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BDI Concepts and Agent Oriented Systems

BDI Concepts and Agent Oriented Systems

Slides on BDI Concepts and Agent Oriented Systems from guest lecture I gave at a graduate level Artificial Intelligence (AI) class in Knowledge Representation and Reasoning in May 2003.

The lecture I gave was in two parts. The first part was about the theoretical concepts behind the BDI model. These slides are reproduced here in LaTeX Beamer format. The second part of the lecture was an overview of example large scale industrial deployed multi-agent simulations using a BDI architecture. The slides corresponding to this part of the lecture are not included here.

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Michael Papasimeon

May 22, 2003
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Transcript

  1. BDI Concepts and Agent Oriented Systems Knowledge Representation and Reasoning

    Michael Papasimeon Intelligent Agent Lab 22 October 2003 Michael Papasimeon BDI Concepts 22 October 2003 1 / 16
  2. Outline The Intentional Stance Beliefs, Desires and Intentions Rational Agency

    and BDI Rao and Georgeff’s Theoretical BDI Interpreter Wooldridge’s Agent Control Loops dMARS and JACK BDI Agent Architecture Example dMARS Plan BDI Dynamics References Michael Papasimeon BDI Concepts 22 October 2003 2 / 16
  3. The Intentional Stance The philosopher Daniel Dennet proposed three ways

    (stances) at which we can predict things about the world: Dennet’s Stances Physical Stance Design Stance Intentional Stance Michael Papasimeon BDI Concepts 22 October 2003 3 / 16
  4. Beliefs, Desires and Intentions Internal mental attitudes of a rational

    BDI agent (or mental state): Beliefs What an agent believes about the world, itself and other agents (informational). Desires What an agent want to achieve (motivational). Intentions How the agent tries to achieve desires (deliberational). Michael Papasimeon BDI Concepts 22 October 2003 4 / 16
  5. Rational Agency and BDI Daniel Dennet: Folk Psychology Michael Bratman:

    Rational Agency Rao and Georgeff: Formal Logical Framework Programming Languages: PRS, dMARS, JACK, JAM, C-PRS, IRMA Michael Papasimeon BDI Concepts 22 October 2003 5 / 16
  6. Theoretical BDI Interpreter (Rao and Georgeff) BDI Interpreter initialize-state(); repeat

    options := option-generator(event-queue); selected-options := deliberate(options); update-intentions(selected-options); execute(); get-new-external-events(); drop-successful-attitudes(); drop-impossible-attitudes(); end repeat Michael Papasimeon BDI Concepts 22 October 2003 6 / 16
  7. Basic Agent Control Loop 1 Adapted from Wooldridge... procedure AGENT

    CONTROL LOOP 1 while True do observe-the-world(); update-internal-world-model(); deliberate-about-what-intention-to-achieve-next() use-means-end-reasoning-to-get-a-plan-for-next-intention() execute-the-plan end while end procedure Michael Papasimeon BDI Concepts 22 October 2003 7 / 16
  8. Basic Agent Control Loop 2 Adapted from Wooldridge... procedure AGENT

    CONTROL LOOP 2(B0) B ← B0 while True do ρ ← get next percept(); B ← brf(B, ρ); D ← deliberate(B); π ← plan(B, I); execute(π); end while end procedure Michael Papasimeon BDI Concepts 22 October 2003 8 / 16
  9. Basic Agent Control Loop 3 Adapted from Wooldridge... procedure AGENT

    CONTROL LOOP 3(B0, I0) B ← B0 I ← I0 while True do ρ ← get next percept(); B ← brf(B, ρ); D ← options(BI); I ← filter(B, D, I); π ← plan(B, I); execute(π); end while end procedure Michael Papasimeon BDI Concepts 22 October 2003 9 / 16
  10. dMARS and JACK Implementations of the BDI model Idea of

    plans as reciples (pre-planning) Least commitment Bounded rationality Dynamic environment Goals, beliefs, plans Intentions and run-time (not design time) constructs Michael Papasimeon BDI Concepts 22 October 2003 10 / 16
  11. A BDI Agent Architecture Michael Papasimeon BDI Concepts 22 October

    2003 11 / 16
  12. Example dMARS Plan Michael Papasimeon BDI Concepts 22 October 2003

    12 / 16
  13. BDI Dynamics (1) 1 An event occurs. A goal is

    posted (internal). A change in the environment and hence a change in belief (external). 2 Agent reasoner searches through the plan library to find the set of plans which can handle this event (defined by the invocation condition). 3 This may result in in 10 plans out of 500 which can handle the event. Out of these 10 plans, the agent reasoner then chooses only those which are appropriate for this context – that is, the current situation. Michael Papasimeon BDI Concepts 22 October 2003 13 / 16
  14. BDI Dynamics (2) 5 This may result in 6 plans

    out of the 10 which are applicable in this context. 6 The agent then chooses one of the plans, puts it on the intention stack, and starts executing the plan steps in the plan. 7 This executing plan is called an intention to achieve the original goal. 8 If the plan fails, the agent will try on of the other applicable plans until one of them succeeds in achieving the goal or all of them fail, in which case the goal will fail. Michael Papasimeon BDI Concepts 22 October 2003 14 / 16
  15. BDI Dynamics Notes It is possible to determine which plan

    is chosen in the applicable plan set by using meta-level reasoning. Plans can wait until particular beliefs are satisfied. Plan steps can involve trying to achieve sub-goals. When trying to achieve a sub-goal, the existing plan is suspended and the new plan is put on top of the intention stack. Michael Papasimeon BDI Concepts 22 October 2003 15 / 16
  16. References Reasoning About Rational Agents, Michael Wooldridge The Intentional Stance,

    Daniel Dennet BDI Agents: From Theory to Practice, Anand Rao and Michael Georgeff Modeling Rational Agents within a BDI-Architecture, Anand Rao and Michael Georgeff Michael Papasimeon BDI Concepts 22 October 2003 16 / 16