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Design of Multi-Agent Systems

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Title: Design of Multi-Agent Systems


1
Design of Multi-Agent Systems
  • Teacher
  • Bart Verheij
  • Student assistants
  • Albert Hankel
  • Elske van der Vaart
  • Web site
  • http//www.ai.rug.nl/verheij/teaching/dmas/
  • (Nestor contains a link)

2
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

3
Deductive Reasoning Agents
  • Decide what to do on the basis of a theory
    stating the best action to perform in any given
    situation
  • ?, ? Do(a) with a ? Ac
  • where
  • ? is such a theory (typically a set of rules)
  • ? is a logical database that describes the
    current state of the world
  • Ac is the set of actions the agent can perform

4
Deductive Reasoning Agents
  • But
  • Theorem proving is in general neither fast nor
    efficient
  • Calculative rationality (rationality with respect
    to the moment calculation started) requires a
    static environment
  • Encoding of perception environment into logical
    symbols isnt straightforward
  • So
  • Use a weaker logic
  • Use a symbolic, not logic-based representation

5
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

6
Planning STRIPS
  • Only atoms and their negation
  • Only represent changes
  • Blocks world (blocks a robot arm)
  • Stack(x,y)
  • Pre Clear(y), Holding(x)
  • Del Clear(y), Holding(x)
  • Add ArmEmpty(y), On(x,y)

7
Problems with planning
  • Frame problem
  • Describe what does not change by an action
  • Qualification problem
  • Describe all preconditions of an action
  • Ramification problem
  • Describe all consequences of an action
  • Prediction problem
  • Describe the duration that something remains true

8
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

9
Agent-oriented programming
  • Agent0 (Shoham)
  • Key idea directly programming agents in terms of
    intentional notions like belief, commitment, and
    intention
  • In other words, the intentional stance is used as
    an abstraction tool for programming!

10
Agent-oriented programming
  • Shoham suggested that a complete AOP system will
    have 3 components
  • a logic for specifying agents and describing
    their mental states
  • an interpreted programming language for
    programming agents (example Agent0)
  • an agentification process, for converting
    neutral applications (e.g., databases) into
    agents

11
Agent-oriented programming
  • Agents in Agent0 have four components
  • a set of capabilities (things the agent can do)
  • a set of initial beliefs
  • a set of initial commitments (things the agent
    will do)
  • a set of commitment rules

12
Agent-oriented programming
  • Each commitment rule contains
  • a message condition
  • a mental condition
  • an action
  • On each agent cycle
  • The message condition is matched against the
    messages the agent has received
  • The mental condition is matched against the
    beliefs of the agent
  • If the rule fires, then the agent becomes
    committed to the action (the action gets added to
    the agents commitment set)

13
A commitment rule in Agent0
  • COMMIT(
  • ( agent, REQUEST, DO(time, action)
  • ), msg condition
  • ( B,
  • now, Friend agent AND
  • CAN(self, action) AND
  • NOT time, CMT(self, anyaction)
  • ), mental condition
  • self,
  • DO(time, action)

14
A commitment rule in Agent0
  • Meaning
  • If I receive a message from agent which requests
    me to do action at time, and I believe that
  • agent is currently a friend
  • I can do the action
  • At time, I am not committed to doing any other
    action
  • then I commit to doing action at time

15
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

16
Concurrent METATEM
  • Concurrent METATEM is a multi-agent language in
    which each agent is programmed by giving it a
    temporal logic specification of the behavior it
    should exhibit
  • These specifications are executed directly in
    order to generate the behavior of the agent
  • Temporal logic is classical logic augmented by
    modal operators for describing how the truth of
    propositions changes over time

17
Concurrent METATEM
  • important(agents)it is now, and will always be
    true that agents are important
  • ?important(ConcurrentMetateM)sometime in the
    future, ConcurrentMetateM will be important
  • ?important(Prolog)sometime in the past it was
    true that Prolog was important
  • (?friends(us)) U apologize(you)we are not
    friends until you apologize
  • ?apologize(you)tomorrow (in the next state), you
    apologize

18
Concurrent METATEM
  • MetateM is a framework for directly executing
    temporal logic specifications
  • The root of the MetateM concept is Gabbays
    separation theoremAny arbitrary temporal logic
    formula can be rewritten in a logically
    equivalent past ? future form.
  • This past ? future form can be used as execution
    rules

19
Concurrent METATEM
  • A MetateM program is a set of such rules
  • Execution proceeds by a process of continually
    matching rules against a history, and firing
    those rules whose antecedents are satisfied
  • The instantiated future-time consequents become
    commitments which must subsequently be satisfied

20
Concurrent METATEM
  • Execution is thus a process of iteratively
    generating a model for the formula made up of the
    program rules
  • The future-time parts of instantiated rules
    represent constraints on this model
  • All asks at some time in the past are followed
    by a give at some time in the future

21
Concurrent METATEM
  • Execution is thus a process of iteratively
    generating a model for the formula made up of the
    program rules
  • The future-time parts of instantiated rules
    represent constraints on this model
  • ConcurrentMetateM provides an operational
    framework through which societies of MetateM
    processes can operate and communicate

22
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23
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

24
Practical reasoning
  • Practical reasoning is reasoning directed towards
    actions the process of figuring out what to do
  • Practical reasoning is a matter of weighing
    conflicting considerations for and against
    competing options, where the relevant
    considerations are provided by what the agent
    desires/values/cares about and what the agent
    believes. (Bratman)
  • Practical reasoning is distinguished from
    theoretical reasoning theoretical reasoning is
    directed towards beliefs

25
Practical reasoning
  • Human practical reasoning consists of two
    activities
  • deliberationdeciding what state of affairs we
    want to achieve
  • means-ends reasoningdeciding how to achieve
    these states of affairs
  • The outputs of deliberation are intentions

26
Intentions in practical reasoning
  1. Intentions pose problems for agents, who need to
    determine ways of achieving them.If I have an
    intention to ?, you would expect me to devote
    resources to deciding how to bring about ?.
  2. Intentions provide a filter for adopting other
    intentions, which must not conflict.If I have an
    intention to ?, you would not expect me to adopt
    an intention ? such that ? and ? are mutually
    exclusive.
  3. Agents track the success of their intentions, and
    are inclined to try again if their attempts
    fail.If an agents first attempt to achieve ?
    fails, then all other things being equal, it will
    try an alternative plan to achieve ?.

27
Intentions in practical reasoning
  1. Agents believe their intentions are
    possible.That is, they believe there is at least
    some way that the intentions could be brought
    about. Otherwise intention-belief inconsistency
  2. Agents do not believe they will not bring about
    their intentions.It would not be rational of me
    to adopt an intention to ? if I believed ? was
    not possible. Otherwise intention-belief
    incompleteness
  3. Under certain circumstances, agents believe they
    will bring about their intentions.It would not
    normally be rational of me to believe that I
    would bring my intentions about intentions can
    fail. Moreover, it does not make sense that if I
    believe ? is inevitable that I would adopt it as
    an intention.

28
Intentions in practical reasoning
  1. Agents need not intend all the expected side
    effects of their intentions.If I believe ??? and
    I intend that ?, I do not necessarily intend ?
    also. (Intentions are not closed under
    implication.)This last problem is known as the
    side effect or package deal problem.

29
Intentions in practical reasoning
  • Intentions are stronger than mere desires
  • My desire to play basketball this afternoon is
    merely a potential influencer of my conduct this
    afternoon. It must vie with my other relevant
    desires . . . before it is settled what I will
    do. In contrast, once I intend to play basketball
    this afternoon, the matter is settled I normally
    need not continue to weigh the pros and cons.
    When the afternoon arrives, I will normally just
    proceed to execute my intentions. (Bratman, 1990)

30
Practical reasoning (abstract)
  • Current beliefs and perception determine next
    beliefs
  • Current beliefs and intentions determine next
    desires
  • Current beliefs, desires and intentions determine
    next intentions
  • Current beliefs, desires and available actions
    determine a plan

31
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

32
Implementing practical reasoning agents
B B_initial I I_initial loop p
see B brf(B,p) //Update world
model I deliberate(B) ?
plan(B,I) //Use means-end reasoning execute(?)
end
33
Interaction between deliberation and planning
  • Both deliberation and planning take time, perhaps
    too much time.
  • Even if deliberation is optimal (maximizes
    expected utility), the resulting intention may no
    longer be optimal when deliberation has finished.
  • (Calculative rationality)

34
Deliberation
  • How does an agent deliberate?
  • Option generationin which the agent generates a
    set of possible alternatives
  • Filteringin which the agent chooses between
    competing alternatives, and commits to achieving
    them.

35
Implementing practical reasoning agents
B B_initial I I_initial loop p
see B brf(B,p) D option(B,I) //
Deliberate (1) I filter(B,D,I) //
Deliberate (2) ? plan(B,I) execute(?) e
nd
36
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

37
Commitment Strategies
  • The following commitment strategies are commonly
    discussed in the literature of rational agents
  • Blind commitmentA blindly committed agent will
    continue to maintain an intention until it
    believes the intention has actually been
    achieved. Blind commitment is also sometimes
    referred to as fanatical commitment.
  • Single-minded commitmentA single-minded agent
    will continue to maintain an intention until it
    believes that either the intention has been
    achieved, or else that it is no longer possible
    to achieve the intention.
  • Open-minded commitmentAn open-minded agent will
    maintain an intention as long as it is still
    believed possible.

38
Commitment Strategies
  • An agent has commitment both to ends (i.e., the
    wishes to bring about), and means (i.e., the
    mechanism via which the agent wishes to achieve
    the state of affairs)
  • Currently, our agent control loop is
    overcommitted, both to means and ends
  • Modification replan if ever a plan goes wrong

39
B B_initial I I_initial loop p
see B brf(B,p) D option(B,I) I
filter(B,D,I) ? plan(B,I) while not
empty(?) do a head(?) execute(a)
//Start plan execution ? tail(?) p
see B brf(B,p) //Update world
plan if not sound(?,B,I) then ?
plan(B,I) //Replan if necessary end end en
d
40
Commitment Strategies
  • Still overcommitted to intentions Never stops to
    consider whether or not its intentions are
    appropriate
  • Modification stop to determine whether
    intentions have succeeded or whether they are
    impossible(Single-minded commitment)

41
B B_initial I I_initial loop p
see B brf(B,p) D option(B,I) I
filter(B,D,I) ? plan(B,I) while not
(empty(?) or succeeded(B,I) or impossible (B,I)
do a head(?) //Check whether intentions
succeeded execute(a) //and are still
possible ? tail(?) p see B
brf(B,p) if not sound(?,B,I) then ?
plan(B,I) end end end
42
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration

43
Intention Reconsideration
  • Our agent gets to reconsider its intentions once
    every time around the outer control loop, i.e.,
    when
  • it has completely executed a plan to achieve its
    current intentions or
  • it believes it has achieved its current
    intentions or
  • it believes its current intentions are no longer
    possible.
  • This is limited in the way that it permits an
    agent to reconsider its intentions
  • Modification Reconsider intentions after
    executing every action

44
  • B B_initial
  • I I_initial
  • loop
  • p see
  • B brf(B,p)
  • D option(B,I)
  • I filter(B,D,I)
  • ? plan(B,I)
  • while not (empty(?) or succeeded(B,I) or
    impossible (B,I) do
  • a head(?)
  • execute(a)
  • ? tail(?)
  • p see
  • B brf(B,p)
  • D option(B,I) //Reconsider (1)
  • I filter(B,D,I) //Reconsider (2)
  • if not sound(?,B,I) then
  • ? plan(B,I)
  • end

45
Intention Reconsideration
  • But intention reconsideration is costly!A
    dilemma
  • an agent that does not stop to reconsider its
    intentions sufficiently often will continue
    attempting to achieve its intentions even after
    it is clear that they cannot be achieved, or that
    there is no longer any reason for achieving them
  • an agent that constantly reconsiders its
    attentions may spend insufficient time actually
    working to achieve them, and hence runs the risk
    of never actually achieving them
  • Solution incorporate an explicit meta-level
    control component, that decides whether or not to
    reconsider

46
  • B B_initial
  • I I_initial
  • loop
  • p see
  • B brf(B,p)
  • D option(B,I)
  • I filter(B,D,I)
  • ? plan(B,I)
  • while not (empty(?) or succeeded(B,I) or
    impossible (B,I) do
  • a head(?)
  • execute(a)
  • ? tail(?)
  • p see
  • B brf(B,p)
  • if reconsider(B,I) then //Decide whether to
    reconsider or not
  • D option(B,I)
  • I filter(B,D,I)
  • end
  • if not sound(?,B,I) then

47
Overview
  • Deductive reasoning agents
  • Planning
  • Agent-oriented programming
  • Concurrent MetateM
  • Practical reasoning agents
  • Practical reasoning intentions
  • Implementation deliberation
  • Implementation commitment strategies
  • Implementation intention reconsideration
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