Introduction to Belief Desire Intention Agentsgoanna.cs.rmit.edu.au › linpa › Presentations › BDIintro.pdf · dynamic static Beliefs onment Pending Events Intention Stacks BDI

Introduction to Belief Desire IntentionAgents

Lin Padgham

RMIT University, Melbourne, Australia

BDI Agent Systems Useful in Many Applications

Unmanned (Aerial)Vehicles

Trading Agents

Logistics

E-Health

Air Traffic Control

BDI (Belief Desire Intention) agents have been used in many successfulapplications in complex environments.

RMIT Agents Group Introduction to BDI 1 / 7

Belief Desire Intention Model of Agency

• BDI is a framework for describing the behaviour of rational agents.

• Based on work in the philosophy of mind:

Dennett

Intentional systems:“[..] whose behaviorcan be predicted by themethod of attributingbelief, desires andrational acumen.”

Bratman

Practical reasoning:“[..] a matter ofweighing conflictingconsiderations [..]provided by what theagent desires [and]believes.”

• Human practical reasoning consists of two activities:• Deliberation: deciding what to do i.e., form intentions.• Means-ends Reasoning: deciding how to do it i.e., form plans.


Belief-Desire-Intention (BDI) Agent Architecture

SENSORS

ACTUATORS

dynamic static

Beliefs

Env

iron

men

tPending Events

Intention Stacks

BDI engine

actions

events

Plan

library

A plan is a programmed recipe for achieving a goal in some situation.A BDI execution engine selects from a plan library, based on the situation.


Goal-Plan Tree: Decomposition and Selection

P1

G2

P2

G3

P5 P6

P3 P4

G4

P7 P8

G5

P9 P10 P11

G6

P12 P13 P14

• A plan typically has a numberof (sub)goal steps.

• Each sub-goal generates an(internal) event which hassome relevant plans.

• So the plan library can beseen as a set of goal-plantrees.

• At each goal node a plan mustbe selected (OR).

• At each plan node the goalsmust be accomplished (AND).


BDI Agent Oriented Programming

• BDI Agent-Oriented Programming provides abstraction at the level ofmental attitudes to explain the operation of a system. Beliefs, Desires,Intentions.

• The modularity of plans makes it easy to develop complexityincrementally.

• The goal oriented approach makes it suitable for use in dynamicenvironments.

• Many efficient and powerful development environments available. JACK,Jadex, Jason, PRS, 2APL, ...

• BDI agent programs are fast to develop. A 2006 study showed:• Gain compared to Java programming 500%.


Example Plan Structure

goal

plan

Action

M:msg

RespondBushfire

EvacHouse

ObtainTransport

GetCar

Walk(Car)Drive(Door)

ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble

M:toDoor M:phoneInfo

MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc

GetFromRadio LocalShelter LeaveTown

Drive(L)

WaitPickUp

Stay&Defend



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

1 2 3

A plan is a sequence of steps



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

1 2 3 goal

action message

A step can be a goal, an action, a message to another agent, or somecomputation.



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

A goal may have different plans, for achieving it in different situations.



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

Context:have car &car at home




RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg


Context: Xis neighbour& X has car




RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg



This can givemultiple planinstances




RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg



This can givemultiple planinstances

OR OR

For a goal to succeed one of the plans must succeed. If one fails try another.



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

AND

For a plan to succeed, all steps must succeed.



RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

goal

plan

Action

M:msg

AND

If things fail, recovery happens as locally as possible



goal

plan

Action

M:msg

car home

RespondBushfire

EvacHouse

ObtainTransport

GetCar


ArrangeLift

M:ReqLift

NoTransport

AssembleMembers

HouseAssemble

M:toDoor

DistAssemble


MoveSafeLoc

WalkToLoc

Walk(L)

DriveToLoc

DetermineLoc


Drive(L)

WaitPickUp

Stay&Defend

Plan selection responsive to changing environment.


Advantages

• Intuitive representation

• Late selection: situation aware...

• Plan failure - retry new plan. Committed to choices, like humans.

• Agent is responsive to environmental changes.

• Huge number of options possible - over 2 million for modest tree.(Subgoal steps 4, Choices 2, Depth 3)


Documents

Introduction to Belief Desire Intention Agentsgoanna.cs.rmit.edu.au › linpa › Presentations › BDIintro.pdf · dynamic static Beliefs onment Pending Events Intention Stacks BDI