scholarly journals Modelling and verifying BDI agents with bigraphs

2022 ◽  
Vol 215 ◽  
pp. 102760 ◽  
Author(s):  
Blair Archibald ◽  
Muffy Calder ◽  
Michele Sevegnani ◽  
Mengwei Xu
Keyword(s):  
2020 ◽  
Vol 16 (4) ◽  
pp. 343-377
Author(s):  
Adel Saadi ◽  
Ramdane Maamri ◽  
Zaidi Sahnoun

The Belief-Desire-Intention (BDI) model is a popular approach to design flexible agents. The key ingredient of BDI model, that contributed to concretize behavioral flexibility, is the inclusion of the practical reasoning. On the other hand, researchers signaled some missing flexibility’s ingredient, in BDI model, essentially the lack of learning. Therefore, an extensive research was conducted in order to extend BDI agents with learning. Although this latter body of research is important, the key contribution of BDI model, i.e., practical reasoning, did not receive a sufficient attention. For instance, for performance reasons, some of the concepts included in the BDI model are neglected by BDI architectures. Neglecting these concepts was criticized by some researchers, as the ability of the agent to reason will be limited, which eventually leads to a more or less flexible reasoning, depending on the concepts explicitly included. The current paper aims to stimulate the researchers to re-explore the concretization of practical reasoning in BDI architectures. Concretely, this paper aims to stimulate a critical review of BDI architectures regarding the flexibility, inherent from the practical reasoning, in the context of single agents, situated in an environment which is not associated with uncertainty. Based on this review, we sketch a new orientation and some suggested improvements for the design of BDI agents. Finally, a simple experiment on a specific case study is carried out to evaluate some suggested improvements, namely the contribution of the agent’s “well-informedness” in the enhancement of the behavioral flexibility.


Author(s):  
Alan Davoust ◽  
Patrick Gavigan ◽  
Cristina Ruiz-Martin ◽  
Guillermo Trabes ◽  
Babak Esfandiari ◽  
...  

Author(s):  
Joao Mario Lopes Brezolin ◽  
Sandro Rama Fiorini ◽  
Marcia De Borba Campos ◽  
Rafael H. Bordini

2018 ◽  
Vol 1 (2) ◽  
pp. 160-167
Author(s):  
John Jairo Páez-Rodríguez ◽  
Enrique González-Guerrero ◽  
Andrea Sánchez-Vallejo

This study presents the advances in the design of the architecture called Human-Robot Scaffolding. The Architecture allows an anthropomorphic social robot to intervene assertively during the learning of the Mean-Fines analysis strategy. Its design recognizes three aspects. Firstly, the scaffolding educational strategy. Second, the psychological theory of Flow. Third, the paradigm BDI agents for the execution of the robot's goals. The partial validation of the architecture has been done with 20 children between 10 and 13 years old from two schools in Colombia. According to the results, the modules and the goals proposed in the architecture promote in an assertive way the learning of the Mean-Fines analysis strategy.


2020 ◽  
Vol 27 (4) ◽  
pp. 442-453
Author(s):  
Nikolay Vyacheslavovich Shilov ◽  
Natalia Olegovna Garanina

Multiagent algorithm is a knowledge-based distributed algorithm that solves some problems by means of cooperative work of agents. From an individual agent's perspective, a multiagent algorithm is a reactive and proactive knowledge/believe-based rational algorithm aimed to achieve an agent's own desires. In the paper we study a couple of knowledge-based multiagent algorithms. One particular algorithm is for a system consisting of agents that arrive one by one (in a non-deterministic order) to a resource center to rent (for a while) one of available desired resources. Available resources are passive, they form a cloud; each of the available resources is lent on demand if there is no race for this resource and returns to the cloud after use. Agents also form a cloud but leave the cloud immediately when they rent a desired resource. The problem is to design a knowledge-based multiagent algorithm, which allows each arriving agent eventually to rent some of desired resources (without race for these resources).


Author(s):  
Rafael C. Cardoso ◽  
Louise A. Dennis ◽  
Michael Fisher
Keyword(s):  

Author(s):  
Jan Sudeikat ◽  
Lars Braubach ◽  
Alexander Pokahr ◽  
Winfried Lamersdorf ◽  
Wolfgang Renz
Keyword(s):  

2016 ◽  
Vol 17 (2) ◽  
pp. 109-123 ◽  
Author(s):  
Aicha Ben Mekki ◽  
Jihène Tounsi ◽  
Lamjed Ben Said

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