Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for a given coordination graph is therefore a central subroutine in cooperative multi-agent reinforcement learning (MARL). Much research in MARL focuses on how to gradually update the parameters of the coordination graph, whilst leaving the solving of the coordination graph up to a known typically exact and generic subroutine. However, exact methods { e.g., Variable Elimination { do not scale well, and generic methods do not exploit the MARL setting of gradually updating a coordination graph and recomputing the joint action to select. In this paper, we examine what happens if we use a heuristic method, i.e., local search, to select joint actions in MARL, and whether we can use outcome of this local search from a previous time-step to speed up and improve local search. We show empirically that by using local search, we can scale up to many agents and complex coordination graphs, and that by reusing joint actions from the previous time-step to initialise local search, we can both improve the quality of the joint actions found and the speed with which these joint actions are found.
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Accurate modeling of end-users’ decision-making behavior is crucial for validating demand response (DR) policies. However, existing models usually represent the decision-making behavior as an optimization problem, neglecting the impact of human psychology on decisions. In this paper, we propose a Belief-Desire-Intention (BDI) agent model to model end-users’ decision-making under DR. This model has the ability to perceive environmental information, generate different power scheduling plans, and make decisions that align with its own interests. The key modeling capabilities of the proposed model have been validated in a household end-user with flexible loads
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Waste separation at companies is considered a priority to achieve a circular and sustainable society. This research explores behaviour change poli-cies for separating the organic fraction of municipal solid waste (OFMSW) at Small and Medium Enterprises (SMEs), particularly in cities. At SMEs, co-work-ers are responsible for waste disposal. Therefore, their behavioural intention to-wards pro-environmental action plays a major role. In this study, we have used agent-based modelling and simulation to explore the waste behaviour of the ac-tors in the system. The models were co-created in participatory workshops, sur-veys and interviews with stakeholders, domain experts and relevant actors. Ad-ditionally, we co-created and tested practical social and technical interventions with the model. We used the collaborative modelling method Lange reported to conceptualise, implement, test and validate the models. Five policies that affect waste separation behaviour were included in the model. The model and simula-tion results were cross-validated with the help of a literature study. The results were validated through experts and historical data to sketch a generalisable idea of networks with similar characteristics. These results indicate that combinations of behaviour profiles and certain policy interventions correlate with waste sepa-ration rates. In addition, individual waste separation policies are often limitedly capable of changing the behaviour in the system. The study also shows that the intention of co-workers concerning environmental behaviour can significantly impact waste separation rates. Future work will include the role of households, policies supporting separating multiple waste types, and the effect of waste sep-aration on various R-strategies.
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Presented at the International Conference on Flexible Automation and Intelligent Manufacturing (FAIM) 23 - 26 June 2015 at the University of Wolverhampton, UK. Authorsupplied abstract: ABSTRACT Customized, on-demand manufacturing is growing through the use of new paradigms and technologies. Agile Manufacturing, cyber physical systems, and reconfigurable systems are examples of these changes. To provide high-mix, low-volume production there is a need for dynamic behaviour and manufacturing machines that can handle a large variety of services. Manufacturing systems can be made more dynamic by using agent-based technology. However, the reconfigurable aspect of these machines has yet to be explored. This paper investigates the possibility to adapt, i.e., reconfigure the hardware of manufacturing machines based on the current manufacturing demand. Using a simulation for a working agent-based platform with reconfiguration capabilities, this paper validates the effects of reconfigurable hardware to change capacity when producing a variety of products in a dynamic production environment. The paper continues to investigate required strategies to effectively use reconfiguration and counter the effects of disturbances that are likely to happen in such systems.
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Insider ethnographic analysis is used to analyze change processes in an engineering department. Distributed leadership theory is used as conceptual framework.
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For me the concept of the teacher educator as a agent of social change, implies that teacher educators should be focused on stimulating change and improvement in teacher education, schools and society. That focus should not only shape our teaching of student teachers, but also our research activities. This has implications for the research projects that we undertake. When research by teacher educators intends to contribute to change and improvement of practices in teacher education, schools and society, our research projects need to be understood as interventions. In the design of PhD or other research projects, not only academic requirements regarding validity should be taken into also account but also criteria that contribute to interventions and change in universities, schools and society.Effective change is a collective challenge, which requires likeminded colleagues.
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In recent years, there have been significant changes in weather patterns, mainly caused by sharp increases in temperature, increases in carbon dioxide, and fluctuations in precipitation levels, negatively impacting agricultural production. Agricultural systems are characterized by being vulnerable to the variation of biophysical and socioeconomic factors involved in the development of agricultural activities. Agent-based models (ABMs) enable the study, analysis, and management of ecosystems through their ability to represent networks and their spatial nature. In this research, an ABM is developed to evaluate the behavior and determine the vulnerability in the sugarcane agricultural system; allowing the capitalization of knowledge through characteristics such as social ability and autonomy of the modeled agents through fuzzy logic and system dynamics. The methodol-ogy used includes information networks for a dynamic assessment of agricultural risk modeled by time series, system dynamics, uncertain parameters, and experience; which are developed in three stages: vulnerability indicators, crop vulnerability, and total system vulnerability. The development of ABM, a greater impact on the environmental contingency is noted due to the increase in greenhouse gas emissions and the exponential increase in extreme meteorological phenomena threatening the cultivation of sugarcane, making the agricultural sector more vulnerable and reducing the yield of the harvest.
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From the article: "To extend the lifetime of products, an agent is connected to the product. This agent has several roles. It depends on the phase of the lifecycle what these roles will be. One of the roles in the usage or recycling phase is to negotiate for buying spare parts in case a part of the product is broken. The same agent can also decide to offer spare parts to other agents to reuse working parts of a broken product. To accomplish this idea, a marketplace for agents has to be set up, where the auctions can take place. To support this concept, blockchain technology has been used. Blockchains are a new type of technology, known from bitcoins, but there are other cases where blockchains can be used. Blockchain is known for its decentralisation, transparency and for making trustful transactions. In this paper the working of different types of blockchains will be briefly explained and determined if they can be useful for online auctions by agents. A prototype of the marketplace using blockchains has been built."
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This chapter presents the currently not established and identifies design requirements for new systems to address this challenge and provide directions for possible improvement. As a result, this chapter introduces the concept of SamenMarkt®, a participatory system in which multi-agent system technology enables distributed price negotiation, distribution and communication between producers, retailers and consumers.
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To meet the care needs of the rapidly ageing patient populations, the cultivation of a compassionate patient-centred healthcare culture has become central in the value-based healthcare discourse. A participatory music practice, ‘Meaningful Music in Healthcare’ employs a person-centred approach to music-making in Dutch hospitals. A grounded theory analysis on ethnographically collected data suggests that music-making serves as a social change agent and cultural resource for catalysing compassionate contact between healthcare professionals and patients. Processes of experiential growth and shared values in music-making and healthcare help to enrich care relationships and allow the emotional dimension of nurses’ professional performance to be explored.
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