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.

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
   

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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
   

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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
   

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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
   

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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
   

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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
   

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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
   

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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
   

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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
   

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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
    

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11. A BDI Agent Architecture
    Michael Papasimeon BDI Concepts 22 October 2003 11 / 16
    

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12. Example dMARS Plan
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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
    

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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
    

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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
    

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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
    

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