Agent-oriented domain-specific language for the development of intelligentdistributed non-axiomatic reasoning agents

У дисертацији је представљен прототип агентског, домен-оријентисаног језика ALAS. Основни мотиви развоја ALAS језика су подршка дистрибуираном не-аксиоматском резоновању као и омогућавање интероперабилности и хетерогене мобилности Siebog агената јер је приликом анализе постојећих агентских домен-оријентисаних језика утврђено да ни један језик не подржава ове захтеве. Побољшање у односу на сличне постојеће агентске, домен-оријентисане језике огледа се и у програмским конструктима које нуди ALAS језик а чија је основна сврха писање концизних агената који се извршавају у специфичним доменима.U disertaciji je predstavljen prototip agentskog, domen-orijentisanog jezika ALAS. Osnovni motivi razvoja ALAS jezika su podrška distribuiranom ne-aksiomatskom rezonovanju kao i omogućavanje interoperabilnosti i heterogene mobilnosti Siebog agenata jer je prilikom analize postojećih agentskih domen-orijentisanih jezika utvrđeno da ni jedan jezik ne podržava ove zahteve. Poboljšanje u odnosu na slične postojeće agentske, domen-orijentisane jezike ogleda se i u programskim konstruktima koje nudi ALAS jezik a čija je osnovna svrha pisanje konciznih agenata koji se izvršavaju u specifičnim domenima.The dissertation presents the prototype of an agent-oriented, domainspecific language ALAS. The basic motives for the development of the ALAS language are support for distributed non-axiomatic reasoning, as well as enabling the interoperability and heterogeneous mobility of agents, because it is concluded by analysing existing agent-oriented, domainspecific languages, that there is no language that supports these requirements. The improvement compared to similar existing agentoriented, domain-specific languages are also reflected in program constructs offered by ALAS language, whose the main purpose is to enable writing the concise agents that are executed in specific domains

Applying semantic technologies to multi-agent models in the context of business simulations.

Agent-based simulations are an effective simulation technique that can flexibly be applied to real-world business problems. By integrating such simulations into business games, they become a widely accepted educational instrument in the context of business training. Not only can they be used to train standard behaviour in training scenarios but they can also be used for open experimentation to discover structure in complex contexts (e.g. complex adaptive systems) and to verify behaviours that have been predicted on the basis of theoretical considerations.Traditional modelling techniques are built on mathematical models consisting of differential or difference equations (e.g. the well-known system dynamics approach). However, individual behaviour is not visible in these equations. This problem is addressed by using software agents to simulate individuals and to model their actions in response to external stimuli.To be effective, business training tools have to provide sufficiently realistic models of real-world aspects. Ideally, system effects on a macroscopic level are caused by behaviour of system components on a more microscopic level. For instance, in modelling market mechanisms market participants can explicitly be modelled as agents with individual behaviour and personal goals. Agents can communicate and act on the basis of what they know and which communication acts they perform. The evolution of the market then depends on the actions of the participants directly and not on abstract mathematical expressions.Generally, agent-based modelling is a challenging task, when modelling knowledge and behaviour. With the rise of the so-called semantic web ontologies have become popular, allowing the representation of knowledge using standardised formal languages which can be made available to agents acting in a simulation. However, the combination of agent-based systems with ontologies has not yet been researched sufficiently, because both concepts (web ontology languages and agent oriented programming languages) have been developed independently and the link has not yet been built adequately.Using ontologies as a knowledge base allows access to powerful standardised inference engines that offer leverage for the decision process of the agent. Agents can then determine their actions in accordance with this knowledge. To model agents using ontologies creates a new perspective for multi-agent simulation scenarios as programming details are reduced and a separation of modelling aspects from coding details is promising as business simulation scenarios can be set up with a reduced development effort.This thesis focuses on how ontologies can be integrated utilising the agent framework Jadex. A basic architecture with layered ontologies and its integration into the belief-desire-intention (BDI) agent model is presented. The abstract level of the approach guarantees applicability to different simulation scenarios which can be modelled by creating appropriate ontologies. Examples are based upon the simulation of market mechanisms within the context of different industries. The approach is implemented in the integrated simulation environment AGADE which incorporates agent-based and semantic technologies. Simulations for different scenarios that model typical market scenarios are presented

Interactive Multiagent Adaptation of Individual Classification Models for Decision Support

An essential prerequisite for informed decision-making of intelligent agents is direct access to empirical knowledge for situation assessment. This contribution introduces an agent-oriented knowledge management framework for learning agents facing impediments in self-contained acquisition of classification models. The framework enables the emergence of dynamic knowledge networks among benevolent agents forming a community of practice in open multiagent systems. Agents in an advisee role are enabled to pinpoint learning impediments in terms of critical training cases and to engage in a goal-directed discourse with an advisor panel to overcome identified issues. The advisors provide arguments supporting and hence explaining those critical cases. Using such input as additional background knowledge, advisees can adapt their models in iterative relearning organized as a search through model space. An extensive empirical evaluation in two real-world domains validates the presented approach

Towards Our Common Digital Future. Flagship Report.

In the report “Towards Our Common Digital Future”, the WBGU makes it clear that sustainability strategies and concepts need to be fundamentally further developed in the age of digitalization. Only if digital change and the Transformation towards Sustainability are synchronized can we succeed in advancing climate and Earth-system protection and in making social progress in human development. Without formative political action, digital change will further accelerate resource and energy consumption, and exacerbate damage to the environment and the climate. It is therefore an urgent political task to create the conditions needed to place digitalization at the service of sustainable development

KINE[SIS]TEM'17 From Nature to Architectural Matter

Kine[SiS]tem – From Kinesis + System. Kinesis is a non-linear movement or activity of an organism in response to a stimulus. A system is a set of interacting and interdependent agents forming a complex whole, delineated by its spatial and temporal boundaries, influenced by its environment. How can architectural systems moderate the external environment to enhance comfort conditions in a simple, sustainable and smart way? This is the starting question for the Kine[SiS]tem’17 – From Nature to Architectural Matter International Conference. For decades, architectural design was developed despite (and not with) the climate, based on mechanical heating and cooling. Today, the argument for net zero energy buildings needs very effective strategies to reduce energy requirements. The challenge ahead requires design processes that are built upon consolidated knowledge, make use of advanced technologies and are inspired by nature. These design processes should lead to responsive smart systems that deliver the best performance in each specific design scenario. To control solar radiation is one key factor in low-energy thermal comfort. Computational-controlled sensor-based kinetic surfaces are one of the possible answers to control solar energy in an effective way, within the scope of contradictory objectives throughout the year.FC