent [us001]
Performer agent [us002]
Performer agent [us003]
Performer agent [us00X]
Planner agent
Internet worldWireless world
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
-<<Role>>-K-base
-Update Believes/Intentions-<<Role Dynamic>>
-VCBP
<<agent>> Planner
- Input-Request ACL for service (Give MRS)-(ACL content = {O, R, hi, UsedBel} )
-O = Objetivos-R = Recursos
-hi : int-UsedBel
<<Capability>> K-base
-Description-Given a set of Preferences about a problem P
-this service offers the Most Replanning-able Solution
<<Service>> Give MRS
TypeInform, Failure
P rotocol:Request-Best Solution for a dynamic environment
Agent Comunication LanguageFIPA ACL
OntologyPlanning ontologyContent Language
FIPA SL
-Input-{ S(p) } S1(p),S2(p),S3(p),..Sn(p) : Posible Solutions
<<Capability>> VCBP
Output:Sf(p) : MRS (Most Replanning-able Solution)
Description:This capability provides the most replanning-able
solution to the performer Agent
Output:S1(p),S2(p),S3(p),..Sn(p) : P osible Solutions
Descr iption:This capability provides solutions that fulfill a
set of given preferences
-Input-Inform ACL for Update Believes/Intentions
-(ACL Content =-b1(t) ,b2(t) ,...bn(t) : Believe
-t : time )
<<Capability>> Update Believes/Intentions
Output:bi(t-1) <- bi( t) : Believe
I[bi(t-1) <- bi( t)] : Intentions
Description:This capability Updates believes and
intentions
Planner Agent class diagram in AUML
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
0 2 4 6 8 10 12
0
1
20
5
10
15
20
25
30
35
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χ 0(α ,β )
χ 0(α ,β )
χ 0(α ,β )χ 0(α ,β )
P a s o 1 : t = t0 P a s o 2 : t = t1
P a s o 3 : t = t2 P a s o 4 : t = t f
step1: t=t0 step2: t=t1
step3: t=t2 step4: t=t3
Glez-Bedia M. y Corchado J. M. (2002) A planning strategy based on variational calculus for deliberative agents. Computing and Information Systems Journal. Vol. 9 No. 2. pp: 2-13. ISSN: 1352-9404
Glez-Bedia M., Corchado J. M., Corchado E. S. ,Fyfe C. (2002) Analytical Model for Constructing Deliberative Agents. Engineering Intelligent Systems. Vol. 10. No 3. pp: 173-185. ISSN 1472-8915.
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
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% Evaluation - degree of satisfaction
Tourists that… 8-10 6-8 4-6 0-4 No answer
Used the help of the agent
14% (55,9%) (4,7%) (2,4%) (0,7%) (36,3%)
Used the help of a tourist guide
23% (62,7%) (19,6%) (8,9%) (1%) (7,8%)
Did not use any of the previous
63% (16,7%) (8,3%) (1,2%) (0,2%) (78,8%)
Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
Tested on 6217 Tourist
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Development of CBR-BDI Agents
Introduction– motivation– goal
Technical Review– agents– cbr-bdi agents– wireless implem.
Proposal– aplication– demo– conclusion
The CBR-BDI agents
• facilitate the construction of distributed wireless system for mobile devices and
• may be adapted for different problem domains, within the constrains imposed by the industry.
The developed infrastructure includes tools
• for generating CBR-BDI autonomous agents that can reason, learn and communicate with the users and with other agents,
• a simple communication protocol based on the FIPA ACL standards, and
• a number of established processes that facilitate the analysis and design of a MAS using AUML.