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Matthias Hölzl lecture slides for the Awareness Virtual Lecture Series 2011 on Adaptation and Awareness in Robot Ensembles.
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Adaptation and Awareness in Robot Ensembles
Matthias HölzlLudwig-Maximilians-Universität München
AWARENESS Summer SchoolDecember 5, 2011
www.ascens-ist.eu
Ensembles
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Ensembles
Massive numbers of nodesExtremely heterogeneousComplex interactions between nodesComplex interactions with humans or other systemsOperating in open and non-deterministic environmentsDynamic adaptation to new
requirementstechnologies andenvironmental conditions
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Swarm Robotics
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Swarm Robotics
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Swarm Robotics
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Ensembles
What is a good model for ensembles?What is adaptivity?What is awareness?What is self-awareness?
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A System Model for Ensembles
Based on Mesarović’s model of general systemsV = (Vi)i∈I : family of setsEnsemble = System = Component = Relation: S ∈ R
((Vi)i∈I
)Modal ensemble:
Set T , binary relation R on TEach Vi is a function space: Vi = F[T → Ai ]
Time ensemble:Modal ensemble where R is a preorder
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Input/Output Configurations
The Vi are divided into input/output configurationsInputs XOutputs YInternal state / awareness sections Z
X = (X1, …, Xk)
Z = (Z1, …, Zm)
Y = (Y1, …, Yl)
(V1, …, Vn) ≅ (X, Y, Z)
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Input/Output Configurations
The Vi are divided into input/output configurationsInputs XOutputs YInternal state / awareness sections Z
X Y
Z
X Y
Z
X Y
Z
X Y
Z
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Combination Operators
A combination operatorcombines components/systems into a new systemmay introduce new inputs/outputs/statesmay introduce complex behavior
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Example: Partial Cascade
S1
S2
X1nc
X2nc
Y1nc
Y2nc
Y1out = X2
in
S1 ∈ R(Xnc1 , (Y nc
1 × Y out1 ))
S2 ∈ R((Xnc2 × X in
2 ),Y nc2 )
Y out1 = X in
2
((x1, x2), (y1, y2)) ∈ S1 . S2 ⇐⇒∃z ∈ Y out
1 : (x1, (y1, z)) ∈ S1 ∧ ((x2, z), y2) ∈ S2
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Goal Satisfaction (Overview)
Model M (Logic)
System Model S(Relational)
Logic
S ⊨ 𝜸
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Goal Satisfaction
Logic LFormulae FM, α |= γ
FS ⊆ F characterizes the relevant properties of S in L
T :M→ FS × Aux → BoolTM : FS × Aux → BoolM characterizes S (using TM):
charTM(M,S) : ⇐⇒ ∀P ∈ FS : ∀α ∈ Aux : M,α |= P ⇐⇒ TM(P,α)
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Goal Satisfaction
S satisfies goal γ, written S |=T γ:
∀M ∈M : charTM(M,S) =⇒ M |= γ
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Heterostatic Ensembles
Maximizing performance instead of simple goal satisfactionA Heterostatic Ensemble consists of
a system S in input/output configuration (X ,Y ,Z)a partially ordered set Ga fitness function φ : X × Y × Z → G
Various notions of ordering possibleweak heterostatic order (relational ordering of domain theory)Egli-Milner ordering. . .
Problem: Can only take “worst case” or “best case” behavior into accountProbabilistic extension (e.g., by stochastic relations)
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Adaptation
Environment η, network or sensors/actuators ν and System SCombination operator ⊗; we write η,ν,S instead of ⊗(η,ν,S)Goal satisfaction in an environment:
η,ν,S 6|= ⊥ Consistencyη,ν,S |= γ Goal Satisfaction
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Adaptation
We usually speak of adaptation when a system works in multiple situationsAdaptation can be
to a new environment: η ′, ν, S |= γto a new network: η,ν ′,S |= γto a new goal: η,ν,S |= γ ′
to a change in the System(?): η,ν,S ′ |= γor any combination thereof
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Adaptation: Example
Two workstations Two workstations, low bandwidth
Mobile phone and workstation Workstation and cluster
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Adaptation: Example
Two mobile phones Two mobile phones and workstation
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Adaptation Domains
Adaptation domain A ⊆ E ×N × G:S can adapt to A, written S A:
S A ⇐⇒ ∀(η,ν,γ) ∈ A : η,ν,S |= γ
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Adaptation Spaces
Adaptation space A: a set of adaptation domains, A ⊆P(E × N × G)Partially ordered by inclusionFor any adaptation space we define a preorder of adaptivity for systems:
S v S ′ ⇐⇒ ∀A ∈ A : S A =⇒ S ′ A
(S ′ is at least as adaptive as S with respect to A)Extension to probabilistic case needed
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Awareness
Awareness is the state or ability to perceive, to feel, or to be conscious of events,objects or sensory patterns. (Wikipedia)Aware: 1. Having knowledge or cognizance (Free Online Dictionary)
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Awareness
Necessary conditions for awareness seem to be:An internal model of the object/state/processChanges in the real world are reflected in the internal model
Awareness is “knowledge in time”Awareness is dual to causal connection
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Awareness
Photo by kimberlykv, used under CC BY 2.0 license, http://www.flickr.com/photos/kimberlykv/6336662270/
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Awareness
Photos by kimberlykv and djburkey, used under CC BY 2.0 (NC) licensehttp://www.flickr.com/photos/kimberlykv/6336662270/ and .../djburkey/193590859/
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Awareness
Photos by kimberlykv and brostad, used under CC BY 2.0 licensehttp://www.flickr.com/photos/kimberlykv/6336662270/ and .../brostad/4662951088/
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Self-Awareness
Let S ' (X ,Y ,Z)Z can contain various awareness sections
awareness of environmentawareness of networkawareness of goals
If Z contains a section ZS that is aware of S we say S has a degree of self awareness
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Literature
Matthias Hölzl and Martin Wirsing.Towards a system model for ensembles.In Gul Agha, Olivier Danvy, and José Meseguer, editors, Festschrift in Honor of CarolynTalcott, LNCS. Springer, 2011.
M. D. Mesarović and Y. Takahara.General Systems Theory: Mathematical Foundations, volume 113 of Mathematics inScience and Engineering.Academic Press, New York, San Francisco, London, 1975.
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Conclusions and Future Work
Denotational system model for ensemblesNotions of adaptation and (self-)awareness
Operational modelsModel of emergenceRelationship to knowledgeAdaptation patterns and white-box adaptation
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