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A model of agent consciousnessand its implementation
Ivan MouraNeurocomputing, 69 (16-18) 2006
pp. 1984-1995.
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Outline
• Introduction• Varieties of consciousness• The global workspace model• Identifying computational correlates of consciousness• A sequential abstract machine• A multithreaded virtual machine• Implementing computational correlates of conscious-ness
• Conclusion• Discussion
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Introduction
• Two paths of the study of consciousness– Search for the neural correlates of consciousness
• Recently, many techniques such as the availability of brain-imaging technique helps this issue burgeoning
– Search for the computational correlates of consciousness• This approach lacks of concrete definitions
• The Purpose of this paper– To delineate a functional aspect of consciousness that
can easily be implemented in a computational progress– To allow for practical experiments, this model of intelli-
gent agents has both formal and executable specifica-tions
• The model is based on Baars’ Global Workspace the-ory of consciousness
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Varieties of consciousness
• N Block, On a confusion about a function of con-sciousness, Behav. Brain Sci. 18(2)(1995)
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Four distinct roles
Category Explanation
Access consciousness(A-consciousness)
- Representative, quantitative, functional- Attached to the sensors reflecting environmen-
tal or self-percepts.- The most inclined to be translate an Algorithm
Phenomenal consciousness(P-consciousness)
- To feel emotional experiences, sensations and to get qualitative inputs- Trickier to implement as it deals mainly with subjective and qualitative information- The hard problems are impossible to solve that rely on subjective aspects(Taylor)(So, it is do not considered it in this model)
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Varieties of consciousness
• N Block, On a confusion about a function of con-sciousness, Behav. Brain Sci. 18(2)(1995)
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Four distinct roles
Category Explanation
Self-consciousness(S-consicousness)
- The reflective capability that we enjoy when we think about ourselves- self-recognition, the awareness of one’s iden-tity- Both cases imply interaction inner states or levels, or between members of a common soci-ety
Monitoring consciousness(M-consciousness)
- The state or process of awareness that leads to one’s sensations and percepts- Internal scanning, which organizes and clusters information contained in the consciousness, is regarded as the proactive function of the con-sciousness- Treats collected information
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Varieties of consciousness
• J.K. O’Regan, A.Noe, A sensorimoto account of vision and visual consciousness, Behav. Brain Sci. 24(2001)
– Fitted A-consciousness– The authors insists that P-consciousness does not exist– That it provides an interesting approach to sensing is
good when we identify some computational correlates of consciousness
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Focusing on visual experience
Category Explanation
Transitive visual con-sciousness or con-sciousness of
- one’s ability to be aware of a particular aspect of a scene
Visual consciousness in general
- A high-order capacity representing the ability to be-come aware of a feature and to be conscious of as-pects of a scene
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Varieties of consciousness
• J.G. Tayor, The Race for Conscious, MIT Press, Cam-bridge 1999
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Declarative and non-declarative memory
Category Explanation
Declarative memory - contains elements that can be conscious- type1 : episodic and autobiographic memories(often called explicit memory) involving experienced or learned elements that one remember- type2 : semantic memory(implicit memory) repre-sents available elements such as general knowledge but the ways they are experienced or learnt elements that one remembers
Non-declarative memory
- contains ‘only representations, such as skills, of which we have no such awareness’
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Varieties of consciousness
• J.G. Tayor, The Race for Conscious, MIT Press, Cam-bridge 1999
– Three parts based on declarative and non-declarative memory
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Declarative and non-declarative memory
Category Explanation
Passive (or perceptual) consciousness
- Occurs when Situations are experienced in a pas-sive mode without accessing to the self
Active consciousness - Occurs when one thinks hard about a problem, paying less attention to perceptual inputs and auto-biographical recalls, unless they are needed to solve the problem
Self-consciousness - the reflective capacity of consciousness ‘in which you are moved by personal memories or are aware of yourself as the experiencer’
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Varieties of consciousness
• A.P. Atkinson, M.S.C. Thomas, A. Cleermans, Con-sciousness : mapping the theoretical landscape, Trends Cogn. Sci. 4(10) (2000)
• Effective computational simulation should qualify as a specilized process model
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Process vs. Representation theory and Specialized vs. Non-specialized theory
Category Explanation
Process vs. repre-sentation
The process vs. representation dimension opposes mod-els that explain consciousness in terms of specific pro-cesses operating over mental representations, with mod-els that explain consciousness in terms of intrinsic prop-erties of mental representation
Specialized vs. non-specialized
The specialized vs. non-specialized distinction refers to the existence or non-existence of a dedicated machinery for consciousness. In the absence of such dedicated ma-chinery, consciousness could be said to emerge from the ‘collective activity of many components distributed both spatially and functionally across the brain, none of them responsible for consciousness on its own’
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The global workspace model
• Well formalized computational model of conscious-ness
• Indentifying and describing the actors that are in-volved in consciousness as well as their interactions, roles and functions
• Made of Modules organized in societies, each having its own functionality and specialization
• Not animated by a government but by its members taken as a whole
• A bottleneck is needed to force the modules either to compete or to collaborate
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The global workspace model
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The global workspace model
• Unconsciousness specialized processors– The basic components– A simple skill, a basic knowledge
• Consciousness or global workspace– A working memory that plays the roles of a bottleneck al-
lowing the system to be regulated– When an unconscious specialized processor is unable to
achieve a given task by itself, it accesses the conscious-ness that will in turn broadcast the needs of the proces-sor to the entire system
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The global workspace model
• Coalitions and conscious processes– The unconscious specialized processors that answer the
broadcasted needs form together with the requesting processor a coalition able to achieve a given task
• Contexts– They are the assumptions of the system that restrain ac-
cess to the consciousness and discharge the coalition formation process
– A context is unconscious and is constituted of a set of specialized processors
– Contexts are composite skills– They are organized into a hierarchy where higher the
level wider the scope– It supports a form of psychological evolution, a form of
learning.
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Identifying computational correlates of consciousness
• Two Functions established by the observation of the global workspace
– Consciousness gives to the unconscious processors the opportunity to form a coalition in order to achieve a given task
– The global workspace allow to fix coalitions into contexts, thus automating action selection(learning process which allows to shift deliberation to automation M-conscious-ness)
• Two types of processors– Processors that depict the environment
• A representation of external elements or situational informa-tion(Facts)
– Processors that activate an action• The action itself is not represented• We assume that such an action is automated and represented
within a context(To call for an action is similar to a calling for a context) 14
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Identifying computational correlates of consciousness
• Formation of coalitions is called deliberation
• A context is defined as an unconscious and permanent processor coalition
– A context formed by Coalitions compiled
• Contexts can select an action without calling on global workspace
• The representation of the environment is abstracted as we assume that the environmental processors are generated by lower-level system
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A sequence abstract machine
• A set of procedures implementing abstract functions defining a general model of reactive agent with sens-ing
• Basic components
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Symbol Explanation
P A plan
A An action
Conditions do(p,a) Action selelction
Conditions switch(p,p’) Changing plan
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A sequence abstract machine
• Example– An agent whose goal is to wander in a grid and to suck
dirt when he finds some or to go (or stay) home when room is clean
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A sequence abstract machine
• Deliberation can be represented within a tree
• Leaves : the action selection processors• Italic-branches : the processor depicting environment• Nodes : the plan names
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A sequence abstract machine
• The abstract machine is defined within the following procedures
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Symbol Explanation
l Agent’s local state
e Environment
p A plan(p0 is the initial plan)
├ The deduction rules where an action selection
Υ Transition functions on the environment
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A sequence abstract machine
• The Layer for Physical system is abstract• This abstract machine implements the deliberation process via sequential processors
• Recalling that consciousness is made of parallel pro-cessors, that several coalitions can access conscious-ness and that consciousness itself is made of two concurrent levels,i.e., deliberation and context forma-tion, calls for a parallel abstract
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A multithreaded virtual machine
• S-conscious– reflective ability– Internal and formal communication language needed to
achieve duties of higher order
• A concurrent agent language that allows to imple-ment agent conversations with dialogues
This language is provided by Bonzon
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Compiling Dynamic Agent Conversations
• Pierre Bonzon, Compiling Dynamic Agent Conversa-tions KI 2002 : Advances in Artificial Intelligence
• Purpose– For multi-agent systems– To implement abstract logical machine that is defined
purely in sequential terms– To support synchronization of this model
• Basic Symbols
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Symbol Explanation
├ The deduction sign
l The Local state
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Compiling Dynamic Agent Conversations
• The Dialog Structure
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Symbol Explanation
| 1. To separate the head and tail list2. To Isolate the guard in a guarded message
|| Metasymbol for representing choices
, Sequence or Conjuction
; Alternative or disjunction
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A multithreaded virtual machine
• Dialog consists of branching sequences of messages with end alternatives
• Branching sequences can have an embedded struc-ture
• Each alternative is prefixed with a condition, the guard
• A guard acts like a deamon. The dialogue is blocked until a guard is satisfied
• Unless re-entered with a resume message, dialogs are exited at the end of a sequence
• Actions interleaved with messages can be executed with an execute message
• Subdialogues can be entered with an enter message• New parallel dialogues can be run with a concurrent message
• Synchronization between two dialogues is achieved with the pairs of messages tell/ask for information ex-change and call/return for requests
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A multithreaded virtual machine
• These dialogues are compiled into plans executed on an abstract machine
• Each dialogue is executed in a separated thread
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A multithreaded virtual machine
• A representation of the virtual machine
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A multithreaded virtual machine
• The agent behaviors is defined with plans that are now deduced by the concurrent virtual machine im-plemented with concurrent dialogs
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A multithreaded virtual machine
• In order to initiate context formation, which is the second functional correlate of consciousness along with deliberation, we reflect the agent’s deliberation to a meta level
• The deliberation process is mirrored in a concurrent level that will serve to implement the context forma-tion process
• Reflection achieves the agent’s ability to become con-scious of its deliberation steps
• New dialogue introspect starts a new thread attached on both basic deliberation threads : switch and do
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A multithreaded virtual machine
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A multithreaded virtual machine
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Implementing computational correlates of consciousness
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• The reflected deliberation progress recording each plans switching with the related condition
• Reflect(switch) stores a switched/3 predicate contain-ing the condition C that triggered the plan switching from P to Q in a dedicated object gw(standing for global workspace)
• The condition is obtained through a request commu-nication act synchronizing the switch dialogue with its reflect dialogue
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Implementing computational correlates of consciousness
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• The reflected deliberation progress recording each plans switching with the related condition
• Reflect(switch) stores a switched/3 predicate contain-ing the condition C that triggered the plan switching from P to Q in a dedicated object gw(standing for global workspace)
• The condition is obtained through a request commu-nication act synchronizing the switch dialogue with its reflect dialogue
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Implementing computational correlates of consciousness
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• Applying reflection to our example may result in ob-taining the following predicates in the gw object:
• Compilation consists in grouping all conditions having led to select an action and generating a new plan of type ‘context’ ==> do(initial, a)‘context’ is the context formed with all the conditions and their generalized arguments
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Implementing computational correlates of consciousness
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• Reflect(do) starts the compilation process initiated by the dialogue trace
• Applying it to our example, the following plans are generated :
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Implementing computational correlates of consciousness
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Implementing computational correlates of consciousness
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• A new plan is set in the agent’s state through the dia-logue teach that runs at the termination of the get_context procedure
• The dialogue teach simply transmits the plan to a learn dialogue that inserts it in the agent’s local state
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Implementing computational correlates of consciousness
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• A new plan is set in the agent’s state through the dia-logue teach that runs at the termination of the get_context procedure
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Implementing computational correlates of consciousness
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• A new plan is set in the agent’s state through the dia-logue teach that runs at the termination of the get_context procedure
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Conclusion
• The key to machine consciousness is to rely on a con-current and multilayered model with explicit interac-tions and synchronization between the threads, as for human consciousness
• The axioms proposed by Aleksander and Dunmmal
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AXIOM Valuation
Depiction axiom interacting with the environment
Imagination ax-iom
It is not enough because this model is predefined. However, this paper consid-ers compiled contexts are ‘imagined el-ements’
Attention axiom Bottleneck is attention
Planning axiom Planning consists in calling the uncon-scious processors leading to a change of state or to an action selection
Emotion axiom It is Not enough. But, context disruption supports it.
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Discussion
• The Computational correlates of consciousness 의 모델들의 우수성은 어떻게 평가할 수 있나 ?
• 이 논문에서 배제한 P-consciousness(feeling) 을 고려한다고 가정하면 어떤 방법들이 존재할 수 있나 ?
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