The Belief-Desire-Intention Architecture of Sincere Software Agent Environment

Software agent is autonomous technology that helps a lot the human being in performing the task. The capability of agent to take actions on behalf of human is one of the reasons why researchers or developers of autonomous systems adapt the human characteristics either in the form of physical or behaviours. Sincerity is one of ethical human behaviour that can be instilled in software agent environment system. To instil the ethical behaviour such as sincerity, the belief-desire-intention (BDI) architecture should be designed. This paper explains the BDI architecture for sincere software agent environment system during performing task.

Autonomous Agents in 3D Crowd Simulation Through BDI Architecture

Agent based simulation (ABS) is a paradigm to modelling systems included of autonomous and interacting agents. ABS has been tremendous growth and used by researchers in the social sciences to study socio-environmental complex systems. To date, various platforms have been introduced for agent-based social simulation. They are rule based in any logic, python based in SPADE and etc. Although those platforms have been introduced, there is still an insufficient to develop a crowd simulation in 3D platform. Having a 3D platform is needed to enabling the crowd simulation for training purposes. However, the current tools and platform still lack features to develop and simulate autonomous agents in the 3D world. This paper introduced a BDI plug in at Unity3D for crowd simulation. BDI is an intelligent agent architecture and it is able to develop autonomous agents in crowd environment. In this paper, we present the BDI plug with a case study of Australia bush fire and discuss a method to support autonomous agents' development in 3D crowd simulation. The tool allows the modeller to develop autonomous agents in 3D world by taking the advantages of Unity3D.

Empowering Communications in Vehicular Networks with an Intelligent Blockchain-Based Solution

Blockchains have emerged over time as a reliable and secure way to record transactions in an immutable manner in a wide range of application domains. However, current related solutions are not yet capable of appropriately checking the authenticity of data when their volumes are huge. They are not also capable of updating Blockchain data blocks and synchronizing them within reasonable timeframes. This is the case within the specific context of Blockchain vehicular networks, where these solutions are commonly cumbersome when attempting to add new vehicles to the network. In order to address these problems, we propose in this paper a new Blockchain-based solution that intelligently implement selective communication and collaborative endorsement approaches to reduce communications between vehicles. Our solution represents the vehicles of the Blockchain as intelligent software agents with a Belief–Desire–Intention (BDI) architecture. Furthermore, we propose an approach based on multi-endorsement levels to exchange data of varying sensitive categories. This approach, which is based on endorsing scores, is also used to shorten the admission of new vehicles into the Blockchain. We run simulations using the Hyperledger Fabric Blockchain tool. Results show the efficiency of our solution in reducing the processing times of transactions within two different scenarios.

BDI Agent Architectures: A Survey

The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach.

Designing emotional BDI agents: good practices and open questions

Intelligent agents built on the basis of the BDI (belief–desire–intention) architecture are known as BDI agents. Currently, due to the increasing importance given to the affective capacities, they have evolved giving way to the BDI emotional agents. These agents are generally characterized by affective states such as emotions, mood or personality but sometimes also by affective capacities such as empathy or emotional regulation. In the paper, a review of the most relevant proposals to include emotional aspects in the design of BDI agents is presented. Both BDI formalizations and BDI architecture extensions are covered. From the review, common findings and good practices modeling affect, empathy and regulatory capacities in BDI agents, are extracted. In spite of the great advance in the area several, open questions remain and are also discussed in the paper.

Elimination of network intrusions via a resource oriented BDI architecture

We propose a resource-oriented architecture of a rational agent for a network intrusion detection system. This architecture describes the behavior of a rational agent after detection of unwanted network activities. We describe the creation of countermeasures to ward off detected threats. Examples are created based on the proposed architecture, describing the process during a rational agent detection. We have described these examples by linear BDI logic behavioral formulæ, that have been proven by Gentzen sequent calculus.