cera-cranium: a test bed for machine consciousness research
DESCRIPTION
This paper describes a novel framework designed as a test bed for machine consciousness cognitive models (MCCM). This MCCM experimentation framework is based on a general-purpose cognitive architecture that can be integrated in different environments and confronted with different problem domains. The definition of a generic cognitive control system for abstract agents is the root of the versatility of the presented framework. The proposed control system, which is inspired in the major cognitive theories of consciousness, provides mechanisms for both sensory data acquisition and motor action execution. Sensory and motor data is represented in the proposed architecture using different level workspaces where percepts and actions are generated thanks to the competition and collaboration of specialized processors. Additionally, this cognitive architecture provides the means to modulate perception and behavior; in other words, it offers an interface for a higher control layer to drive the way percepts and actions are generated and how they interact with each other. This mechanism permits the experimentation with virtually any high level cognitive model of consciousness. An illustrative application scenario, autonomous explorer robots, is also reviewed in this work.TRANSCRIPT
Raúl Arrabales, Agapito Ledezma and Araceli Sanchis
Computer Science DepartmentCarlos III University of Madrid
http://Conscious-Robots.com/Raul
International Workshop on Machine Consciousness 2009PolyU, Hong Kong, 14th June 2009
CERA-CRANIUM: A Test Bed for Machine Consciousness
Research
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Contents
Introduction and objectives. Related work. Objectives. CERA-CRANIUM. Experimentation settings. Example of application. Conclusions.
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Introduction (I) Theories of consciousness
Philosophical or psychological background.
Metaphorical descriptions.
Need to bridge the gap between theories and implementation.
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Introduction (II) Cognitive theories of consciousness
Global Workspace Theory (Baars, 1997).
Multiple Draft Model (Dennett, 1991).
Inspiration for the design of a partial computational model of consciousness.
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Introduction (III) Common ground
Non-unitary mechanisms producing the unity of self.
In other words, conscious contents emerge as a result of competition/collaboration (Minsky, Dennett, Hofstadter, Baars, Shanon).
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Introduction (IV) Objectives
To understand how cognitive skills associated with consciousness can be integrated effectively.
To test different machine consciousness models.
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Introduction (V) Functionalism:
Is this a reductionist approach? Does this mean that phenomenal
aspects are ignored?
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Related work (I) Shanahan’s (2005, 2006) cognitive
architecture.
IDA and LIDA (Ramamurthy et al., 2006).
Computational Agent Framework for Consciousness (Moura & Bonzon, 2004).
CERA-CRANIUM (Arrabales et al., 2007, 2008).
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Related work (II) Common denominator:
Shared workspace and specialized processors.
Different approaches in terms of: Architecture. Problem domain. Perceptual flow. Decision taking. Modulation.
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Objectives Experimentation platform.
Test bed for high level cognitive approaches.
Generic but configurable cognitive architecture.
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CERA-CRANIUM (I) CERA-CRANIUM Provides:
Mechanisms for specialized processors
Creation, Association, Combination, Competition.
Mechanisms to regulate the former processes.
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CERA-CRANIUM (II) CERA: layered control architecture.
CRANIUM: runtime tool for the creation and management of high amounts of parallel processes in shared workspaces.
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CERA-CRANIUM (III) CERA: layered design
Sensorimotor services layer. Physical layer. Mission-specific layer. Core layer.
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CERA-CRANIUM (IV)
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Agent
Sensors
Actuators
CERA World
Accessible environment
Reachable environment
Sensor Services
Motor Services
Physical Layer
Mission-specific Layer
Core Layer
Different levels of description
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CERA-CRANIUM (V) CRANIUM
Blackboard Pandemoniu
m
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SpecializedProcessors
Working Memory
Focus of Attention
Contexts
Interim Coalition
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CERA-CRANIUM (VI) Perceptual flow:
Sensory data. Single percepts. Complex percepts. Mission percepts.
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CERA-CRANIUM (VIbis)
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Sensor
Single Percepts
Sensor Preprocessors
Sensor Readings
Timer
Proprioception
Sensor Service
Agent
CERA sensory-motor services
CERA physical layer
Percept Aggregators
S (World)
eventsδSj N(δSj)N(δSJ)
j t
Complex Percept
M(SCJ)
Knowledge representation
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CERA-CRANIUM (VII) Behavior generation:
Mission behaviors. Simple behaviors. Single actions. Motor controller commands.
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CERA-CRANIUM (VIIbis)
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Actuator
Atomic Actions
Action Preprocessors
Single Actions
Timer
Proprioception
Motor Service
Agent
CERA sensory-motor services
CERA physical layer
Action Planners
S (World)
ActionδBi
N(δBi) N(δBI)j t
Simple Behaviors
Action Dispatcher M(BCI)
Action generation
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CERA-CRANIUM (VIII) Bottom-up flow
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CERA Core Layer
CERA M-S LayerCERA Physical LayerSensor Service
Sensor Service
Single Percepts
…
CRANIUM Workspace
Complex Percepts
…
CRANIUM Workspace
Mission Percepts
Sensor Preprocessors
…Specialized Processors
Sensor Service
CERA S-MSensors
…Percept
Aggregators
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CERA-CRANIUM (IX) Top-down flow
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CERA Core Layer
CERA M-S LayerCERA Physical LayerMotor Service
Motor Service
Single Actions
…
CRANIUM Workspace
Simple Behaviors
…
CRANIUM Workspace
Mission Behaviors
Action Preprocessors
…Specialized Processors
Motor Service
CERA S-MActuators
…Action
Planners
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CERA-CRANIUM (X) CRANIUM processor types
Sensor preprocessors Raw sensory data single
percepts
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CERA-CRANIUM (XI) CRANIUM processor types
Action preprocessors Atomic actions Single actions.
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CERA-CRANIUM (XII) CRANIUM processor types
Percept aggregators Single percepts complex
percepts. Complex percepts complex
percepts.
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CERA-CRANIUM (XIII) CRANIUM processor types
Reactive processors Single percept simple
behavior. Complex percept simple
behavior.
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CERA-CRANIUM (XIV) CRANIUM processor types
Action planners Simple behavior atomic
actions.
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CERA-CRANIUM (XV) CRANIUM processor types
Sensory predictors Single percepts mismatch
complex percept. Complex percepts mismatch
complex percept.
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CERA-CRANIUM (XVI) Multi-level concurrent feedback loops
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CERA M-S Layer CERA Core LayerCERA Physical LayerCERA S-MWORLD
(a)
(b)
(c)
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CERA-CRANIUM (XVII) Physical level feedback loops
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Contact Sensor Service
Drive Service
Single Percepts
Simple Behavior
MotorControllers
Crash!
Contact Sensors
WORLD AGENT CERA S-M
CERA Physical Layer
Actions
Complex Percept Reactive
Processor
Workspace
Action Planner
Percept Aggregator
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CERA-CRANIUM (XVIII) Software architecture
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Agent sensory-motor machinery
.Net FrameworkCCR
CRANIUM
DSS
CERA Physical
CERA Sensory- Motor Services
.Net FrameworkCCR
CRANIUMDSS
CERA Mission-specific
.Net FrameworkCCR
DSS
CERA Core
MCCM Configuration
DSSP DSSP
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CERA-CRANIUM (XVIIIbis) Software architecture
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Single Percepts
Complex Percepts
…
Workspace
…
Workspace
Mission Percepts
Core Layer
Physical Layer Mission-Specific Layer
Modulation Commands
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CERA-CRANIUM (XIX) The proposed cognitive
architecture is focused on: Selecting next content of conscious
perception. Selecting next action to be
executed.
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Experimentation settings Variables:
Cognitive model of consciousness. Agent (physical or simulated). Problem domain and mission. Environment (physical or
simulated).
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Applications
Current applications:
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Application example (I)
Autonomous exploration and mapping
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Application example (II)
Autonomous exploration and mapping.
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Application example (III)
Percepts (bumpers).
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(0,0)
-52º
-19º0º
19º
52º
BAb5
BR
b1
b2
b3 b4
b5
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Application example (IV)
Single percept (bumper).
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Impact
j referentLeft-j referent
Right-j referent
N(δSJ)
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Application example (V)
Complex percept (bumper).
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Impact
Left-j referent
Right-j referent
j referent
M(SCJ)
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Application example (VI)
CERA Core Layer Design.
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Physical Layer
Mission Percepts,Complex percepts,Mismatch Percepts,Novelty Percepts,
…
M(SCJ)
…
CRANIUM Workspace
…
CRANIUM Workspace
M-S Layer Core Layer
Workspace Commands
Current Model State
Contextual J-Index
Calculation
Cognitive Model
Meta-goalsRule-based
system
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Conclusions (I)
From sensory to qualia?
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Sonar transducer
Ultrasonic beam (three-dimensional cone)
Left-j referent
Right-j referent
j referent vector(| j | = range measurement)
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Conclusions (II)
Different implementations of CERA layers.
Explore workspace modulation techniques.
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Thank you