establishing a roadmap and metrics for conscious machines development

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Raúl Arrabales, Agapito Ledezma and Araceli Sanchis Computer Science Department Carlos III University of Madrid http:// Conscious - Robots.com / Raul IEEE International Conference on Cognitive Informatics 2009 PolyU, Hong Kong, 15th June 2009 Establishing a Roadmap and Metrics for Conscious Machines Development

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From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.

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Page 1: Establishing a Roadmap and Metrics for Conscious Machines Development

Raúl Arrabales, Agapito Ledezma and Araceli Sanchis

Computer Science DepartmentCarlos III University of Madrid

http://Conscious-Robots.com/Raul

IEEE International Conference on Cognitive Informatics 2009

PolyU, Hong Kong, 15th June 2009

Establishing a Roadmap and Metrics for Conscious

Machines Development

Page 2: Establishing a Roadmap and Metrics for Conscious Machines Development

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Contents

Introduction Objectives ConsScale Applying the scale Example Conclusions

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Page 3: Establishing a Roadmap and Metrics for Conscious Machines Development

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Introduction (I) There are many approaches to

consciousness. Intuitively it involves:

Perception. Emotions. Attention. Self-recognition. Theory of Mind (ToM). …

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Introduction (II) Existing cognitive architectures cover

some of these aspects: BDI Agents. ACT-R. SOAR. ICARUS. Haikonen’s Cognitive Architecture. LIDA. CRONOS.

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Introduction (III) From a functional point of view a

human-like mind requires a number of cognitive skills. BUT, they need to be efficiently integrated.

HOW? Consciousness is (here) considered as the

global process that provides the required synergy (“the grand function”).

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Page 6: Establishing a Roadmap and Metrics for Conscious Machines Development

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Objectives How to measure the level of

consciousness? Quantitatively and Qualitatively.

To propose a developmental path for the design of conscious machines.

Avoid the existing controversial issues about assessing consciousness.

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Page 7: Establishing a Roadmap and Metrics for Conscious Machines Development

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ConsScale Levels Level -1: Disembodied Level 0: Isolated Level 1:Decontrolled Level 2:Reactive Level 3:Adaptive Level 4:Attentional Level 5:Executive Level 6:Emotional Level 7:Self-Conscious Level 8:Empathic Level 9:Social Level 10: Human-like Level 11: Super-Conscious

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ConsScale Levels (Criteria)

Architectural Components Cognitive Skills Observed behavior

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Page 9: Establishing a Roadmap and Metrics for Conscious Machines Development

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ConsScale (I) Level -1: Disembodied

Behavior: not a situated agent. Phylogeny: amino acid

BE

Page 10: Establishing a Roadmap and Metrics for Conscious Machines Development

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ConsScale (II) Level 0: Isolated

Behavior: not a situated agent. Phylogeny: isolated chromosome.

BE

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ConsScale (III) Level 1: Decontrolled

Behavior: not a situated agent. Phylogeny: dead bacteria.

BE

S A

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ConsScale (IV) Level 2: Reactive

Behavior: reflexes. Phylogeny: virus.

S

E

A

B

R

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ConsScale (V) Level 3: Adaptive

Behavior: basic ability to learn new reflexes. Phylogeny: earthworm.

S

E

A

B

R

M

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ConsScale (VI) Level 4: Attentional

Behavior: attack and escape. Attention + emotion. Phylogeny: fish.

S

E

AB

RM

Ei

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ConsScale (VII) Level 5: Executive

Behavior: set shifting. Emotional learning. Phylogeny: quadruped mammal.

S

Ei

AB

RME

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ConsScale (VIII) Level 6: Emotional

Behavior: feelings influence behavior. Phylogeny: monkey. ToM Stage 1: “I know”.

S

Ei

AB

RME

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ConsScale (IX) Level 7: Self-Conscious

Behavior: advanced planning. Usage of tools. Mirror test. Phylogeny: monkey. ToM Stage 2: “I know I know”.

S

Ei

AB

RME “I”

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ConsScale (X) Level 8: Empathic

Behavior: making of tools. Social behavior. Phylogeny: chimpanzee. ToM Stage 3: “I know you know”.

S

Ei

A“I”

RM

E

“others”

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ConsScale (XI) Level 9: Social

Behavior: linguistic capabilities. Ability for culture. Phylogeny: human. ToM Stage 4: “I know you know I know”.

S

Ei

A“I”

RM

“others”

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ConsScale (XII) Level 10: Human-like

Behavior: accurate verbal report. Culture. Technology. Phylogeny: human. Adapted environment.

Ec

S

Ei

A“I”

RM

“others”

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ConsScale (XIII) Level 11: Super-Conscious

Behavior: several streams of consciousness. Phylogeny: n/a.

Ec

S

Ei

A“I” M

“others”

R

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Cognitive Skills (CSi,j)7 CS7,1: Representation of the relation between self and perception.

CS7,2: Representation of the relation between self and action.

CS7,3: Representation of the relation between self and feelings.

CS7,4: Self-recognition capability.

CS7,5: Advance planning including the self as an actor in the plans.

CS7,6: Use of imaginational states in planning.

CS7,7: Learning of tool usage.

8 CS8,1: Ability to model others as subjective selves.

CS8,2: Learning by imitation of a counterpart.

CS8,3: Ability to collaborate with others in the pursuit of a common goal.

CS8,4: Social planning (planning with socially aware plans).

CS8,5: Ability to make new tools.

9 CS9,1: Ability to develop Machiavellian strategies like lying and cunning.

CS9,2: Social learning (learning of new Machiavellian strategies).

CS9,3: Advanced communication skills (accurate report of mental

content).CS9,4: Groups are able to develop a culture.

10 CS10,1: Accurate verbal report. Advanced linguistic capabilities.

CS10,2: Ability to pass the Turing test.

CS10,3: Ability to modify and adapt the environment to agent’s needs.

CS10,4: Groups are able to develop a civilization and advance culture and

technology.

11 CS11,1: Ability to manage several streams of consciousness.

Level Cognitive Skills (CSi,j)

2 CS2,1: Fixed reactive responses (“reflexes”).

3 CS3,1: Autonomous acquisition of new adaptive reactive responses.

CS3,2: Usage of propioceptive sensing for embodied adaptive responses.

4 CS4,1: Selection of relevant sensory information.

CS4,2: Selection of relevant motor information.

CS4,3: Selection of relevant memory information.

CS4,4: Evaluation (positive or negative) of selected objects or events.

CS4,5: Selection of what needs to be stored in memory.

CS4,6: Trial and error learning. Re-evaluation of selected objects or

events.CS4,7: Directed behavior toward specific targets like following or escape.

CS4,8: Evaluation of the performance in the achievement of a single goal.

CS4,9: Basic planning capability: calculation of next n sequential actions.

CS4,10: Depictive representations of percepts [17].

5 CS5,1: Ability to move back and forth between multiple tasks.

CS5,2: Seeking of multiple goals.

CS5,3: Evaluation of the performance in the achievement of multiple

goals.CS5,4: Autonomous reinforcement learning (emotional learning).

CS5,5: Advanced planning capability considering all active goals.

6 CS6,1: Self-status assessment (background emotions).

CS6,2: Background emotions cause effects in agent’s body.

CS6,3: Representation of the effect of emotions in organism (feelings).

CS6,4: Ability to hold a precise and updated map of body schema.

CS6,5: Abstract learning (learned lessons generalization).

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ConsScale as a Roadmap Consider consciousness as an

integrator that puts a mind together.

Consider synergy instead of isolated cognitive abilities.

Evolutionary inspired developmental path.

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CQS

ConsScale Quantitative Score. Li

Particular score for level i. CLS

Cumulative Level score. CQS

ConsScale Quantitative score.

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Li

ncsf Number of cognitive skills fulfilled.

J Maximum number of CS. Ji Total number of CS in level i.

otherwisei

isncsfif

JJncsfLi

103

3

00

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Li (Ji = 6)

1 2 3 4 5 6

0.2

0.4

0.6

0.8

1.0

Ji = 6

ncsf

L i

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Li (Ji = 10)

2 4 6 8 10

0.0

0.2

0.4

0.6

0.8

1.0

Ji = 10

ncsf

L i

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CLS

Li Level i partial score. i Level index.

11

2 1

2

i iLiCLS

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CLS possible values

2 4 6 8 10

0.0

0.5

1.0

1.5

ConsScale Level

CLSi

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CQS (0 to 1000)

CLS Cumulative level score. K Constant value (~0’97). a Constant value (-1).

10

5

aKCLSCQS e

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CQS possible valuesi Description CQS

1 Decontrolled 0.00

2 Reactive 0.18

3 Adaptive 2.21

4 Attentional 12.20

5 Executive 41.23

6 Emotional 101.08

7 Self-Conscious 200.02

8 Empathic 341.44

9 Social 524.54

10 Human-Like 745.73

11 Super-Conscious 1000.00

0.0 0.5 1.0 1.5

020

040

060

080

010

00

CQS for levels 1 to 11.

CLS - Cumulative Levels Score

CQS

L5L1 L2 L3

L4

L6

L7

L8

L9

L10

L11

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CQS online calculator

http://conscious-robots.com/consscale

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Example (I)UT3 Server

UT3 Client(spectator).NET Framework

Robotics Developer Studio Runtime

UT3 Remote Bot API

CERA

CERAUT3 Viewer Server

Mutator

UT3 Client(Human player)

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Example (II)Agent L2 L3 L4 CLS CQS

Reactive-Bot 1 0 0.000 1.000 0.18

Adaptive-Bot 1 1 0.000 1.250 2.22

Attentional-Bot 1 1 0.216 1.255 2.38

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Conclusions

Cognitive approach to artificial consciousness metrics.

Framework for evaluation.

The general scale needs to be instantiated.

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Thank you