Hybrid Multi-agent Systems: Integrating Swarming and BDI Agents

2007 ◽  
pp. 1-14 ◽  
Author(s):  
H. Van Dyke Parunak ◽  
Paul Nielsen ◽  
Sven Brueckner ◽  
Rafael Alonso
Keyword(s):  
Multi Agent Systems ◽  
Bdi Agents ◽  
Agent Systems ◽  
Multi Agent

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.

Dimensions in programming multi-agent systems

2019 ◽  
Vol 34 ◽  
Author(s):  
Olivier Boissier ◽  
Rafael H. Bordini ◽  
Jomi F. Hübner ◽  
Alessandro Ricci
Keyword(s):  
Programming Model ◽  
Environment Interaction ◽  
Multi Agent Systems ◽  
Bdi Agents ◽  
Agent Systems ◽  
Programming Abstractions ◽  
Multi Agent

Abstract Research on Multi-Agent Systems (MAS) has led to the development of several models, languages, and technologies for programming not only agents, but also their interaction, the application environment where they are situated, as well as the organization in which they participate. Research on those topics moved from agent-oriented programming towards multi-agent-oriented programming (MAOP). A MAS program is then designed and developed using a structured set of concepts and associated first-class design and programming abstractions that go beyond the concepts normally associated with agents. They include those related to environment, interaction, and organization. JaCaMo is a platform for MAOP built on top of three seamlessly integrated dimensions (i.e. structured sets of concepts and associated execution platforms): for programming belief desire intention (BDI) agents, their artefact-based environments, and their normative organizations. The key purpose of our work on JaCaMo is to support programmers in exploring the synergy between these dimensions, providing a comprehensive programming model, as well as a corresponding platform for developing and running MAS. This paper provides a practical overview of MAOP using JaCaMo. We show how emphasizing one particular dimension leads to different solutions to the same problem, and discuss the issues of each of those solutions.

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.

Design of an Intelligent System to Support Tutors in Learning Communities Using Multi-Agent Systems and Fuzzy Logic

2015 ◽  
Vol 10 (8) ◽  
pp. 845 ◽  
Author(s):  
Youness Chaabi ◽  
R. Messoussi ◽  
V. Hilaire ◽  
Y. Ruichek ◽  
K. Lekdioui ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Learning Communities ◽  
Intelligent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent
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