4,469 research outputs found

    Web-Based Recommendation System for Smart Tourism: Multiagent Technology

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    The purpose of the study is to design and develop a recommended system based on agent and web technologies, which utilizes a hybrid recommendation filtering for the smart tourism industry. A hybrid recommendation system based on agent technology is designed by considering the online communication with other sectors in the tourism industry, such as the tourism supply chain, agency etc. However, online communication between the sectors via agents is designed and developed based on the contract net protocol. Furthermore, the design system is developed on the java agent development framework and implemented as a web application. Case study-based results considering two scenarios involving 100 customers illustrated that the proposed web application improves the rate of the recommendation for the customers. In the first scenario without disturbances, this rate was improved by 20% and the second scenario with disturbances yielded a 30% rate of acceptable recommendation. In addition, based on the second scenario, real time data communication on the system occurred, thus the proposed system supported real time data communication

    Design and implementation of a software agent platform applied in E-learning and course management

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    Text in English; Abstract: English and TurkishIncludes bibliographical references (leaves 86-89)xi, 115 leavesIn this thesis, we report an experience on constructing a software agent platform for development and implementation of software agent systems running with integrated e-learning and course management applications which are developed and running under different technologies. The proposed platform consists of an agent development framework namely JADE (Java Agent Development Environmet), a common database infrastructure serving to many different applications and the applications infrastructure running on different platforms. An example e-university application module which is an integrated course management software running on the proposed platform namely Course ON-LINE and an agent application running as an add-on utility to this application namely GAIA is explained in detail to demonstrate the use of the proposed application.Bu çalışmada farklı teknolojiler kullanılarak geliştirilen ve farklı platformlarda çalıştırılmakta olan ve tümleşik yapıdaki uzaktan eğtim ve ders yönetimi araçları uygulamalarla birlikte çalışabilecek yazılım etmen sistemlerinin geliştirilebilmesini sağlayan bir yazılım geliştirme ve çalıştırma ortamı inşa etme deneyimi aktarılmıştır. Önerilen ortam JADE (Java Agent Development Environmet), isimli bir etmen geliştirme aracı, etmen sistemleri dahil tüm uygulamaların ortak kullandıkları bir veritabanı altyapısı, ve farklı ortamlarda çalışan ve farklı teknolojilerle geliştirilmiş uygulamaların altyapısından oluşmaktadır. Önerilen ortamın kullanılışını göstermek için tümleşik ders web sayfaları yönetim aracı olan ve e-üniversite uygulamalarının bir parçası olan Course ON-LINE ve onunla birlikte çalışan bir yazılım etmeni uygulaması olan GAIA uygulamaları detaylıca sunulmuştur

    Self-organisation of mobile robots in large structure assembly using multi-agent systems

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    Competition between manufacturers in large structure assembly (LSA) is driven by the need to improve the adaptability and versatility of their manufacturing systems. The lack of these qualities in the currently used systems is caused by the dedicated nature of their fixtures and jigs. This has led to their underutilisation and costly changeover procedures. In addition to that, modern automation systems tend to be dedicated to very specific tasks. This means that such systems are highly specialised and can reach obsolescence once there is a substantial change in production requirements. In this doctoral thesis, a dynamic system consisting of mobile robots is proposed to overcome those limitations. As a first knowledge contribution in this doctoral thesis, it is investigated under which conditions using mobile robots instead of the traditional, fixed automation systems in LSA can be advantageous. In this context, dynamic systems are expected to be more versatile and adaptive than fixed systems. Unlike traditional, dedicated automation systems, they are not constrained to gantry rails or fixed to the floor. This results in an expanded working envelope and consequently the ability to reach more workstations. Furthermore, if a product is large enough, the manufacturer can choose how many mobile robots to deploy around it. Accordingly, it was shown that the ability to balance work rates on products and consequently meet their due times is improved. For the second knowledge contribution, two fundamentally different decision-making models for controlling mobile agents in the complex scheduling problem are investigated. This is done to investigate ways of taking full advantage from the potential benefits of applying mobile robots. It is found that existing models from related academic literature are not suited for the given problem. Therefore, two new models had to be proposed for this purpose. It was plausible to use an agent-based approach for self-organisation. This is because similarly to agents, mobile robots can perform independently of one-another; and have limited perception and communication abilities. Finally, through a comparison study, scenarios are identified where either model is better to use. In agreement with much of the established literature in the field, the models are shown to exhibit the common advantages and disadvantages of their respective architecture types. Considering that the enabling technologies are nearing sufficient maturity for deploying mobile robots in LSA, it is concluded that this approach can have several advantages. Firstly, the granularity and freedom of movement enables much more control over product completion times. Secondly, the increased working envelope enables higher utilisation of manufacturing resources. In the context of LSA, this is a considerable challenge because products take a very long time to get loaded and unloaded from workstations. However, if the product flow is steady, there are rare disruptions and rare production changes, fixed automation systems have an advantage due to requiring much less time (if any) for moving and localising. Therefore, mobile systems become more preferred to fixed systems in environments where there is an increasing frequency of disruptions and changes in production requirements. The validation of agent-based self-organisation models for mobile robots in LSA confirms the expectations based on existing literature. Also, it reveals that with relatively low amounts of spare capacity (5%) in the manufacturing systems, there is little need for sophisticated models. The value of optimised models becomes apparent when spare capacity approaches 0% (or even negative values) and there is less room for inefficiencies in scheduling

    The e-revolution and post-compulsory education: using e-business models to deliver quality education

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    The best practices of e-business are revolutionising not just technology itself but the whole process through which services are provided; and from which important lessons can be learnt by post-compulsory educational institutions. This book aims to move debates about ICT and higher education beyond a simple focus on e-learning by considering the provision of post-compulsory education as a whole. It considers what we mean by e-business, why e-business approaches are relevant to universities and colleges and the key issues this raises for post-secondary education

    Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization

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    On top of Smart Grid technologies and new market mechanism design, the further deregulation of retail electricity market at distribution level will play a important role in promoting energy system transformation in a socioeconomic way. In today’s retail electricity market, customers have very limited ”energy choice,” or freedom to choose different types of energy services. Although the installation of distributed energy resources (DERs) has become prevalent in many regions, most customers and prosumers who have local energy generation and possible surplus can still only choose to trade with utility companies.They either purchase energy from or sell energy surplus back to the utilities directly while suffering from some price gap. The key to providing more energy trading freedom and open innovation in the retail electricity market is to develop new consumer-centric business models and possibly a localized energy trading platform. This dissertation is exactly pursuing these ideas and proposing a holistic localized electricity retail market to push the next-generation retail electricity market infrastructure to be a level playing field, where all customers have an equal opportunity to actively participate directly. This dissertation also studied and discussed opportunities of many emerging technologies, such as reinforcement learning and deep reinforcement learning, for intelligent energy system operation. Some improvement suggestion of the modeling framework and methodology are included as well.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145686/1/Tao Chen Final Dissertation.pdfDescription of Tao Chen Final Dissertation.pdf : Dissertatio

    Context-Aware and Adaptable eLearning Systems

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    The full text file attached to this record contains a copy of the thesis without the authors publications attached. The list of publications that are attached to the complete thesis can be found on pages 6-7 in the thesis.This thesis proposed solutions to some shortcomings to current eLearning architectures. The proposed DeLC architecture supports context-aware and adaptable provision of eLearning services and electronic content. The architecture is fully distributed and integrates service-oriented development with agent technology. Central to this architecture is that a node is our unit of computation (known as eLearning node) which can have purely service-oriented architecture, agent-oriented architecture or mixed architecture. Three eLeaerning Nodes have been implemented in order to demonstrate the vitality of the DeLC concept. The Mobile eLearning Node uses a three-level communication network, called InfoStations network, supporting mobile service provision. The services, displayed on this node, are to be aware of its context, gather required learning material and adapted to the learner request. This is supported trough a multi-layered hybrid (service- and agent-oriented) architecture whose kernel is implemented as middleware. For testing of the middleware a simulation environment has been developed. In addition, the DeLC development approach is proposed. The second eLearning node has been implemented as Education Portal. The architecture of this node is poorly service-oriented and it adopts a client-server architecture. In the education portal, there are incorporated education services and system services, called engines. The electronic content is kept in Digital Libraries. Furthermore, in order to facilitate content creators in DeLC, the environment Selbo2 was developed. The environment allows for creating new content, editing available content, as well as generating educational units out of preexisting standardized elements. In the last two years, the portal is used in actual education at the Faculty of Mathematics and Informatics, University of Plovdiv. The third eLearning node, known as Agent Village, exhibits a purely agent-oriented architecture. The purpose of this node is to provide intelligent assistance to the services deployed on the Education Pportal. Currently, two kinds of assistants are implemented in the node - eTesting Assistants and Refactoring eLearning Environment (ReLE). A more complex architecture, known as Education Cluster, is presented in this thesis as well. The Education Cluster incorporates two eLearning nodes, namely the Education Portal and the Agent Village. eLearning services and intelligent agents interact in the cluster

    Combining MAS and P2P Systems: The Agent Trees Multi-Agent System (ATMAS)

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    The seamless retrieval of information distributed across networks has been one of the key goals of many systems. Early solutions involved the use of single static agents which would retrieve the unfiltered data and then process it. However, this was deemed costly and inefficient in terms of the bandwidth since complete files need to be downloaded when only a single value is often all that is required. As a result, mobile agents were developed to filter the data in situ before returning it to the user. However, mobile agents have their own associated problems, namely security and control. The Agent Trees Multi-Agent System (AT-MAS) has been developed to provide the remote processing and filtering capabilities but without the need for mobile code. It is implemented as a Peer to Peer (P2P) network of static intelligent cooperating agents, each of which control one or more data sources. This dissertation describes the two key technologies have directly influenced the design of ATMAS, Peer-to-Peer (P2P) systems and Multi-Agent Systems (MAS). P2P systems are conceptually simple, but limited in power, whereas MAS are significantly more complex but correspondingly more powerful. The resulting system exhibits the power of traditional MAS systems while retaining the simplicity of P2P systems. The dissertation describes the system in detail and analyses its performance

    MODELLING & SIMULATION HYBRID WARFARE Researches, Models and Tools for Hybrid Warfare and Population Simulation

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    The Hybrid Warfare phenomena, which is the subject of the current research, has been framed by the work of Professor Agostino Bruzzone (University of Genoa) and Professor Erdal Cayirci (University of Stavanger), that in June 2016 created in order to inquiry the subject a dedicated Exploratory Team, which was endorsed by NATO Modelling & Simulation Group (a panel of the NATO Science & Technology organization) and established with the participation as well of the author. The author brought his personal contribution within the ET43 by introducing meaningful insights coming from the lecture of \u201cFight by the minutes: Time and the Art of War (1994)\u201d, written by Lieutenant Colonel US Army (Rtd.) Robert Leonhard; in such work, Leonhard extensively developed the concept that \u201cTime\u201d, rather than geometry of the battlefield and/or firepower, is the critical factor to tackle in military operations and by extension in Hybrid Warfare. The critical reflection about the time - both in its quantitative and qualitative dimension - in a hybrid confrontation it is addressed and studied inside SIMCJOH, a software built around challenges that imposes literally to \u201cFight by the minutes\u201d, echoing the core concept expressed in the eponymous work. Hybrid Warfare \u2013 which, by definition and purpose, aims to keep the military commitment of both aggressor and defender at the lowest - can gain enormous profit by employing a wide variety of non-military tools, turning them into a weapon, as in the case of the phenomena of \u201cweaponization of mass migrations\u201d, as it is examined in the \u201cDies Irae\u201d simulation architecture. Currently, since migration it is a very sensitive and divisive issue among the public opinions of many European countries, cynically leveraging on a humanitarian emergency caused by an exogenous, inducted migration, could result in a high level of political and social destabilization, which indeed favours the concurrent actions carried on by other hybrid tools. Other kind of disruption however, are already available in the arsenal of Hybrid Warfare, such cyber threats, information campaigns lead by troll factories for the diffusion of fake/altered news, etc. From this perspective the author examines how the TREX (Threat network simulation for REactive eXperience) simulator is able to offer insights about a hybrid scenario characterized by an intense level of social disruption, brought by cyber-attacks and systemic faking of news. Furthermore, the rising discipline of \u201cStrategic Engineering\u201d, as envisaged by Professor Agostino Bruzzone, when matched with the operational requirements to fulfil in order to counter Hybrid Threats, it brings another innovative, as much as powerful tool, into the professional luggage of the military and the civilian employed in Defence and Homeland security sectors. Hybrid is not the New War. What is new is brought by globalization paired with the transition to the information age and rising geopolitical tensions, which have put new emphasis on hybrid hostilities that manifest themselves in a contemporary way. Hybrid Warfare is a deliberate choice of an aggressor. While militarily weak nations can resort to it in order to re-balance the odds, instead military strong nations appreciate its inherent effectiveness coupled with the denial of direct responsibility, thus circumventing the rules of the International Community (IC). In order to be successful, Hybrid Warfare should consist of a highly coordinated, sapient mix of diverse and dynamic combination of regular forces, irregular forces (even criminal elements), cyber disruption etc. all in order to achieve effects across the entire DIMEFIL/PMESII_PT spectrum. However, the owner of the strategy, i.e. the aggressor, by keeping the threshold of impunity as high as possible and decreasing the willingness of the defender, can maintain his Hybrid Warfare at a diplomatically feasible level; so the model of the capacity, willingness and threshold, as proposed by Cayirci, Bruzzone and Gunneriusson (2016), remains critical to comprehend Hybrid Warfare. Its dynamicity is able to capture the evanescent, blurring line between Hybrid Warfare and Conventional Warfare. In such contest time is the critical factor: this because it is hard to foreseen for the aggressor how long he can keep up with such strategy without risking either the retaliation from the International Community or the depletion of resources across its own DIMEFIL/PMESII_PT spectrum. Similar discourse affects the defender: if he isn\u2019t able to cope with Hybrid Threats (i.e. taking no action), time works against him; if he is, he can start to develop counter narrative and address physical countermeasures. However, this can lead, in the medium long period, to an unforeseen (both for the attacker and the defender) escalation into a large, conventional, armed conflict. The performance of operations that required more than kinetic effects drove the development of DIMEFIL/PMESII_PT models and in turn this drive the development of Human Social Culture Behavior Modelling (HCSB), which should stand at the core of the Hybrid Warfare modelling and simulation efforts. Multi Layers models are fundamental to evaluate Strategies and Support Decisions: currently there are favourable conditions to implement models of Hybrid Warfare, such as Dies Irae, SIMCJOH and TREX, in order to further develop tools and war-games for studying new tactics, execute collective training and to support decisions making and analysis planning. The proposed approach is based on the idea to create a mosaic made by HLA interoperable simulators able to be combined as tiles to cover an extensive part of the Hybrid Warfare, giving the users an interactive and intuitive environment based on the \u201cModelling interoperable Simulation and Serious Game\u201d (MS2G) approach. From this point of view, the impressive capabilities achieved by IA-CGF in human behavior modeling to support population simulation as well as their native HLA structure, suggests to adopt them as core engine in this application field. However, it necessary to highlight that, when modelling DIMEFIL/PMESII_PT domains, the researcher has to be aware of the bias introduced by the fact that especially Political and Social \u201cscience\u201d are accompanied and built around value judgement. From this perspective, the models proposed by Cayirci, Bruzzone, Guinnarson (2016) and by Balaban & Mileniczek (2018) are indeed a courageous tentative to import, into the domain of particularly poorly understood phenomena (social, politics, and to a lesser degree economics - Hartley, 2016), the mathematical and statistical instruments and the methodologies employed by the pure, hard sciences. Nevertheless, just using the instruments and the methodology of the hard sciences it is not enough to obtain the objectivity, and is such aspect the representations of Hybrid Warfare mechanics could meet their limit: this is posed by the fact that they use, as input for the equations that represents Hybrid Warfare, not physical data observed during a scientific experiment, but rather observation of the reality that assumes implicitly and explicitly a value judgment, which could lead to a biased output. Such value judgement it is subjective, and not objective like the mathematical and physical sciences; when this is not well understood and managed by the academic and the researcher, it can introduce distortions - which are unacceptable for the purpose of the Science - which could be used as well to enforce a narrative mainstream that contains a so called \u201ctruth\u201d, which lies inside the boundary of politics rather than Science. Those observations around subjectivity of social sciences vs objectivity of pure sciences, being nothing new, suggest however the need to examine the problem under a new perspective, less philosophical and more leaned toward the practical application. The suggestion that the author want make here is that the Verification and Validation process, in particular the methodology used by Professor Bruzzone in doing V&V for SIMCJOH (2016) and the one described in the Modelling & Simulation User Risk Methodology (MURM) developed by Pandolfini, Youngblood et all (2018), could be applied to evaluate if there is a bias and the extent of the it, or at least making clear the value judgment adopted in developing the DIMEFIL/PMESII_PT models. Such V&V research is however outside the scope of the present work, even though it is an offspring of it, and for such reason the author would like to make further inquiries on this particular subject in the future. Then, the theoretical discourse around Hybrid Warfare has been completed addressing the need to establish a new discipline, Strategic Engineering, very much necessary because of the current a political and economic environment which allocates diminishing resources to Defense and Homeland Security (at least in Europe). However, Strategic Engineering can successfully address its challenges when coupled with the understanding and the management of the fourth dimension of military and hybrid operations, Time. For the reasons above, and as elaborated by Leonhard and extensively discussed in the present work, addressing the concern posed by Time dimension is necessary for the success of any military or Hybrid confrontation. The SIMCJOH project, examined under the above perspective, proved that the simulator has the ability to address the fourth dimension of military and non-military confrontation. In operations, Time is the most critical factor during execution, and this was successfully transferred inside the simulator; as such, SIMCJOH can be viewed as a training tool and as well a dynamic generator of events for the MEL/MIL execution during any exercise. In conclusion, SIMCJOH Project successfully faces new challenging aspects, allowed to study and develop new simulation models in order to support decision makers, Commanders and their Staff. Finally, the question posed by Leonhard in terms of recognition of the importance of time management of military operations - nowadays Hybrid Conflict - has not been answered yet; however, the author believes that Modelling and Simulation tools and techniques can represent the safe \u201ctank\u201d where innovative and advanced scientific solutions can be tested, exploiting the advantage of doing it in a synthetic environment

    Multi-Agent Systems

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    This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

    Maximizing User Engagement In Short Marketing Campaigns Within An Online Living Lab: A Reinforcement Learning Perspective

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    ABSTRACT MAXIMIZING USER ENGAGEMENT IN SHORT MARKETING CAMPAIGNS WITHIN AN ONLINE LIVING LAB: A REINFORCEMENT LEARNING PERSPECTIVE by ANIEKAN MICHAEL INI-ABASI August 2021 Advisor: Dr. Ratna Babu Chinnam Major: Industrial & Systems Engineering Degree: Doctor of Philosophy User engagement has emerged as the engine driving online business growth. Many firms have pay incentives tied to engagement and growth metrics. These corporations are turning to recommender systems as the tool of choice in the business of maximizing engagement. LinkedIn reported a 40% higher email response with the introduction of a new recommender system. At Amazon 35% of sales originate from recommendations, while Netflix reports that ‘75% of what people watch is from some sort of recommendation,’ with an estimated business value of 1billionperyear.Whiletheleadingcompanieshavebeenquitesuccessfulatharnessingthepowerofrecommenderstoboostuserengagementacrossthedigitalecosystem,smallandmediumbusinesses(SMB)arestrugglingwithdecliningengagementacrossmanychannelsascompetitionforuserattentionintensifies.TheSMBsoftenlackthetechnicalexpertiseandbigdatainfrastructurenecessarytooperationalizerecommendersystems.Thepurposeofthisstudyistoexplorethemethodsofbuildingalearningagentthatcanbeusedtopersonalizeapersuasiverequesttomaximizeuserengagementinadataefficientsetting.Weframethetaskasasequentialdecisionmakingproblem,modelledasMDP,andsolvedusingageneralizedreinforcementlearning(RL)algorithm.Weleverageanapproachthateliminatesoratleastgreatlyreducestheneedformassiveamountsoftrainingdata,thusmovingawayfromapurelydatadrivenapproach.Byincorporatingdomainknowledgefromtheliteratureonpersuasionintothemessagecomposition,weareabletotraintheRLagentinasampleefficientandoperantmanner.Inourmethodology,theRLagentnominatesacandidatefromacatalogofpersuasionprinciplestodrivehigheruserresponseandengagement.ToenabletheeffectiveuseofRLinourspecificsetting,wefirstbuildareducedstatespacerepresentationbycompressingthedatausinganexponentialmovingaveragescheme.AregularizedDQNagentisdeployedtolearnanoptimalpolicy,whichisthenappliedinrecommendingone(oracombination)ofsixuniversalprinciplesmostlikelytotriggerresponsesfromusersduringthenextmessagecycle.Inthisstudy,emailmessagingisusedasthevehicletodeliverpersuasionprinciplestotheuser.Atatimeofdecliningclickthroughrateswithmarketingemails,businessexecutivescontinuetoshowheightenedinterestintheemailchannelowingtohigherthanusualreturnoninvestmentof1 billion per year. While the leading companies have been quite successful at harnessing the power of recommenders to boost user engagement across the digital ecosystem, small and medium businesses (SMB) are struggling with declining engagement across many channels as competition for user attention intensifies. The SMBs often lack the technical expertise and big data infrastructure necessary to operationalize recommender systems. The purpose of this study is to explore the methods of building a learning agent that can be used to personalize a persuasive request to maximize user engagement in a data-efficient setting. We frame the task as a sequential decision-making problem, modelled as MDP, and solved using a generalized reinforcement learning (RL) algorithm. We leverage an approach that eliminates or at least greatly reduces the need for massive amounts of training data, thus moving away from a purely data-driven approach. By incorporating domain knowledge from the literature on persuasion into the message composition, we are able to train the RL agent in a sample efficient and operant manner. In our methodology, the RL agent nominates a candidate from a catalog of persuasion principles to drive higher user response and engagement. To enable the effective use of RL in our specific setting, we first build a reduced state space representation by compressing the data using an exponential moving average scheme. A regularized DQN agent is deployed to learn an optimal policy, which is then applied in recommending one (or a combination) of six universal principles most likely to trigger responses from users during the next message cycle. In this study, email messaging is used as the vehicle to deliver persuasion principles to the user. At a time of declining click-through rates with marketing emails, business executives continue to show heightened interest in the email channel owing to higher-than-usual return on investment of 42 for every dollar spent when compared to other marketing channels such as social media. Coupled with the state space transformation, our novel regularized Deep Q-learning (DQN) agent was able to train and perform well based on a few observed users’ responses. First, we explored the average positive effect of using persuasion-based messages in a live email marketing campaign, without deploying a learning algorithm to recommend the influence principles. The selection of persuasion tactics was done heuristically, using only domain knowledge. Our results suggest that embedding certain principles of persuasion in campaign emails can significantly increase user engagement for an online business (and have a positive impact on revenues) without putting pressure on marketing or advertising budgets. During the study, the store had a customer retention rate of 76% and sales grew by a half-million dollars from the three field trials combined. The key assumption was that users are predisposed to respond to certain persuasion principles and learning the right principles to incorporate in the message header or body copy would lead to higher response and engagement. With the hypothesis validated, we set forth to build a DQN agent to recommend candidate actions from a catalog of persuasion principles most likely to drive higher engagement in the next messaging cycle. A simulation and a real live campaign are implemented to verify the proposed methodology. The results demonstrate the agent’s superior performance compared to a human expert and a control baseline by a significant margin (~ up to 300%). As the quest for effective methods and tools to maximize user engagement intensifies, our methodology could help to boost user engagement for struggling SMBs without prohibitive increase in costs, by enabling the targeting of messages (with the right persuasion principle) to the right user
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