A Formal Model of Communication and Context Awareness in Multiagent Systems

MASQ (Multi-Agent Systems based on Quadrants) is a generic metamodel that integrates many of the concepts issued from the research in the multiagent systems field by defining four perspectives over agent-based interaction according to two axes: internal/external and individual/collective. The aim of this paper is to provide a formal description of MASQ by specifying clear relations between the basic elements of the four quadrants and by analysing the dynamics of a multi-agent system through its transitions and through the classical mind cycle. The proposed formal model has been designed as a theoretical framework and therefore the specifications of many components of a multi-agent system such as the internal architecture of minds, the casual laws of environments or the social laws in organizations and institutions are intentionally left generic to allow for many further concretizations.

Assalamu’alaikum Wr. Wb. and Greetings.I am pleased and honored to welcome you at the First International Conference on Computer Science and Applied Mathematic (ICCSAM 2018), which was held this year by AMIK and STIKOM Tunas Bangsa Pematangsiantar in collaboration with the Indonesian Computer and Information Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS) and Bank Muamalat. As Chair of the Foundation, I would like to convey a greeting Welcome to Parapat City Lake Toba to presenters from various countries and especially those I respect for the presence of scientists in the field of Computer and Mathematical Sciences and industry practitioners in the 2018 ICCSAM event.I see that this activity is designed to enhance the exchange of knowledge and new discoveries in computer science and mathematics and related fields in industry. I hope that scientists in the field of computer science and mathematics and those who work in the industry can share knowledge and work together as a team that has mutual relations with each other. I am very pleased to say that the theme of this conference, “Advancing Computability Innovation” is very much in line with the objectives of AMIK and STIKOM conferences and missions, namely “to become a Science and Technology based Study Program that meets industrial needs and functions as a research center in Information Data Science. The conference was held in response to output and aoutcame which had a significant contribution in the field of computer science and mathematics as an inseparable unit of science towards the development of local and global industries. It is our happiness and honor to welcome distinguished professors present to convey their expertise at this conference.I hope this meeting will enable the development of productive dialogue between participants from various countries. They also provide invaluable opportunities for networking among participants, institutions and industries. I also hope that diversity in these fields can reveal more opportunities for researchers and practitioners from all over the world to start a lot of research related to the industry in the future.I would like to congratulate AMIK and STIKOM Tunas Bangsa for starting this conference with a synergistic contribution from dedicated partners namely the USU Faculty of Mathematics and Natural Sciences, USU’s Faculty of Computer and Information Technology, the Indonesian Computer and Informatics Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS), Bank Muamalat, Malaysia Pahang University (UMP), University of Essex, United Kingdom, Ankara, Turkey and Institute of Applied Mathematics Middle East Technical University to all delegates for their full support, cooperation and contribution to the 2018 ICCSAM. I also want to thank the Organizing Committee for their perseverance and extraordinary efforts. Various sponsors are also rewarded for their contributions. I really hope that all participants will get a pleasant stay here at NIAGARA HOTEL and bring back unforgettable experiences and valuable knowledge from this conference.Thanks.H. Ahmad Ridwansyah Putra

A central problem in the study of autonomous cooperating systems is that of how to establish mechanisms for controlling the interactions between different parts (which are called agents) of the system. One way to integrate such mechanisms into a multi-agent system is to exploit the technique of cooperation or negotiation protocols. In a protocol we distinguish to essential layers: the communication layer specifying the possible flow of messages between different agents, and the decision layer, which controls the selection of a message (speech-act) that the agent sends in a specific situation. In this report we first give a short introduction of our agent model InteRRap which provides the basis for the modeling of the different scenarios considered in the AKA-Mod project at the DFKI. The techniques we will discuss in the following are located in the plan based component and in the cooperation component of this model. The domain of application is the MARS scenario (Modeling a Multi-Agent Scenario for Shipping Companies) which implements a group of shipping companies whose goal it is to deliver a set of dynamically given orders, satisfying a set of given time and/or cost constraints. The complexity of the orders may exceed the capacities of a single company. Therefore, cooperation between companies is required in order to achieve the goal in a satisfactory way. This domain is of considerable interest for studies with economical background as well as for research projects. We give a short summary of results from economical studies that are concerned with the real-world situation in Germany in the transportation domain. They show the need for the development of new techniques from the field of computer science to tackle the problems therein. Then, an overview on related research is presented. Two approaches are discussed in more detail: the first one being based on OR-techniques and a second one being based on the concept of partial intelligent agents attempting to integrate techniques from OR and DAI. Both approaches are concerned with the situation in a single company. However, our purpose to handle the case of distributed shipping companies requires additional mechanisms, e.g. to cope with the problems of task allocation and task decomposition in multi-agent systems. Mechanisms for distributed task decomposition and task allocation processes in multi-agent systems belong to the core of our studies. Therefore, we will first discuss techniques for these problems in a general setting and then describe their implementations in the MARS system. In this description, particular emphasis is placed on the cooperation within a shipping company. Here, one company agent has to allocate a set of orders its truck agents. The truck agents support the company agents by giving cost estimations based on their route planning facility. Thus, this procedure provides the basis for the decisions of the company agents and is discussed in very detail. Finally, we present results from a series of benchmark tests. The test sets have also been run with OR-implementations and thus, give us the opportunity to compare our implementation against these approaches.

The international scientific and practical journal “Software products and systems” was organized in 1988 on the initiative of the General Director of the NGO “Centerprogramsystem” prof. V. P. Tikhomirov (Tver) and V. M. Silina (Moscow), head of the Main editorial office of the international journal “Problems of management theory and practice”. In the period from 1988 to 2018, the editor-in-chief of the journal was academician S. V. Yemelyanov. Since 2020, the international editorial Board, which includes well-known scientists in the field of information technologies of the Russian Federation, Belarus, Ukraine, Azerbaijan, Germany, Finland, Mexico, Vietnam and other countries, is headed by academician G. I. Savin. Associate members of the editorial Board are the national research University “MEI” (Moscow), the technological Institute of the southern Federal University (Taganrog), TvSTU and the research Institute “Centerprogramsystem”. The journal is reviewed in the bibliographic databases of RSCI, CrossRef, and is included in the List of leading peerreviewed journals and publications recommended by the higher attestation Commission of the Russian Federation for publication of research results in the defense of candidate and doctoral theses in the fields of computer Science, computer engineering and management (05.13.XX). The journal publishes the results of original research in the field of information technologies, applied artificial intelligence systems, including the development of databases and knowledge bases, expert and training systems, decision support systems and image recognition, multiagent systems, data mining systems, neural networks, robots, and telecommunications systems. However, the subject area of research is not limited. The magazine “Software products and systems” regularly acts as an information sponsor for international and national scientific and technical events in the field of information technology and artificial intelligence.

In the mobile learning context, it is helpful to consider context awareness and adaptivity as two sides of the same coin. The purpose of the adaptivity and context awareness is to better support a variety of learners, given that they may have very different skills and motivations to learn in varying contexts. The recent research on adaptivity and context awareness has turned towards supporting pervasive environments and this is coupled with the increasing trend in seeing learning environments from an informal learning perspective. In this paper are presented experiences of developing an adaptive and context aware mobile learning system, with examples of other systems underlining the development towards supporting pervasive learning environments. We then consider approaches for the future development of systems supporting pervasive learning environments.

In this paper, the paradigm of rationality is examined from the point of view of designing, and possibly implementing, agents endowed with the capacity to interact in a multi-agent environment. The work that will be presented originates from a cross-fertilization between the fields of social simulation and Multi-Agent Systems (MAS) research. In the MAS field, models of intelligent agents in a multi-agent context have been formalized and implemented. The question then arises as to whether the model of rational agents may contribute fruitfully to construct and implement multi-agents systems.

Artificial Intelligence (AI) has become an increasingly important and popular topic not just within the field of Computer Science but also the world at large. One of the current challenges in the field of AI is multi-agent planning, of which Swarm Intelligence (SI) is a possible solution drawing from natural systems as an inspiration. While individual agents in a flock or swarm are mostly simplistic and similar in nature, together they can develop extremely complex and emergent behaviour. A very well-known implementation of Swarm Intelligence is “Boids”. Bird like objects first introduced by Craig Reynolds in 1987 that flock and move together based on the 3 core steering behaviours of Separation, Alignment, and Cohesion. However, even current work on boids tend to let individual agents be “reactive” in nature, giving instructions to themselves based on their current state and their observations of the environment around them. This project aims to study how adding an additional layer on top of traditional flocking behaviour, by making agents “socially aware” through actively sharing opinions with each other, will affect the dynamics of a flock.

Digitalization and the use of autonomous systems challenge companies in new ways, particularly concerning the automatic distribution of tasks. Various approaches are being discussed in research, specifically in the field of multi-agent systems. However, there does not seem to be a universally applicable and generally accepted solution. Due to the multitude of different approaches and the associated challenges, traceability is of particular interest and requires further analysis. This paper reviews the traceability of different negotiation-based approaches for task allocation in multi-agent systems. We conducted a structured literature review and implemented a prototype using an existing workflow engine for the approach we identified as most suitable, applying a weighted scoring model. The evaluation of the implemented demonstrator, performed both with and without restarting negotiations, indicates that a traceable distribution of tasks with a negotiation mechanism is feasible.

Route-planning is a perplexing problem in the field of computer science. Finding computationally viable solutions to route-planning is a challenging task. Various techniques have been devised to solve this problem; however, there is a trade-off in these techniques between computational complexity and accuracy. One paradigm defined in artificial intelligence which can contribute to this problem’s solution is a multi-agent system, in which a group of agents work together to achieve a common goal. These agents require a robust mechanism for coordination and information exchange in order to achieve this goal. When applied to route-planning, these agents interact to compute the optimal path based on distance, speed, and a variety of environmental factors that may impact travelling time. The consideration of these factors allows a solution generated by the system to be applicable to real world sitations. In this work, a hybrid model is proposed which utilizes a multi-agent system to compute travelling time for a given route. This system utilizes a Bayesian network to model interdependencies which exist between environmental factors. In order to illustrate the potential effectiveness of the proposed model, several case studies from the state of Alabama are presented.

Despite great effort in research and teaching as well as in raising women’s quotas in the public sector and in enterprises, a gender gap in computer science can still be observed. The reasons are manifold, including the lack of interest of girls because of existing stereotypes of male nerds, misconceptions in the field of computer science, and concrete differences in students’ self-concept and performance. Girls do not choose schools or studies in the field of computer science because working on computers or coding is unattractive to them. Research shows poorer performance, missing interest, and lower self-concept for girls in secondary computing education as well as a high dropout rate of female students in computer science courses at the bachelor’s level. Software development exams contribute to those high dropout rates, and women often choose a different subject or even stop their university education altogether. This leads to fewer female employees in the field of computer science, and this situation calls for special measures at several levels. The current paper provides an overview of the initiatives of our university that aim to address several aspects of the gender gap. The programs offered aim to (1) increase interest in computer science and recruit (highly) gifted girls for our talent programs, (2) recruit and support female bachelor’s and master’s students in computer science, and (3) redesign programming courses and teaching materials to reduce the gender gap in performance and support, especially for female students. This study also describes a cyber tutoring program in which highly gifted girls between 13 and 16 years collaborate with and are supervised by female role models in higher positions in STEM. The evaluation results gained in the first year of this case study are promising and suggest that the extension and further development of the program would be advantageous.

Improving autonomous agents' awareness has aroused a great deal of interests in agent research. The objective is to formulate an approach that provides advanced awareness capabilities in the agents' behaviour. In this paper, we explore the techniques proposed in the literature that have been adopted to enable agents' awareness which are Active Perception (AP), Situation Awareness (SA) and Context Awareness (CA). In addition, we illustrate the possible integration of the techniques' core phases with a multi-agent system (MAS). In doing so, we propose an approach to Situation Awareness for a decentralized MAS environment which is abbreviated as SAMAS. The approach assists in the agents' decision-making process through decomposing the context of an event's situations. Consequently, the SAMAS approach provides human-based assessments to the agents' performance. The assessments are fed back to the agents' to maintain the active perception of their actions. The paper contributes an independent SA approach considered from the perspective of MAS in a dynamic environment.

The main challenge that artificial intelligence research is facing nowadays is how to guarantee the development of responsible technology. And, in particular, how to guarantee that autonomy is responsible. The social fears on the actions taken by AI can only be appeased by providing ethical certification and transparency of systems. (See for instance the Barcelona declaration https://www.iiia.csic.es/barcelonadeclaration/) However, this is certainly not an easy task. As we very well know in the multiagent systems field, the prediction accuracy of system outcomes has limits as multiagent systems are actually examples of complex systems. And AI will be social, there will be thousands of AI systems interacting among themselves and with a multitude of humans; AI will necessarily be multiagent. Although we cannot provide complete guarantees on outcomes, we must be able to define with accuracy what autonomous behaviour is acceptable (ethical), to provide repair methods for anomalous behaviour and to explain the rationale of AI decisions. Ideally, we should be able to guarantee responsible behaviour of individual AI systems by construction. I understand by an ethical AI system one that is capable of deciding what are the most convenient norms, abide by them and make them evolve and adapt. The area of multiagent systems has developed a number of theoretical and practical tools that properly combined can provide a path to develop such systems, that is, provide means to build ethical-by-construction systems: agreement technologies to decide on acceptable ethical behaviour, normative frameworks to represent and reason on ethics, and electronic institutions to operationalise ethical interactions. Along my career, I have contributed with tools on these three areas. In this keynote, I will describe a methodology to support their combination that incorporates some new ideas from law, and organisational theory.

When seeking solutions to current problems in the field of computer science – and other fields – we encounter situations where traditional approaches no longer bring the desired results. Our cognitive skills also limit the implementation of reliable mental simulation within the basic set of relations. The world around us is becoming more complex and mutually interdependent, and this is reflected in the demands on computer support. Thus, in today‘s education and science in the field of computer science and all other disciplines and areas of life need to address the issue of the paradigm shift, which is generally accepted by experts. The goal of the paper is to present the systems thinking that facilitates and extends the understanding of the world through relations and linkages. Moreover, the paper introduces the essence of systems thinking and the possibilities to achieve mental a shift toward systems thinking skills. At the same time, the link between systems thinking and functional literacy is presented. We adopted the “Bathtub Test” from the variety of systems thinking tests that allow people to assess the understanding of basic systemic concepts, in order to assess the level of systems thinking. University students (potential information managers) were the examined subjects of the examination of systems thinking that was conducted over a longer time period and whose aim was to determine the status of systems thinking. . The paper demonstrates that some pedagogical concepts and activities, in our case the subject

A New Approach In Learning For Intelligent Multi Agent Systems

In the field of multi-agent systems, a lot of attention has been focused lately on investigating various architectures and methodologies that promote effective organization and coordination within large-scale, complex, distributed systems. Specifically, the interest is in developing approaches that can be implemented within multi-agent systems to produce desirable emergent behavior that coordinates individual actors in a system competing for resources such as bandwidth, computing power, and data. This extended abstract outlines polymorphic self-* agents that evolve a core set of roles and behavior based on environmental cues. The agents adapt these roles based on the changing demands of the environment. The design combines strategies from game theory, stigmergy, and other biologically inspired models.