scholarly journals Agents and Robots for Reliable Engineered Autonomy:A Perspective from the Organisers of AREA 2020

2021 ◽  
Vol 10 (2) ◽  
pp. 33
Author(s):  
Rafael C. Cardoso ◽  
Angelo Ferrando ◽  
Daniela Briola ◽  
Claudio Menghi ◽  
Tobias Ahlbrecht
Keyword(s):  
Research Trends ◽  
Multi Agent Systems ◽  
Open Problems ◽  
Future Directions ◽  
Agent Systems ◽  
Research Areas ◽  
Multi Agent ◽  
Active Research ◽  
High Level ◽  
First Time

Multi-agent systems, robotics and software engineering are large and active research areas with many applications in academia and industry. The First Workshop on Agents and Robots for reliable Engineered Autonomy (AREA), organised the first time in 2020, aims at encouraging cross-disciplinary collaborations and exchange of ideas among researchers working in these research areas. This paper presents a perspective of the organisers that aims at highlighting the latest research trends, future directions, challenges, and open problems. It also includes feedback from the discussions held during the AREA workshop. The goal of this perspective is to provide a high-level view of current research trends for researchers that aim at working in the intersection of these research areas.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 2338-2350
Author(s):  
Robert E. Smith ◽  
Claudia Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Multi-Agent Systems Research and Social Science Theory Building

2007 ◽  
pp. 101-110
Author(s):  
H. Verhagen
Keyword(s):  
Social Science ◽  
Organization Theory ◽  
Social Science Research ◽  
Science Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Research Areas ◽  
Systems Research ◽  
Science Theory ◽  
Multi Agent

This chapter describes the possible relationship between multi-agent systems research and social science research, more particularly sociology. It gives examples of the consequences and possibilities of these relationships, and describes some of the important issues and concepts in each of these areas. It finally points out some future directions for a bi-directional relationship between the social sciences and multi-agent systems research which hopefully will help researchers in both research areas, as well as researchers in management and organization theory.

scholarly journals Deliberative Agents in Dynamic Environments, Using Jason and NARS

2021 ◽  
Author(s):  
valeria seidita ◽  
francesco lanza ◽  
Patrick Hammer ◽  
Antonio Chella ◽  
Pei Wang
Keyword(s):  
Dynamic Environments ◽  
General Intelligence ◽  
Multi Agent Systems ◽  
Bdi Agents ◽  
Agent Systems ◽  
Intelligence System ◽  
Artificial General Intelligence ◽  
Reasoning System ◽  
Multi Agent ◽  
High Level

This work explore the possibility to combine the Jason reasoning cycle with a Non-Axiomatic Reasoning System (NARS) to develop multi-agent systems that are able to reason, deliberate and plan when information about plans to be executed and goals to be pursued is missing or incomplete. The contribution of this work is a method for BDI agents to create high-level plans using an AGI (Artificial General Intelligence) system based on non-axiomatic logic.

A Collaborative Multi-Agent Framework for Internet-Based Teleoperation Systems

2013 ◽  
Vol 5 (2) ◽  
pp. 31-54
Author(s):  
Nader Cheaib ◽  
Samir Otmane ◽  
Malik Mallem
Keyword(s):  
Conceptual Model ◽  
Multi Agent Systems ◽  
Collaborative Process ◽  
Agent Systems ◽  
Collaborative Software ◽  
Research Areas ◽  
Multi Agent ◽  
Collaboration Process ◽  
3C Model ◽  
Teleoperation Systems

This paper presents a conceptual model of an agent (called Collaborator Agent) intended to design collaborative software architectures based on multi-agent systems. The authors’ model combines astutely two research areas: Multi-Agent Systems (MAS) and Computer Supported Cooperative Work (CSCW). The particularity of their approach is the division of the collaborative process into three spaces according to Ellis' 3C model: communication, coordination and production. In their work, the authors extend the 3C model by adding a fourth space: collaboration. Hence, the authors present a model based on four types of agents (collaboration, communication, coordination and production) supporting the whole set of collaborative tasks. The model is used to create the conceptual software architecture of their MAS. The authors apply their conceptual model on the ARITI-C system for collaborative online robot teleoperation. Finally, the authors present a quantitative evaluation of the collaboration process in ARITI-C.

scholarly journals Desire: Modelling Multi-Agent Systems in a Compositional Formal Framework

1997 ◽  
Vol 06 (01) ◽  
pp. 67-94 ◽  
Author(s):  
Frances M. T. Brazier ◽  
Barbara M. Dunin-Keplicz ◽  
Nick R. Jennings ◽  
Jan Treur
Keyword(s):  
Transportation Network ◽  
Application Domain ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Modelling Framework ◽  
Formal Framework ◽  
Multi Agent ◽  
High Level ◽  
Electricity Utility

This paper discusses an example of the application of a high-level modelling framework which supports both the specification and implementation of a system's conceptual design. This framework, DESIRE (framework for DEsign and Specification of Interacting REasoning components), explicitly models the knowledge, interaction, and coordination of complex tasks and reasoning capabilities in agent systems. For the application domain addressed in this paper, an operational multi-agent system which manages an electricity transportation network for a Spanish electricity utility, a comprehensible specification is presented.

An event-driven high level model for the specification of laws in open multi-agent systems

2009 ◽  
Vol 82 (4) ◽  
pp. 629-642 ◽  
Author(s):  
Rodrigo Paes ◽  
Carlos Lucena ◽  
Gustavo Carvalho ◽  
Don Cowan
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Event Driven ◽  
Multi Agent ◽  
Level Model ◽  
High Level

scholarly journals Deliberative Agents in Dynamic Environments, Using Jason and NARS

2021 ◽  
Author(s):  
valeria seidita ◽  
francesco lanza ◽  
Patrick Hammer ◽  
Antonio Chella ◽  
Pei Wang
Keyword(s):  
Dynamic Environments ◽  
General Intelligence ◽  
Multi Agent Systems ◽  
Bdi Agents ◽  
Agent Systems ◽  
Intelligence System ◽  
Artificial General Intelligence ◽  
Reasoning System ◽  
Multi Agent ◽  
High Level

This work explore the possibility to combine the Jason reasoning cycle with a Non-Axiomatic Reasoning System (NARS) to develop multi-agent systems that are able to reason, deliberate and plan when information about plans to be executed and goals to be pursued is missing or incomplete. The contribution of this work is a method for BDI agents to create high-level plans using an AGI (Artificial General Intelligence) system based on non-axiomatic logic.

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