Real-Time Prediction of Gamers Behavior Using Variable Order Markov and Big Data Technology: A Case of Study

This paper presents the results and conclusions found when predicting the behavior of gamers in commercial videogames datasets. In particular, it uses Variable-Order Markov (VOM) to build a probabilistic model that is able to use the historic behavior of gamers and to infer what will be their next actions. Being able to predict with accuracy the next user’s actions can be of special interest to learn from the behavior of gamers, to make them more engaged and to reduce churn rate. In order to support a big volume and velocity of data, the system is built on top of the Hadoop ecosystem, using HBase for real-time processing; and the prediction tool is provided as a service (SaaS) and accessible through a RESTful API. The prediction system is evaluated using a case of study with two commercial videogames, attaining promising results with high prediction accuracies

An Architecture Approach for 3D Render Distribution using Mobile Devices in Real Time

Nowadays, video games such as Massively Multiplayer Online Game (MMOG) have become cultural mediators. Mobile games contribute to a large number of downloads and potential benefits in the applications market. Although processing power of mobile devices increases the bandwidth transmission, a poor network connectivity may bottleneck Gaming as a Service (GaaS). In order to enhance performance in digital ecosystem, processing tasks are distributed among thin client devices and robust servers. This research is based on the method ‘divide and rule’, that is, volumetric surfaces are subdivided using a tree-KD of sequence of scenes in a game, so reducing the surface into small sets of points. Reconstruction efficiency is improved, because the search of data is performed in local and small regions. Processes are modeled through a finite set of states that are built using Hidden Markov Models with domains configured by heuristics. Six test that control the states of each heuristic, including the number of intervals are carried out to validate the proposed model. This validation concludes that the proposed model optimizes response frames per second, in a sequence of interactions

Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure

In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis) lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise

Integrating Agents into a Collaborative Knowledge-based System for Business Rules Consistency Management

Capitalization and reuse of expert knowledge are very important for the survival of an enterprise. This paper presents a collaborative approach that utilizes domain ontology and agents. Thanks to our knowledge formalizing process, we give to domain expert an opportunity to store different forms of retrieved knowledge from experiences, design rules, business rules, decision processes, etc. The ontology is built to support business rules management. The global architecture is mainly composed of agents such as Expert agent, Evaluator agent, Translator agent, Security agent and Supervisor agent. The Evaluator agent is at the heart of our functional architecture, its role is to detect the problems that may arise in the consistency management module and provides a solution to these problems in order to validate the accuracy of business rules. In addition, a Security agent is defined to handle both security aspects in rules modeling and multi-agent system. The proposed approach is different from the others in terms of the number of rule’s inconsistencies which are detected and treated like contradiction, redundancy, invalid rules, domain violation and rules never applicable, the collaboration that is initiated among business experts and the guarantee of security of the business rules and all the agents which constitute our system. The developed collaborative system is applied in an industrial case study.

Strategic negotiation models for grid scheduling

One of the key requirements for Grid infrastructures is the ability to share resources with nontrivial qualities of service. However, resource management in a decentralized infrastructure is a complex task as it has to cope with di erent policies and objectives of the di erent resource providers and the resource users. This problem is further complicated due to the diversity of the resource types and the heterogeneity of their local resource management systems. Agreement-based resource management can be used to address these issues because in the negotiation process of creating such bilateral service level agreements (SLAs) between Grid parties, the di erent polices of the resource providers and the users will be abstracted and observed. Such negotiation processes should be automated with no or minimal human interaction, considering the potential scale of Grid systems and the amount of necessary transactions. Therefore, strategic negotiation models play important roles. In this thesis, we have made several novel research contributions which are as follows: - An agreement based resource management approach is analyzed. Requirements for the automatic negotiation problems in Grid computing are introduced. Furthermore, related work in the areas of economics and agent communities are investigated. - Several negotiation models and negotiation strategies are proposed and examined. Simulation results demonstrate that these proposed negotiation models are suitable and e ective for Grid environments. - Firstly, a strategic negotiation model using time-based negotiation strategies is proposed and evaluated using discrete event based simulation techniques. - Secondly, time-based negotiation strategies are quite limited in the dynamically changing Grid environment because they are quite simple and static; so learning based negotiation strategies are investigated and evaluated, which are quite exible and e ective in the dynamically changing Grid environment. Also we adopted negotiation strategies considering opportunistic functions for Grid scheduling. - Thirdly, it is usually necessary that resources from di erent resource providers are co-allocated to satisfy the complex requirements of the users, so a strategic negotiation model supporting co-allocation and the tradeo between "first" and "best" agreements in the Grid computing is also proposed and evaluated. - Finally, the contributions of the current research work to the WSNegotiation protocol are analyzed

Multi-Agent Systems

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

Putting the User at the Centre of the Grid: Simplifying Usability and Resource Selection for High Performance Computing

Computer simulation is finding a role in an increasing number of scientific disciplines, concomitant with the rise in available computing power. Realizing this inevitably re- quires access to computational power beyond the desktop, making use of clusters, supercomputers, data repositories, networks and distributed aggregations of these re- sources. Accessing one such resource entails a number of usability and security prob- lems; when multiple geographically distributed resources are involved, the difficulty is compounded. However, usability is an all too often neglected aspect of computing on e-infrastructures, although it is one of the principal factors militating against the widespread uptake of distributed computing. The usability problems are twofold: the user needs to know how to execute the applications they need to use on a particular resource, and also to gain access to suit- able resources to run their workloads as they need them. In this thesis we present our solutions to these two problems. Firstly we propose a new model of e-infrastructure resource interaction, which we call the user–application interaction model, designed to simplify executing application on high performance computing resources. We describe the implementation of this model in the Application Hosting Environment, which pro- vides a Software as a Service layer on top of distributed e-infrastructure resources. We compare the usability of our system with commonly deployed middleware tools using five usability metrics. Our middleware and security solutions are judged to be more usable than other commonly deployed middleware tools. We go on to describe the requirements for a resource trading platform that allows users to purchase access to resources within a distributed e-infrastructure. We present the implementation of this Resource Allocation Market Place as a distributed multi- agent system, and show how it provides a highly flexible, efficient tool to schedule workflows across high performance computing resources

Agent-Based Mediated Service Negotiation

Brazier, F.M.T. [Promotor]Overeinder, B.J. [Copromotor

Collaboration with agents in VR environments

Virtual reality is gaining on importance in many fields – scientific simulation, training, therapy and also more and more in entertainment. All these applications require the human user to interact with virtual worlds inhabited by intelligent characters and to solve simulated or real problems. This thesis will present an integrated approach to simulated problem solving in virtual reality environments, with the emphasis on teamwork and the ability to control the simulations. A simulation framework satisfying these goals will be presented. A unified approach to the representation of semantic information in virtual environments based on predicate calculus will be introduced, including the representation of the world state, action semantics and basic axioms holding in the simulated world. Afterwards, the focus will be on the collaboration model based on task delegation and facilitator-centric architecture. A simple but efficient facilitator design will be presented. The issues of the collaborative problem solving will be examined. A new technique using propositional (STRIPS-like) planning with delegated actions and object-specific planning will be described. A control technique for virtual characters/objects will be detailed, enabling run-time exchange of control and control sharing over a virtual entity between multiple autonomous agents and/or human users. Finally, a set of case studies will be shown, illustrating the possible applications of the techniques developed and described in this dissertation