An Abstract Machine for Classes of Communicating Agents Based on Deduction

Bonzon, Pierre E.

doi:10.1007/3-540-45448-9_15

Cited by 3 publications

(5 citation statements)

References 8 publications

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“…In contrast, the caught operator was defined using a ask(s,ψ)/tell(r,ϕ) pair involving a simplified ϕ ψθ operation (because the agent's local state cannot be of any use in this case). Somehow, this a posteriori justifies the choice of communication primitives we made in [3]. We are well aware of the formal inconsistencies that arise when trying to model self referential sentences using a single uniform language, as discovered by Montague [13].…”

Section: Discussionmentioning

confidence: 84%

“…where the acknowledgment flag ack(i,message) is raised in l Class when the message issued by agent i is interpreted using function τ i (for further details, see [3]). Similarly to actions, the synchronizing operations tellAsk and callReturn are interpreted by state transformer functions τ Class that uses l Class as a blackboard.…”

Section: A Virtual Machine For Executing Dialogsmentioning

confidence: 99%

“…Our recent proposal, that introduces formal communication primitives within a multi-agent system [3] and defines a language for agent dialogs [4], is an example of an agent model that can be used for this purpose. In this approach, consciousness will primarily function as a monitor of actions and beliefs (in the weak sense of the word and not in Hoare's strict sense) that allows for the triggering of new actions.…”

Section: Introductionmentioning

confidence: 99%

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Conscious Behavior through Reflexive Dialogs

Bonzon

2003

KI 2003: Advances in Artificial Intelligence

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We consider the problem of executing conscious behavior i.e., of driving an agent's actions and of allowing it, at the same time, to run concurrent processes reflecting on these actions. Toward this end, we express a single agent's plans as reflexive dialogs in a multi-agent system defined by a virtual machine. We extend this machine's planning language by introducing two specific operators for reflexive dialogs i.e., conscious and caught for monitoring beliefs and actions, respectively. The possibility to use the same language both to drive a machine and to establish a reflexive communication within the machine itself stands as a key feature of our model.

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Section: Discussionmentioning

confidence: 84%

Section: A Virtual Machine For Executing Dialogsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Conscious Behavior through Reflexive Dialogs

Bonzon

2003

KI 2003: Advances in Artificial Intelligence

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“…At the¯rst level, resulting from the integration of communication into a model of intelligent agents [Bonzon, 2002a], processes are de¯ned in a high level language that provides the necessary tool for the simulation of cognitive functions. At the second level, abstract de¯nitions (including logical expressions representing compiled knowledge) are mapped into a variation of the -calculus [Milner, 1999].…”

Section: Introduction: a Methodological Problemmentioning

confidence: 99%

TOWARDS MACHINE CONSCIOUSNESS: GROUNDING ABSTRACT MODELS AS Π-Processes

Bonzon¹

2011

Int. J. Mach. Conscious.

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We present a two-level model of concurrent communicating systems (CCS) to serve as a basis for machine consciousness. A language implementing threads within logic programming is¯rst introduced. This high-level framework allows for the de¯nition of abstract processes that can be executed on a virtual machine. We then look for a possible grounding of these processes into the brain. Towards this end, we map abstract de¯nitions (including logical expressions representing compiled knowledge) into a variant of the -calculus. We illustrate this approach through a series of examples extending from a purely reactive behavior to patterns of consciousness.

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“…We then integrated within this framework a simplification of the communication model [5]. In the resulting model [1], two agents communicate under the control of nd-plans requiring each a synchronization flag. These plans are directly executable on our abstract machine (in essence, a sequential machine with deductive capabilities).…”

Section: Introductionmentioning

confidence: 99%

Compiling Dynamic Agent Conversations

Bonzon

2002

KI 2002: Advances in Artificial Intelligence

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We consider defining executable dialogues for communicating agents. Towards this end, we introduce agent classes whose communication primitives are based on deduction. Their operational semantics are given by an abstract logical machine that is defined purely in sequential terms. These agents communicate under the control of plans requiring a synchronization flag. These plans can be rewritten as dialogues with an implicit synchronization. Reversibly, dialogues can be compiled back into plans and then executed on the sequential machine. Sub-dialogues can be entered from any dialogue, such achieving dynamic conversation structures.

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An Abstract Machine for Classes of Communicating Agents Based on Deduction

Cited by 3 publications

References 8 publications

Conscious Behavior through Reflexive Dialogs

Conscious Behavior through Reflexive Dialogs

TOWARDS MACHINE CONSCIOUSNESS: GROUNDING ABSTRACT MODELS AS Π-Processes

Compiling Dynamic Agent Conversations

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