Convergence of employers’ and students’ expectations in the educational environment of the agricultural university

In the digital age, a modern university is becoming a driver for the development of complex multi-agent ecosystems and a supplier of a new type of human resources, characterized not only by intellectual potential and high qualifications but also by such qualities in demand in the labor market as creativity, critical thinking, the need for continuous learning and “agency”, which is understood as the ability to self-organize and proactivity [1]. The education system and universities themselves face challenges that force us to turn to the once-actual ideas of integration and convergence, which can fulfill the increased need to achieve synergy effects and multiplier indicators that contribute to achieving high ratings in a short time. It is convergent processes that lie at the heart of the developing communicative space of the university today, whose activities are based on the intersection of the interests and expectations of various actors, which are implemented on multi-agent platforms. At the same time, the opportunities that are opening up due to the rapid introduction of digital technologies require restructuring the space of interactions between subjects towards the formation of flexible forms, network models, alliances, virtual corporations, connecting clusters built on the principles of active cooperation, exchange of best practices and developments.

Efficient Performative Actions for E-Commerce Agents

The foundational features of multi-agent systems are communication and interaction with other agents. To achieve these features, agents have to transfer messages in the predefined format and semantics. The communication among these agents takes place with the help of ACL (Agent Communication Language). ACL is a predefined language for communication among agents that has been standardised by the FIPA (Foundation for Intelligent Physical Agent). FIPA-ACL defines different performatives for communication among the agents. These performatives are generic, and it becomes computationally expensive to use them for a specific domain like e-commerce. These performatives do not define the exact meaning of communication for any specific domain like e-commerce. In the present research, we introduced new performatives specifically for e-commerce domain. Our designed performatives are based on FIPA-ACL so that they can still support communication within diverse agent platforms. The proposed performatives are helpful in modelling e-commerce negotiation protocol applications using the paradigm of multi-agent systems for efficient communication. For exact semantic interpretation of the proposed performatives, we also performed formal modelling of these performatives using BNF. The primary objective of our research was to provide the negotiation facility to agents, working in an e-commerce domain, in a succinct way to reduce the number of negotiation messages, time consumption and network overhead on the platform. We used an e-commerce based bidding case study among agents to demonstrate the efficiency of our approach. The results showed that there was a lot of reduction in total time required for the bidding process.

Programming Agents by Their Social Relationships: A Commitment-Based Approach

Multiagent systems can be seen as an approach to software engineering for the design and development of complex, distributed software. Generally speaking, multiagent systems provide two main abstractions for modularizing the software: the agents and the environment where agents operate. In this paper, we argue that also the social relationships among the agents should be expressed explicitly and become first-class objects both at design- and at development-time. In particular, we propose to represent social relationships as commitments that are reified as resources in the agents’ environment and can be directly manipulated by the agents via standard operations. We demonstrate that this view induces an agent programming schema that is substantially independent of the actual agent platform, provided that commitments are available as explained. The paper exemplifies the schema on two agent platforms, JADE and JaCaMo, where commitments are made available via the 2COMM library.

Multi-agent modeling and simulation of a stock market

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

Human-Like Agents for Repeated Negotiation

Virtual agents have been used as tools in negotiation—from acting as mediators to manifesting as full-fledged conversational partners. Virtual agents are a powerful tool for teaching negotiation skills, but require an accurate model of human behavior to perform well both as partners and teachers. The work proposed here aims to expand the current horizon of virtual negotiating agents to utilize human-like strategies. Further agents developed using this framework should be cognizant of the social factors influencing negotiation, including reputation effects and the implications of long-term repeated relationships. A roadmap of current efforts to develop agent platforms and future expansions is discussed.