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BehaviorNet An Action Selection Mechanism. Aregahegn Negatu And Conscious Software Research Group. Intelligent agents. Agents have Drives, agenda, primary motivation Goals, subgoals Agents live in an environment Agents continuously act in pursuit of their goals/agenda. Behavior.

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behaviornet an action selection mechanism

BehaviorNetAn Action Selection Mechanism

Aregahegn Negatu

And

Conscious Software Research Group

intelligent agents
Intelligent agents
  • Agents have
    • Drives, agenda, primary motivation
    • Goals, subgoals
  • Agents live in an environment
  • Agents continuously act in pursuit of their goals/agenda
behavior
Behavior
  • Is a form of response to a specific environmental configuration.
  • Such responses are modulated by the underlying goals/drives.
  • Agents can have more than one relevant behavior in a given situation.
action selection
Action Selection
  • Agents exhibit multiple behaviors at a time (given situation) – parallel.
    • Not time sharing.
  • Behaviors conflict : use same mechanism or shared resource.
  • Agents have competing behaviors or actions.
action selection cont
Action Selection (cont.)
  • Agents encounter multiple, competing, relevant behaviors to choose from.
  • The major intelligence of an agent is used to decide “what to do next.”
    • Franklin: Artificial minds
  • Thus, the action-selection problem.
  • MASM: Maes’ Action Selection Mechanism
    • How to do the Right thing? (Maes,1990).
masm behavior
MASM: Behavior
  • Behavior (Competence module) is like a production rule:
    • Situation: precondition
    • Action: (addition, deletion)
  • Behavior has an activation: a level of strength.
masm behaviornet
MASM: BehaviorNet
  • BehaviorNet is a digraph.
    • With Behaviors as nodes, and
    • Three types of links:
      • Successor
      • Predecessor
      • Conflicter
  • Links are determined and created by behaviors (local decision).
a behavior stream
A behavior stream

Acknowledged

Send an

Acknowledge-

ment

Drive to

acknowledge

Goal-directing

Activation

Compose an

Acknowledge-

ment

Get e-mail

address

Find a

Message

template

Behavior codelets

From sideline

Environmental activation

masm building behaviornet
MASM: Building BehaviorNet

B1

a

w

b

y

c

B3

w

r

x

s

y

B2

c

x

d

z

e

masm activation spreading
MASM: Activation Spreading
  • Global goals: built-in source of motivation
  • Environment: Situational relevance.
  • Behaviors
    • Activation by successors and predecessors.
    • Inhibition by conflicters.
  • Activation spreads in a greedy way.
masm algorithm
MASM: Algorithm
  • Loop for ever
    • Add external activation
      • from goals & environment.
    • Spread activation/inhibition among behaviors
      • Forward activation via successor links
      • Backward activation via predecessor links
      • Backward inhibition via conflicter links
    • Decay: total activation in system is constant.
    • Behavior fires if:
      • It’s executable (all it’s preconditions are satisfied).
      • It’s activation level is over a threshold (theta).
      • It’s activation is the maximum of such.
masm algorithm cont
MASM: Algorithm (cont.)
  • If one behavior fires,
    • its activation is set to zero.
    • Threshold value is reset to default.
  • If no behavior fires, reduce threshold value by x%.
    • System “thinks” for one more round and try again.
masm tuning the dynamics
MASM: Tuning the dynamics
  • Action selection emerges from the dynamics of activation spreading.
  • Tunable parameters:
    • Amount of activation injected by environment.
    • Amount If activation energy injected by goals.
    • The threshold value, theta.
masm characteristics
MASM: Characteristics
  • Thoughtful
  • Reactive and fast
  • Situation-oriented and opportunistic.
  • Goal-oriented.
  • Persistent: biased to ongoing goal/plan.
  • Goals interact and avoid conflicts.
  • Robust.
  • Some of the characteristics are not independent of each other and are tunable.
    • Example: thoughtfulness vs. reactive.
behaviornet in ida
BehaviorNet in IDA
  • Is based on MASM.
  • Introduces variables with instantiation mechanism.
  • BehaviorNet has:
    • Drives: built-in primary motivators.
      • Importance
      • Intensity
    • Streams: Action plans for specific problem.
      • Behaviors
      • Goals
behaviornet in ida cont
BehaviorNet in IDA (cont.)
  • Behavior:
    • Precondition, addition, deletion lists
    • Activation
    • Variable slots
    • Underlying codelets
  • Goals:
    • same as behaviors but may not have codelets to underlie them
    • Satisfaction-condition (continuous, one-time)
  • Streams are linked as in MASM
  • Activation spreads as in MASM
stream examples
Stream examples

G

G1

G2

G

B1

B2

B1

B2

B1

B3

B4

B3

B4

B6

B5

stream instantiation
Stream instantiation
  • Template stream:
    • no variables bound
  • Instantiated stream:
    • Some or all variables are bound.
    • Underlying codelets are instantiated
    • Is part of the dynamics in the active behavior net
example of instantiated streams
Example of instantiated streams

Stream 1

Drive 1

Drive 2

Two streams in the same context

Stream 2

slide20

IDA’s Architecture

Metacognition

Database

Perception

Linear

Functional

Deliberation

Negotiation

Write

Orders

Behavior Net

Conceptual

& Behavioral

Learning

“Consciousness”

Perception

Associative

Memory

Episodic

Memory

Emotions

goal context system
Goal context System
  • Behavior: a goal context.
  • Stream: a goal context hierarchy.
  • Executing behavior: Dominant goal context.
    • Its stream: dominant goal context hierarchy.
  • BehaviorNet: a hierarchical goal context system.
goal context hierarchy
Goal context hierarchy

D

G

Stream 1

B1

B2

B5

B3

B4

Stream 3

G

Stream 2

G

B1

B1

B2

B2

B3

working with consciousness
Working with “Consciousness”

Behavior Net template

B1

B1

B1

G

B1

Sky box

Stands

Working

Memory

Black board

Broadcast

Sideline

Playing

Field

c u c cycle
C-U-C cycle

Behavior Net

System

Behavior

Codelets

Environment

Internal States

Work Space

Behavior

Priming

Codelets

Consciousness

System

Attention

Codelets

remarks
Remarks
  • Goal hierarchy instantiation
    • With preattentive or subliminal perception
    • With conscious event
  • Motivation
    • Built-in - drives
    • Situational
  • Significance of action has a level of informativeness
  • Unconscious avoidance of goal conflicts
  • Action types
    • unconscious,
    • consciously mediated,
    • voluntary
  • Drives, as the deepest component in the goal hierarchy, are part of self-concept.