koen hindriks, birna van riemsdijkmulti-agent systemen agent programming in g oal multi-agent...

Koen Hindriks, Birna van Riemsdijk Multi-agent systemen

Agent Programming in GOALMulti-agent Systems & Communication

Koen HindriksDelft University of Technology, The Netherlands

Koen Hindriks, Birna van Riemsdijk Multi-agent systemenKoen Hindriks, Birna van Riemsdijk Multi-agent systemen

GOAL So Far

• mental states (beliefs, goals)

• mental state conditions & macros

• action specifications, built-in actions

• action rules

• environment & perception

• modules


Outline (today)

• Intro Multi-Agent Systems (MAS)

• Specifying a MAS in GOAL

• Communication in GOAL

• Coordination in MAS


Multi-Agent Systems (MAS)


Multi-Agent System

Environment

A1Agents A2

A3A4

Intersecting spheres of influence of multiple agents acting in an environment

Intersecting spheres:•Action perspective: may interfere, change same parts of environment•Perception perspective: agents may have different views on environment


Multi-Agent System

Environment

A1Agents A2

A3

A4

Various approaches to coordinate activity of multiple agents

Various coordination techniques have been proposed, main ideas:•Communication protocols impose structure on agent communication•Add organization structure on top of multi-agent system

Note: Without explicit agent communication still implicit communication possible via environment if perception spheres overlap


Multi-Agent System

Environment

A1Agents A2

A3

A4

Not all agents need to be ‘connected’ to the environment


Specifying a MAS


MAS Specification

In GOAL, a .mas file is a recipe for launching a

multi-agent system, specifying:

• which environment will be launched,

• how many agents will be launched,

• the agent names for agent processes

• which agents are connected to environment

• which .goal file is used to create an agent.


MAS Specification

A .mas file is a recipe for launching a MAS:

• which environment will be launched

• environment started by jar file,

• some of which may be initialized using the init command (check out environment doc).

environment{ "blocksworld.jar".

init[configuration="bwconfigEx1.txt"].}


MAS Specification


• which agent files will be used

• agent file defines a possible agent type.

agentfiles { "coffeemaker.goal".

"coffeegrinder.goal".}


MAS Specification


• which agent processes will be created

• a launch policy specifies when, which and how many agent processes will be created.

• launch maker:coffeemaker. launches one agent process called maker using the agent file referenced by coffeemaker (coffeemaker.goal).

• does not connect agent to an environment.

launchpolicy { launch maker:coffeemaker. launch grinder:coffeegrinder.

}


MAS Specification


• which agent processes will be created

• a conditional launch rule is triggered by the environment:

whenever a controllable entity becomes available in the environment, an event is generated.

• the agent created by the launch part of the rule is connected to that entity.

launchpolicy { when entity@env do launch elevator:file1. }


MAS Specification


• additional checks in launch rule

• this launch rule can only be applied if there is an available entity of type car, and the rule can be applied at most 3 times.

Remark: launch rules are applied in linear order.

launchpolicy { when [type=car,max=3]@env do launch elevator:file1. }


MAS Specification: Example


• environment section may be empty, in that case mas is run without an environment.

• agentfiles and launchpolicy must be non-empty.

agentfiles { "coffeemaker.goal".

"coffeegrinder.goal".}

launchpolicy { launch maker:coffeemaker. launch grinder:coffeegrinder.

}


Agent Identity and Other AgentsHow does an agent know it is not alone?• The names of all agents generated by GOAL are

inserted in the belief base of all other agents.• For example, agent(tarzan) is inserted in the

belief base of agent jane when tarzan is created.

How is an agent able to differentiate itself from other agents? I.e. how does agent jane know she is not tarzan?

• Upon creation, the fact me(<name>) where name is the agent’s name is inserted in the belief base of that agent.


Communication in GOAL


Communication: Primitives

• Communication primitives:– send(<recipients>, <content>)– sendonce(<recipients>, <content>)

• Example: Tarzan sends Jane a message:– send(jane, meeting(date(1,2,2010), time(12,0), duration(1,0), [jane, tarzan]))


GOAL Agent Architecture• The basis of communication in GOAL is a simple

mailbox semantics.

Agent

EnvironmentReal or simulatedworld of events

actionpercept

Beliefs

Goals

ActionRulesProcess

percepts

message Processmessage


Communication: SemanticsAction: send(<recipients>, <content>)• ground send action can always be performed, i.e.

precondition is true,

• assume agent sender sends message to recipients

• then GOAL puts

sent(<recipients>, <content>)

in the mailbox of sender,• agents that receive message put

received(sender, <content>)

in their mailbox. NB: keep in mind it may take some time before agent b receives the message.


Communication: SemanticsAction: sendonce(<recipients>, <content>)

• same as send(<recipients>, <content>), but

• sendonce action can only be performed if the mailbox of the sending agent does not contain:

sent(<recipients>, <content>)

i.e. precondition is:

not(sent(<recipients>, <content>)


Using Messages in MailboxThe facts in the mailbox can be used like any other facts in the

belief base of an agent.

That is,

• sent(<recipient>, <content>) and• received(name, <content>)

can be used in:– in conditions in action rules– clauses in the knowledge or beliefs section


Using Messages in Mailbox

• After receiving a message from tarzan, agent jane will have:received(tarzan, meeting(date(1,2,2010), time(12,0), duration(1,0), [jane,tarzan]))

in her mailbox.

• Consequently, jane will believe:bel(received(tarzan, meeting(date(1,2,2010), …, …, [jane,tarzan])))


Processing Message Pattern• Inserting received information into belief base and

removing received message:

• Removing received message cleans up the mailbox and makes sure that the action rule is not applied repeatedly (even after the received info is outdated).

• Using received messages in mental state conditions other than for processing the message, and using them in knowledge base, gives less readable code.

if bel(received(A,Proposition)) then insert(Proposition) + delete(received(A,Proposition))


Message Types• GOAL supports three message types, called

moods:

– declarative, typically used to inform

Example: The time is 2 o'clock

operator: ‘:’ : send(jane, :time(14,0))– imperative, typically used to indicate a goal

Example: I want the door to be closed!

operator: ‘!’ : send(jane, !door(closed))– interrogative, typically used to ask a question

Example: How much milk is left?

operator: ‘? : send(jane, ?amountMilk(_))


Message TypesMood operators are translated to Prolog predicates in

mailbox:

– declarative: no predicatereceived(tarzan, time(14,0))

– imperative: impreceived(tarzan, imp(door(closed)))

– interrogative: intreceived(tarzan, int(amountMilk(_)))

See programming guide, section 6.5.


Agent SelectorsFirst argument of a send action is called an agent selector, which can be:•An agent name: send(jane, …)•A variable (to be instantiated): send(Person, …)•A list of selectors: send([jane,tarzan,Person], …)•A quantor:

– send(self, …) : message sent to agent itself– send(all, …) : message sent to all agents (incl. itself)– send(allother, …) : message sent to all other agents


Sending messages to oneself

• Messages sent to oneself change the agent’s own mental state! Sending messages to oneself has special meaning.

• Changes are different for different moods:– send(self, :fact) inserts fact in belief base– send(self, !fact) adopts fact as goal and

deletes fact from belief base.– send(self, ?fact) deletes fact from belief base

N.B.: Do not use messages to self as an alternative way of updating the agent’s beliefs and goals!

N.B.: Do not use messages to self as an alternative way of updating the agent’s beliefs and goals!


Selecting agents to send to

• Suppose agent wants to send to all other agents that are producers of milk that it wants to have milk.

Q: Write an action rule which achieves this:– Use predicates have/1 and producerOf/2.

A: if a-goal(have(milk)), bel(agent(X), producerOf(X, milk))

then send(X, !have(milk))

koen hindriks, birna van riemsdijkmulti-agent systemen agent programming in g oal multi-agent...

Documents

agent processes

agent names

agent files

multiagent system note

explicit agent communication

possible agent type

environment slide

environment section