Concrete architectures (Section 1.4) Part II: Shabbir Ssyed

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Concrete architectures (Section 1.4)Part II
Shabbir Ssyed

• We will describe four classes of agents
• Logic based agents
• Reactive agents
• Belief-desire-intention agents
• Layered architectures

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Reactive architectures (Section 1.4)

• Subsumption architecture Rodney Brooks
• Task accomplishing behavior.
• Situation? Action.
• Many behaviors can fire simultaneously.
• Subsumption hierarchy Lower layer has higher
  priority than higher layers.

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Background

• Emergent behavior
• Ant colony
• Artificial life
• Intelligence without reason
• Intelligence without representation

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Simple algorithm

1. Var firedf(R)
2. Var selected A
3. Begin
4. fired(c,a)(c,a) ? R and p? c
5. for each (c,a) ? fired do
6. if (? (c,a) ? fired such
   that(c,a)lt(c,a))then
7. return a
8. End-if
9. End-for
10. Function action(pP)A
11. Return null
12. End function action

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Robot scenario

• If detect an obstacle then change direction (1.6)
• If carrying samples and at the base then drop
  samples (1.7)
• If carrying samples and not at base then travel
  upgradient (1.8)
• If detect a sample then pick sample up (1.9)
• If true then move randomly (1.10)
• (1.6) lt (1.7) lt (1.8) lt (1.9) lt (1.10)

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Modified sequence

• If carrying samples and at the base then drop
  samples (1.11)
• If carrying samples and not at the base then drop
  2 crumbs and travel up gradient (1.12)
• If sense crumbs then pick up 1 crumb and travel
  down gradient (1.13)
• (1.6) lt (1.11) lt (1.12) lt (1.9) lt (1.13) lt (1.10)

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Advantages distadvantages

• Advantages
• simplicity, economy, computational tractability,
• robustness against failure.
• Disadvantages
• How decision making can be done on non-local
  information.
• How purely reactive agents can be designed that
  learn from experience.
• Relationships between individual behaviors,
  environments, and overall behaviors are not
  understandable
• It is harder to build agents that contain
  multiple layers.

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Concrete architectures (Section 1.4)

• We will describe four classes of agents
• Logic based agents
• Reactive agents
• Belief-desire-intention agents
• Layered architectures

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Belief-Desire-Intention architecture

• Deliberation
• what goals we want to achieve.
• Means-ends reasoning/analysis
• how are we going to achieve these goals.
• If(conditions)
• Thenstatements
• Elsestatements

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Roles of Intentions

• Intentions drive means-ends reasoning
• Intentions constrain future deliberation.
• Intentions persist.
• Intentions influence beliefs upon which future
  practical reasoning is based.

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Tradeoff between degree of commitment and
reconsideration

• Rate of change of world ?
• If ? is
• low
• bold agents outperform cautious agents.
• high
• cautious agents outperform bold agents.
• Different environments require different types of
  decision strategies.

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BDI Architecture
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Functions

• Options? (Bel)? (Int)?? (Des)
• Filter? (Bel)? (Int)? (Des)?? (Int)
• Execute? (Int)?A
• ActionP?A
• Current intentions are either previously held
  intentions or newly adopted options

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Concrete architectures (Section 1.4)

• We will describe four classes of agents
• Logic based agents
• Reactive agents
• Belief-desire-intention agents
• Layered architectures

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Layered architecture

• Horizontal layering
• Vertical layering
• One pass control
• Two pass control.
• Examples
• Touring machines (Horizotal arch.)
• InteRRaP (Vertical layered two pass arch.)

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Turing MachinesInnes Ferguson
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Layers

• Reactive
• Reactive layer provides more or less immediate
  response to changes that occur in environment.
• Implemented as set of situationaction rules
  like subsumption.
• These rules map sensor I/p directly to effector
  o/p.
• Makes reference to agents current state.
• Cannot do explicit reasoning about the world.
• Planning
• Does not generate plans from scratch employs
  library of plans called skeletons.
• Modelling
• Represents various entities in the worlds.
• Predicts conflicts between agents and generates
  new goals to resolve the conflicts

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IntRRaP Joerg Mueller
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Properties of Layers

• Situation recognition maps KB and current goals
  to a new set of goals
• Goal activation selects which plans to execute,
  based on the current plans, goals, and KB of that
  layer
• Bottom up activation
• Top down execution

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Difference between TM InteRRaP

• KB is in InteRRaP not in TM.
• In TM
• each layer directly coupled with I/p and o/p so
  a control layer is necessary.
• In InteRRaPP
• layers interact with each other.

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Layered vs. unlayered architecture

• Layered architecture lacks the conceptual and
  semantic clarity of unlayered architecture (e.g.,
  logic-based)
• But remains the most popular because layering
  represents decomposition of functionality

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Agent Programming Languages (Section 1.5)

• Agent0
• Agent-oriented programming Yoav Shoham, 1990
• Concurrent METATEM
• Logic formulae Michael Fisher, 1994

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Agent0 language components

1. set of initial capabilities,
2. Set of initial beliefs,
3. Set of initial commitments (intentions)
4. Set of commitment rules

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Agent0 commitment rules

• A commitment rule has
• Message condition
• Mental condition
• Action
• Rule fires when
• Message condition matches against messages
  received by agent and
• Mental condition matches against beliefs held by
  agent
• Action can be private or communicative

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Flow control in Agent0
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Concurrent METATEM

• Each agent is programmed by giving a temporal
  logic specification.
• Agents specification is executed directly to
  generate its behaviour.
• Pi? Fi. Is a rule. Each rule is continuously
  matched against an internal recorded history, if
  matched rule fires.
• If rule fires then commitment is updated to
  future time part.
• Example Agent X asks Resource Controller(RC) for
  resource and RC gives X the resource, after
  mutual exclusion is performed.

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Conclusions

• Goal of Introduction
• What is an agent
• Why this is an important area for building
  flexible autonomous systems
• Goal of research activities
• Theory, design, construction and implementation
  of intelligent agents

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THANK YOU for your attentionLets start the
discussion!