Consiglio Nazionale delle Ricerche
Istituto di Calcolo e Reti ad Alte Prestazioni

Towards Self-Adaptation and
Evolution i...
BPMN
Commercial workflow engines follow the
plan as in the blueprint (BPMN, BPEL)
The execution model is based on the
pet...
Self-Adaptive Workflows
•

In current workflow systems,
• a unexpected situation generates a fail to the
standard plan,
• ...
Our Approach
FROM BPMN to Goals
Decoupling WHAT and HOW
We

desire that BPMN is used for

◦ describing the result to address,
◦ not “how to address it”
...
Goal in GoalSpec
Goal
TRIGGERING CONDITION
The state of the world that
must hold because the goal
becomes active

ACTOR LI...
Extracting GoalSPEC from BPMN
The workflow execution may be seen as a

finite set of state transitions from the
start eve...
Examples
Every FlowNode potentially impacts the state
of the workflow
WHEN completed(client_credential)
THE user role SHAL...
THE Agent ARCHITECTURE
Why Software Agents
Agents encapsulate autonomy and

proactivity.
Agents ground on the classic AI loopmodel: sense – rea...
The BDI Architecture
(mental states)

Agent1

Agent2

AgentN

(plans)

(act and perceive)

Environment

13
Context-Awareness and SelfAwareness
•

Proactive contextual matching of the
behavior (how) with expected results (what)

•...
The Self-Aware Agent
SYSTEM GOALS

Self-Aware agents
knows:
•system goals
•their own execution
state
•their capabilities a...
Self-Organization Algorithm
Goal commitment is a social activity
Each goal prescribes a state transition (TC ->

FS)

A...
A solution is a set of potential contracts for addressing sub-goals:
contract( potential commitment, curriculum, request i...
Conclusions:
The new Lifecycle of Business Process
Business
Analyst

models

Theebusiness sanalyst
Th busines analyst itio...
Conclusions:
The components of the MAS Solution
•

Agents are specialized: every agent owns its own capacities.
– User cap...
Future Works
Agents

Learns by

◦ Experience  to improve owned capabilities
◦ Studying  to acquire new capabilities
Co...
Thanks for your Attention
Luca Sabatucci
sabatucci@pa.icar.cnr.it

Consiglio Nazionale delle Ricerche
Istituto di Calcolo ...
Overview of a Self-Adaptive Workflow System
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Overview of a Self-Adaptive Workflow System

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Overview of a Self-Adaptive Workflow System

  1. 1. Consiglio Nazionale delle Ricerche Istituto di Calcolo e Reti ad Alte Prestazioni Towards Self-Adaptation and Evolution in Business Process Luca Sabatucci 15 Ottobre 2013
  2. 2. BPMN Commercial workflow engines follow the plan as in the blueprint (BPMN, BPEL) The execution model is based on the petri-net model: token and activation •
  3. 3. Self-Adaptive Workflows • In current workflow systems, • a unexpected situation generates a fail to the standard plan, • alternative plans can not be autonomously considered • In order to enable self-adaptation, • rigid constraints of a workflow must be relaxed • plans should be searched in a broader solution space.
  4. 4. Our Approach
  5. 5. FROM BPMN to Goals
  6. 6. Decoupling WHAT and HOW We desire that BPMN is used for ◦ describing the result to address, ◦ not “how to address it” We use a Goal-Oriented approach GoalSPEC: a language to describe business goals to delegate to the system
  7. 7. Goal in GoalSpec Goal TRIGGERING CONDITION The state of the world that must hold because the goal becomes active ACTOR LIST Who is responsible FINAL STATE The state of the world that must be true for considering the goal addressed In oorderto des In rder to des ibe cr cr Trigggercco dit ibe Tri ger onndit n io n io andd an FFinalstaate inal st te weeuusean oo to w se an nnto gica lo gicalapppro h lo l ap roac h ac (WHEN MESSAGE book_request(Book) RECEIVED FROM THE Client ROLE AND WHEN available(Book) ) THE Clerk ROLE SHALL ADDRESS book_checkout(Book,Client) (BookManagment example) Each goal in GoalSPEC Each goal in GoalSPEC defines aa defines ition, desireddStateeTrans ition, desire Stat Trans G:TC -> FS G:TC -> FS
  8. 8. Extracting GoalSPEC from BPMN The workflow execution may be seen as a finite set of state transitions from the start event to the end event. Where: each FlowNode generates a single step of the transition We identify intermediate transitions
  9. 9. Examples Every FlowNode potentially impacts the state of the workflow WHEN completed(client_credential) THE user role SHALL ADDRESS ( done(booking) AND sent(receipt,client) ) OR error(booking) AFTER 1 hour SINCE WHEN done(login) OR WHEN user_number > MAX_USERS OR WHEN thrown(stopping_signal) THE user role SHALL ADRESS done (logout)
  10. 10. THE Agent ARCHITECTURE
  11. 11. Why Software Agents Agents encapsulate autonomy and proactivity. Agents ground on the classic AI loopmodel: sense – reason – act BDI agents represent a good abstraction for self-awareness and contextawareness MAS are a flexible and powerful method for distributed reasoning
  12. 12. The BDI Architecture (mental states) Agent1 Agent2 AgentN (plans) (act and perceive) Environment 13
  13. 13. Context-Awareness and SelfAwareness • Proactive contextual matching of the behavior (how) with expected results (what) • The agent must be able to reason • on evolving business goals • on the execution context • on its capabilities
  14. 14. The Self-Aware Agent SYSTEM GOALS Self-Aware agents knows: •system goals •their own execution state •their capabilities and how capabilities can be used (means-end reasoning) CAPABILITIES Agent1 Agent2 AgentN (plans) (UI) Capability encapsulat es the ability to manipulat e resources, to call web services or to interact with humans Environment System goals derive from business analysis, when some business goal is delegated to the system t) en tm mi m (co (UI) Resources (databases, …) Business Analyst Web Service Web Service Workflow User 15
  15. 15. Self-Organization Algorithm Goal commitment is a social activity Each goal prescribes a state transition (TC -> FS) Agents may own capabilities for addressing sub-transitions (sinput -> soutput) A Solution is a decomposition of the main transition TC -> FS into a set of sub-transitions A Team prescribes a collaboration among many agents, and it is regulated by contracts and rewards.
  16. 16. A solution is a set of potential contracts for addressing sub-goals: contract( potential commitment, curriculum, request income) TThealalgori m he gorith thmfor distriribute an forsearching gsolutitions is dist butedd an re searchin solu ons is dd recursiv cursivee system-goal goal-set {TC | FS} sub-goal G1..G5 G1 G2 {TC | IS1} AGENTS G3 {IS1 | IS2} {IS2 | IS3} G5 {IS3 | IS4} I may commit to G3 A1 ch Agents tries sto mat ch Agents trie to mat goal s their rcapacicitieswith goal thei capa tie with transitionnTC -> FS transitio TC -> FS de IF Agents alalsodecicide IF Agents so de the PARTICIPATEEto the PARTICIPAT to H solutionnanddWHIC H solutio an WHIC PART play in it, PART play in it, r depending gon thei r dependin on thei workinngqueuee worki g queu G4 AN Aj Recursionnstops w Recursio stops w n no he he solutionnisisdiscover n no solutio discoveeddor in re or in theetrivivialcase of nu th tr ial case of nu ll ll transition transition contract( {IS2 | IS3}, my_curriculum, 1) backward-goal decompose and recursively search sub-goals {TS | IS2} A1 A2 {IS4 | FS} forward-goal {IS3 | FS} AN A1 A2 AN ay be Many ysolutions m ay be Man solutions m discovered. . discovered alu ed ev ated Each solutionnisisev aluat Each solutio according gto: : accordin to ts’ completeness,s,agen ts’ ) completenes agen cost ) tal st reputationnanddto tal co reputatio an to
  17. 17. Conclusions: The new Lifecycle of Business Process Business Analyst models Theebusiness sanalyst Th busines analyst itional l continues sto useetrad itiona continue to us tradhis odel his instruments to m odel instruments to m processes s processe revises The system automatically translates BPMN into goals Every yagent in th Ever agent in th syst ee em autonomously de system autonomously de des ci whennto commit cides whe to committo so me to some goalal go GoalSPEC isis a GoalSPEC a language for language for expressing ggoals expressin goals that tgrounds son tha ground on ontology yandd ontolog an defines sa agoalalas the define go as the tuple tuple (actor,r, (acto trigger-condition, trigger-condition, final-state) ) final-state GoalSPEC injection worker Business Expert interacts commits to analyzes analyzes Running MAS analyzes commits to analyzes 18 Environment perturbations
  18. 18. Conclusions: The components of the MAS Solution • Agents are specialized: every agent owns its own capacities. – User capacities are used to interact with humans and monitor their activity – Service capacities are used to manipulate the environment. • Agent are peers: there is not a pre-established organization. They organize themselves in teams every time a new workflow starts – The self-org algorithm considers many criteria (experience, cost, trust) – The team is the candidate group of agents for addressing the workflow, in a given context – Anyway, the context may change for some reason during the execution: • In case of starvation the team tries to relax some constraints • If some task fails, the team is dismissed and a new team is formed • If no alternative team can be found, the analyst is informed of failure • Commitment: when an agent is involved in a team, it tries to address its responsibilities at best of its possibilities – It waits for triggering conditions hold – It selects and executes the proper capacity or composition of capacities – It checks that result is the expected final state • Trust and Reward:: agents that successfully complete their task gain reputation and they increase their chance to be selected again.
  19. 19. Future Works Agents Learns by ◦ Experience  to improve owned capabilities ◦ Studying  to acquire new capabilities Coupling Goals and Norms in GoalSPEC Open Systems and Clouds
  20. 20. Thanks for your Attention Luca Sabatucci sabatucci@pa.icar.cnr.it Consiglio Nazionale delle Ricerche Istituto di Calcolo e Reti ad Alte Prestazioni

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