scholarly journals Knowledge Dynamics and Behavioural Equivalencesin Multi-Agent Systems

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2869
Author(s):  
Bogdan Aman ◽  
Gabriel Ciobanu
Keyword(s):  
Local Knowledge ◽  
Operational Semantics ◽  
Transition System ◽  
Process Calculus ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Knowledge Dynamics ◽  
The Relationship ◽  
Labelled Transition System

We define a process calculus to describe multi-agent systems with timeouts for communication and mobility able to handle knowledge. The knowledge of an agent is represented as sets of trees whose nodes carry information; it is used to decide the interactions with other agents. The evolution of the system with exchanges of knowledge between agents is presented by the operational semantics, capturing the concurrent executions by a multiset of actions in a labelled transition system. Several results concerning the relationship between the agents and their knowledge are presented. We introduce and study some specific behavioural equivalences in multi-agent systems, including a knowledge equivalence able to distinguish two systems based on the interaction of the agents with their local knowledge.

Hierarchical Design Method for Multi-Agent Systems

2015 ◽  
Vol 7 (2) ◽  
pp. 105-134
Author(s):  
Bouneb Messaouda ◽  
Saïdouni Djamel Eddine
Keyword(s):  
Design Methodology ◽  
Design Method ◽  
Transition System ◽  
Hierarchical Design ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Labeled Transition System ◽  
System Assessment ◽  
Definition Of

This paper proposes a new hierarchical design method for the specification and the verification of multi agent systems (MAS). For this purpose, the authors propose the model of Refinable Recursive Petri Nets (RRPN) under a maximality semantics. In this model, a notion of undefined transitions is considered. The underlying semantics model is the Abstract Maximality-based Labeled Transition System (AMLTS). Hence, the model supports a definition of a hierarchical design methodology. The example of goods transportation is used for illustrating the approach. For the system assessment, the properties are expressed in CTL logic and verified using the verification environment FOCOVE (Formal Concurrency Verification Environment).

Application of Fuzzy Labeled Transition System to Contract Net Protocol

2015 ◽  
Vol 6 (3) ◽  
pp. 27-46 ◽  
Author(s):  
Sofia Kouah ◽  
Djamel Eddine Saïdouni
Keyword(s):  
Dynamic Systems ◽  
Transition System ◽  
Multi Agent Systems ◽  
Contract Net Protocol ◽  
Agent Systems ◽  
Contract Net ◽  
Multi Agent ◽  
Refinement Process ◽  
Labeled Transition System

For developing large dynamic systems in a rigorous manner, fuzzy labeled transition refinement tree (FLTRT for short) has been defined. This model provides a formal specification framework for designing such systems. In fact, it supports abstraction and enables fuzziness which allows a rigorous formal refinement process. The purpose of this paper is to illustrate the applicability of FLTRT for designing multi agent systems (MAS for short), among others collective and internal agent's behaviors. Therefore, Contract Net Protocol (CNP for short) is chosen as case study.

scholarly journals A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities - In the Context of I4.0 as Virtual Assets (AAS)

2021 ◽  
Author(s):  
Jackson Tavares Veiga ◽  
Marcosiris Amorim de Oliveira Pessoa ◽  
Fabrício Junqueira ◽  
Paulo Eigi Miyagi ◽  
Diolino José Dos Santos Filho
Keyword(s):  
Intelligent Agents ◽  
Manufacturing Systems ◽  
Multi Agent Systems ◽  
Production Flow ◽  
Systematic Method ◽  
Passive Components ◽  
Agent Systems ◽  
Modelling Procedure ◽  
Multi Agent ◽  
The Relationship

Manufacturing systems need to meet I4.0 guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements behavior.

scholarly journals A Logic for Agent Organizations

2009 ◽  
pp. 220-240 ◽  
Author(s):  
Virgina Dignum ◽  
Frank Dignum
Keyword(s):  
Social Order ◽  
Autonomous Agents ◽  
Formal Model ◽  
Organizational Structures ◽  
Theoretical Framework ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Common Goals ◽  
The Relationship

Organization concepts and models are increasingly being adopted for the design and specification of multi-agent systems. Agent organizations can be seen as mechanisms of social order, created to achieve common goals for more or less autonomous agents. In order to develop a theory on the relationship between organizational structures, organizational actions, and actions of agents performing roles in the organization, we need a theoretical framework to describe and reason about organizations. The formal model presented in this chapter is sufficiently generic to enable the comparison of different existing organizational approaches to Multi-Agent Systems (MAS), while having enough descriptive power to describe realistic organizations.

scholarly journals A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities—In the Context of I4.0 as Virtual Assets (AAS)

Computers ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 161
Author(s):  
Jackson T. Veiga ◽  
Marcosiris A. O. Pessoa ◽  
Fabrício Junqueira ◽  
Paulo E. Miyagi ◽  
Diolino J. dos Santos Filho
Keyword(s):  
Intelligent Agents ◽  
Manufacturing Systems ◽  
Multi Agent Systems ◽  
Production Flow ◽  
Systematic Method ◽  
Passive Components ◽  
Agent Systems ◽  
Modelling Procedure ◽  
Multi Agent ◽  
The Relationship

Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements’ behavior.

scholarly journals A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities - In the Context of I4.0 as Virtual Assets (AAS)

2021 ◽  
Author(s):  
Jackson Tavares Veiga ◽  
Marcosiris Amorim de Oliveira Pessoa ◽  
Fabrício Junqueira ◽  
Paulo Eigi Miyagi ◽  
Diolino José Dos Santos Filho
Keyword(s):  
Intelligent Agents ◽  
Manufacturing Systems ◽  
Multi Agent Systems ◽  
Production Flow ◽  
Systematic Method ◽  
Passive Components ◽  
Agent Systems ◽  
Modelling Procedure ◽  
Multi Agent ◽  
The Relationship

Manufacturing systems need to meet I4.0 guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements behavior.

Modeling knowledge dynamics in multi-agent systems based on informants

2012 ◽  
Vol 27 (1) ◽  
pp. 87-114 ◽  
Author(s):  
Luciano H. Tamargo ◽  
Alejandro J. García ◽  
Marcelo A. Falappa ◽  
Guillermo R. Simari
Keyword(s):  
Axiomatic Characterization ◽  
Minimal Change ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Representation Theorems ◽  
Consistency Maintenance ◽  
Agent Systems ◽  
Multi Agent ◽  
Knowledge Dynamics ◽  
Epistemic Model

AbstractIn this paper, we model knowledge dynamics in agents’ belief bases in a collaborative multi-agent system (MAS). Four change operators are introduced: expansion, contraction, prioritized revision, and non-prioritized revision. For all of them, both constructive definitions and an axiomatic characterization by representation theorems are given. We formally justify minimal change, consistency maintenance, and non-prioritization principles. These operators are based on an epistemic model for multi-source belief revision in which a rational way to weigh the beliefs using a credibility order among agents is developed. The defined operators can be seen as skills added to the agents improving the collective reasoning of a MAS.

Machine Learning for Agents and Multi-Agent Systems

2011 ◽  
pp. 1-26
Author(s):  
Daniel Kudenko ◽  
Dimitar Kazakov ◽  
Eduardo Alonso
Keyword(s):  
Machine Learning ◽  
Autonomous Agents ◽  
Machine Learning Techniques ◽  
Multi Agent Systems ◽  
Learning Agents ◽  
Agent Systems ◽  
Learning Techniques ◽  
Comprehensive Survey ◽  
Multi Agent ◽  
The Relationship

In order to be truly autonomous, agents need the ability to learn from and adapt to the environment and other agents. This chapter introduces key concepts of machine learning and how they apply to agent and multi-agent systems. Rather than present a comprehensive survey, we discuss a number of issues that we believe are important in the design of learning agents and multi-agent systems. Specifically, we focus on the challenges involved in adapting (originally disembodied) machine learning techniques to situated agents, the relationship between learning and communication, learning to collaborate and compete, learning of roles, evolution and natural selection, and distributed learning. In the second part of the chapter, we focus on some practicalities and present two case studies.

Machine Learning for Agents and Multi-Agent Systems

2011 ◽  
pp. 403-420
Author(s):  
Daniel Kudenko ◽  
Dimitar Kazakov ◽  
Eduardo Alonso
Keyword(s):  
Machine Learning ◽  
Autonomous Agents ◽  
Machine Learning Techniques ◽  
Multi Agent Systems ◽  
Learning Agents ◽  
Agent Systems ◽  
Learning Techniques ◽  
Comprehensive Survey ◽  
Multi Agent ◽  
The Relationship

In order to be truly autonomous, agents need the ability to learn from and adapt to the environment and other agents. This chapter introduces key concepts of machine learning and how they apply to agent and multi-agent systems. Rather than present a comprehensive survey, we discuss a number of issues that we believe are important in the design of learning agents and multi-agent systems. Specifically, we focus on the challenges involved in adapting (originally disembodied) machine learning techniques to situated agents, the relationship between learning and communication, learning to collaborate and compete, learning of roles, evolution and natural selection, and distributed learning. In the second part of the chapter, we focus on some practicalities and present two case studies.

scholarly journals MAPSS an Intelligent Architecture for the Pedagogical Support: Experiment, Results & Discussion

2019 ◽  
Vol 14 (21) ◽  
pp. 61 ◽  
Author(s):  
Najoua Hrich ◽  
Mohamed Lazaar ◽  
Mohamed Khaldi
Keyword(s):  
Decision Making ◽  
Secondary School ◽  
Support System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Adaptive Architecture ◽  
Multi Agent ◽  
Cognitive Decision ◽  
The Impact ◽  
The Relationship

In this paper, the authors have experimented the MaPSS (Multiagent pedagogical support system) which is an adaptive architecture based on ontologies and multi-agent systems for the presentation of the pedagogical support in its principal tasks: assessment of the knowledge, analyze of results and adapt remediation. In previous works, the authors have designed an ontology to present the relationship between the test questions and the concepts to evaluate and between those concepts and their remedial activities contents. Also, they have presented the operation of each agent (IT or human) of the system and the principle of collaboration between them. The experience consists on the use of an implemented prototype of MaPSS to support learners of Moroccan qualified secondary school in the domain of algorithmic and programming, and the impact of its use on the improving cognitive decision making to adapt learning.

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