Dimensions in programming multi-agent systems

Author(s):  
Olivier Boissier ◽  
Rafael H. Bordini ◽  
Jomi F. Hübner ◽  
Alessandro Ricci

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.

2021 ◽  
Author(s):  
valeria seidita ◽  
francesco lanza ◽  
Patrick Hammer ◽  
Antonio Chella ◽  
Pei Wang

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.


2021 ◽  
Author(s):  
valeria seidita ◽  
francesco lanza ◽  
Patrick Hammer ◽  
Antonio Chella ◽  
Pei Wang

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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