Smart Agent and it’s effect on Artificial Intelligence : A Review Study

Current networking technologies, as well as the ready availability of large quantities of data and knowledge on the Internet-based Infosphere, offer tremendous opportunities for providing more abundant and reliable information to decision makers and decision support systems. The use of the Internet has increased at a breakneck pace. Some prevailing features of the Infosphere, however, have hindered successful use of the Internet by humans or decision support machine systems. To begin with, the information available on the internet is disorganized, multi-modal, and spread around the globe on server pages. Second, every day, the number and variety of data sources and services grows dramatically. In addition, the availability, type, and dependability of information services are all changing all the time. Third, the same piece of knowledge can be obtained from a number of different sources. Fourth, due to the complex existence of information sources and possible information updating and maintenance issues, information is vague and probably incorrect. As a result, collecting, filtering, evaluating, and using information in problem solving is becoming increasingly difficult for a human or computer device. As a consequence, identifying information sources, accessing, filtering, and incorporating data in support of decision-making, as well as managing information retrieval and problem-solving efforts of information sources and decision-making processes, has become a critical challenge. To fix this issue, the idea of "Intelligent Software Agents" has been suggested. Although a precise definition of an intelligent agent is still a work in progress, the current working definition is that Intelligent Software Agents are programs that act on behalf of their human users to perform laborious information gathering tasks such as locating and accessing information from various on-line information sources, resolving inconsistencies in the retrieved information, filtering out irrelevant data.

Multi-Agent System Development and Application for Supply Chain Management Tasks

In today’s dynamically changing environment, we need to be able to respond in a timely manner to changes in supply chain processes. Software agents are successfully used in supply chain management tasks for a variety of purposes. The behaviour of agents is determined by the purpose of their development, and the effectiveness of the use of agents is considered in accordance with the purpose of their development. The paper presents research on the development of a multi-agent system for supply chain management, focusing on the steps of developing a multi-agent system. The choice of each algorithm for agents is analysed and argued. The application of the developed multi-agent system for supply chain management is also described in the paper. The efficiency of application of the developed multi-agent system is presented as well.

Development of the blockchain architecture of the Industrial Internet of Things system of the enterprise

The development of the digital economy in the modern world requires solving the issue of security of Industrial Internet of Things (IIoT) applications. A large number of distributed, network-based, IIoT devices managed by intelligent programs (software agents) require protection. A successful attack on any IIoT device will lead to hacking of the IIoT application and to large financial losses, as well as to the termination of the IIoT application, therefore, the research topic is relevant. The purpose of this article is to radically solve the security problem of the IIoT application by developing a blockchain architecture of the application. The authors were tasked with investigating all aspects of the blockchain system that ensure the security of IIoT application devices. The peculiarity of the blockchain system is that its participants are software agents that control the application devices. As a result of the research, the concept of the blockchain architecture of the IIoT application is proposed. He mechanisms of consensus of intelligent programs of IIoT devices as equal active participants of the blockchain network are investigated. The consensus mechanism and the cryptographic system of the distributed registry of the blockchain network increase the information security of the IIoT application. The synergistic effect of the blockchain system and intelligent systems of software agents of IIoT application devices significantly increases the efficiency of the solution. Intelligent systems of software agents and IIoT applications are effectively trained on the blockchain platform, and as a result, we get a decentralized supercomputer in the form of a blockchain system.

AI-Based Chatbot to Solve Modern-Day Enterprise Business Problems

Communicating with employees through forums and emails has become an increasingly popular way for many multinational companies to provide human resource services in real time. Today, employee chat service agents are often replaced by conversational software agents or chatbots. These systems are designed to communicate with human users through natural language, generally based on artificial intelligence (AI). Time and cost saving opportunities have led to the widespread deployment of AI-based chatbots. Chatbots are one of the most basic and popular examples of human-computer intelligent interaction (HCI). Designed to convincingly simulate the way humans behave as dialogue partners. In the proposed system, we propose a chat robot that can dynamically respond to employee human resource queries. The proposed HR system is based on the Microsoft Cognitive Services chatbot. This Microsoft Teams-based platform provides a broad foundation of intelligence and is trained based on various data sets provided by the organization's HR.

Diversification of Legislation Editing Open Software (LEOS) Using Software Agents—Transforming Parliamentary Control of the Hellenic Parliament into Big Open Legal Data

The accessibility and reuse of legal data is paramount for promoting transparency, accountability and, ultimately, trust towards governance institutions. The aggregation of structured and semi-structured legal data inevitably leads to the big data realm and a series of challenges for the generation, handling, and analysis of large datasets. When it comes to data generation, LEOS represents a legal informatics tool that is maturing quickly. Now in its third release, it effectively supports the drafting of legal documents using Akoma Ntoso compatible schemes. However, the tool, originally developed for cooperative legislative drafting, can be repurposed to draft parliamentary control documents. This is achieved through the use of actor-oriented software components, referred to as software agents, which enable system interoperability by interlinking the text editing system with parliamentary control datasets. A validated corpus of written questions from the Hellenic Parliament is used to evaluate the feasibility of the endeavour, and the feasibility of using it as an authoring tool for written parliamentary questions and generation of standardised, open, legislative data. Systemic integration not only proves the tool’s versatility, but also opens up new grounds in interoperability between formerly unrelated legal systems and data sources.

Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS can create human-like artificial emotions during interactions with their environment. We describe the underlying mechanisms for this. The control system also captures its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, stores these artificial emotions. ARTEMIS then utilizes current and stored emotions to adapt decision making and planning processes. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes their orders and instructions. The environment of this user assistant consists of several other autonomous agents that offer their services. The execution of a user’s orders requires interactions of the user assistant with these autonomous service agents. These interactions lead to the creation of artificial emotions within the user assistant. The first experiments show that it is possible to realize an autonomous user assistant with plausible artificial emotions with ARTEMIS and record these artificial emotions in its Agent Knowledge Graph. The results also show that captured emotions support successful planning and decision making in complex dynamic environments. The user assistant with emotions surpasses an emotionless version of the user assistant.

Using Semantic Technology To Model Persona For Adaptable Agents

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. Although numerous applications based on these types of models are already available, the options for modelling and calibration of the agents as goal-oriented individuals are either simplified to aggregated parameters or associated with overly complex and opaque implementation details. This makes it difficult to reuse available simulation models. In this paper, we demonstrate how the combination of persona models together with semantic methods can be applied to achieve a well-structured agent model that allows for improved reusability.