Autonomy Ancient G reek autonomy one who gives oneself their own law autonomy I ndependence or freedom as of the will or ones actions the autonomy of the individual ID: 527054
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Slide1
AutonomySlide2
Autonomy
Ancient
G
reek:
autonomy = „one who gives oneself their own law“
au·ton·o·my:
I
ndependence
or freedom, as of the
will
or
one's actions:
the autonomy
of the individual
.
The
condition of being
autonomous
; self-government, or
the right
of
self-government
; independenceSlide3
Types of autonomy
Autonomy of environment
Social autonomy
Operational autonomy / autonomy of control
Goal autonomySlide4
Why is autonomy desirable?
≈
Same
reasons as for AGI
Reduces or eliminates human control and intervention
Less operational cost
Highly autonomous systems more reusable
Building
learning, flexible, self-adaptive systems that can operate without complete
pre-specification of tasks
Central feature of human intelligenceSlide5
Autonomy
Task fully specified?
Task only focused towards external environment?
Task involves learning?
Autonomy is closely related to intelligence
Learning to perform partially specified or unspecified tasks requires intelligenceSlide6
Autonomy
Most current “autonomous” systems are built to operate in conditions more or less fully described a priori, which is insufficient for achieving highly autonomous systems that adapt efficiently to unforeseen situations.
Fully specified operation
Operating contexts must comply with specification
Systems not meant to change
E.
Nivel
& K. R. Thórisson: Self-Programming: Operationalizing Autonomy
Behaviorally autonomous systems
Change as desirable and controllable phenomenon
Structural
autonomy
Automatic adaptation
Adaptation is used here in a strong sense as the ability of a machine not only to maintain but also to improve its utility function and so, in partially specified conditions with limited resources (including time) and knowledge.
IKON FLUX
In our view, autonomous systems automatically perform
tasks
in some
environment
,
with
unforeseen
variations
occurring in both, through some type of automatic learning and
adaptation that
improves the system's performance with respect to its high-level goalsSlide7
Autonomy
Weak autonomy
Systems that require some degree of human control to perform target tasks
Medium autonomy
Systems that perform fully specified target tasks without human intervention
Strong autonomy
Systems generating own goals that learn to
adapt to unforeseen varations
and perform new tasks without human
control Slide8
Autonomy
Autonomy = (system S, task T, context C)
From Sanz 2000
System
S
is autonomous if it can fulfill task
T
in context
C
A
refrigerator (
SYSTEM =
”refrigerator of Alex”) is autonomous because it
can fulfill
its task (TASK = ”keep the
interior temperature at 5° C
”) in a specific context (CONTEXT = ”
Interior of
a house in Philadelphia”)Slide9
Automatic vs AutonomousSlide10
AFLUS autonomy framework
http://www.nist.gov/el/isd/ks/upload/ALFUS-BG.pdfSlide11
Autonomy Comparsion Framework for AGI systems (Thórisson & Helgason)Slide12
Autonomy dimensions
Learning
Enables system to handle novel situations and task varations
Meta-learning
System improves own operation, increasing its capacity to solve complex tasks
Realtime
Failure to keep up with the environment reduces autonomy and overall operation
May introduce artificial pauses etc.
Resource management
Autonomous operation involving multiple simultaneous cognitive processes, complex environments, limited resources and time constraints requires sophisticated management of resourcesSlide13
Evaluation of selected AGI systemsSlide14
Qualitative comparison