Understanding how innovations are accepted in a dynamic and complex market environment is a crucial factor for competitive advantage. To understand the relevant factors for this diffusion and to predict success, empirically grounded agent-based models have become increasingly popular in recent years. Despite the popularity of these innovation diffusion models, no common framework that integrates their diversity exists. This article presents a flexible, modular and extensible common description and implementation framework that allows to depict the large variety of model components found in existing models. The framework aims to provide a theoretically grounded description and implementation framework for empirically grounded agent-based models of innovation diffusion. It identifies 30 component requirements to conceptualize an integrated formal framework description. Based on this formal description, a java-based implementation allowing for flexible configuration of existing and future models of innovation diffusion is developed. As a variable decision support tool in decision-making processes on the adoption of innovations the framework is valuable for the investigation of a range of research questions on innovation diffusion, business model evaluation and infrastructure transformation.

Conventional method of development which repeats phases of design, implementation and testing is not adequate for systems like intelligent agents for which complex behavior is required but specification is unclear at the beginning of development process. Incremental design of agent's model during simulation seems more suitable for it enables direct feedback in behavioral changes of a system. This interactivity speeds up development process and helps to uncover parts of a space of all models to designer - thanks to new knowledge acquired during simulation. This thesis aims to provide comparison of suitability of two agent architectures and respective platforms in context of SmallDEVS modeling and simulation framework for this methodology of development. First approach is reactive and decentralized subsumption architecture based on DEVS formalism and the second one is PNagent, framework realizing deliberative BDI architecture using Object Oriented Petri Nets.

[pt] A ciência de dados precisa de uma grande quantidade de dados para testar e melhorar soluções. Jogos são largamente usados para abstrair situações da vida real. Rodadas de pôquer são um bom exemplo pois, por não saber as cartas dos oponentes, o jogador analisa um cenário de informação incompleta numa competição de agentes que envolve conhecimento probabilístico, análise de risco e brefe. Isso o diferencia de xadrez, damas e jogos de conhecimento perfeito e algoritmos de busca em forca bruta sobre o espaço de soluções. Usar o pôquer como um caso de teste possibilita a análise de diferentes abordagens usadas na vida real, porém num cenário mais controlado. Esta dissertação propõe um arcabouço de funcionalidades para criar e testar diferentes algorítimos de Deep Learning, que podem jogar pôquer entre sí, aprender com o histórico e maximizar suas recompensas. / [en] Data science research needs real examples to test and improve solutions. Games are widely used to mimic those real-world examples. Poker rounds are a good example of imperfect information state with competing agents dealing with probabilistic knowledge, risk assessment, and possible deception, unlike chess, checkers and perfect information brute-force search style of games. By using poker as a test-bed we can analyze different approaches used in real-world examples, in a more controlled environment, which should give great insights on how to tackle those real-world scenarios. We propose a framework to build and test different neural networks that can play against each other, learn from a supervised experience and maximize its rewards.

Tesis por compendio / [ES] El transporte de personas y bienes supone un problema complejo a la vez que un servicio esencial en la sociedad moderna. Entre los distintos modos de transporte, el transporte rodado supone ventajas y retos únicos, gracias a su flexibilidad y operación tanto urbana como interurbana. La creciente preocupación social respecto al medio ambiente afecta también al transporte rodado, pues los vehículos a motor son una gran fuente de emisiones de gases de efecto invernadero. Sin embargo, la digitalización de la sociedad y la aparición de nuevos modelos de transporte indican el potencial de mejora del transporte rodado, que podría adaptarse mejor a sus usuarios a la vez que operar de forma más sostenible. En esta tesis afrontamos la mejora del transporte rodado mediante técnicas de computación e inteligencia artificial. Esto incluye el modelado de sistemas de transporte mediante sistemas multiagente y su posterior simulación virtual. La operación de las flotas de transporte está determinada por la distribución de tareas, la planificación de las acciones de cada vehículo y su posterior coordinación. Exploramos distintas técnicas y desarrollamos propuestas que mejoran la operación de distintos sistemas de transporte rodado considerando tres puntos de vista: el del operador, el del usuario y, finalmente, el de la sostenibilidad. En otras palabras, apuntamos a obtener sistemas con mayor rendimiento económico y calidad de servicio a la par que un reducido impacto medioambiental. El objetivo de la mejora del transporte rodado se lleva a cabo desde tres frentes. Primero, se propone un marco de trabajo para el modelado efectivo y la simulación de sistemas de transporte. Esta aportación nos sirve como herramienta para la experimentación del resto de la investigación. Después, la investigación se centra en el transporte urbano, caso de uso para el que modelamos la ciudad como un escenario con recursos compartidos. Proponemos el uso de flotas de vehículos descentralizados para una mayor reactividad del sistema. Mediante un modelado de autointerés, se incentiva a los vehículos a proveer de un mejor servicio a los usuarios a la vez que evitan la congestión de los recursos. Finalmente, con la intención de aportar soluciones innovadoras también a las áreas rurales, se adaptan nuestras propuestas previas para el caso de uso del transporte rural interurbano. En este caso, observamos la necesidad de transporte público flexible y adaptado a los usuarios, con especial importancia en su sostenibilidad económica. Nuestras propuestas de sistema siguen estos principios atendiendo al paradigma del transporte adaptable a la demanda. Los resultados de esta tesis aportan soluciones prácticas para la mejora de distintos sistemas de transporte rodado, contribuyendo a un futuro de movilidad flexible más sostenible y adaptada al usuario. Como aportación en el ámbito de la inteligencia artificial, las técnicas desarrolladas tienen el potencial de ser adaptadas a campos más allá del transporte como soluciones generales para la distribución de tareas y la coordinación de elementos distribuidos. / [CA] El transport de persones i béns suposa un problema complex alhora que un servei essencial en la societat moderna. Entre els diferents modes de transport, el transport rodat suposa avantatges i reptes únics, gràcies a la seua flexibilitat i operació tant urbana com interurbana. La creixent preocupació social respecte al medi ambient afecta també al transport rodat, doncs els vehicles de motor són una gran font d'emissions de gasos d'efecte d'hivernacle. No obstant això, la digitalització de la societat i l'aparició de nous models de transport indiquen el potencial de millora del transport rodat, que podria adaptar-se millor als seus usuaris alhora que operar de forma més sostenible. En esta tesi afrontem la millora del transport rodat mitjançant tècniques de computació i intel·ligència artificial. Això inclou el modelatge de sistemes de transport mitjançant sistemes multiagent i la seua posterior simulació virtual. L'operació de les flotes de transport està determinada per la distribució de tasques, la planificació de les accions de cada vehicle i la seua posterior coordinació. Explorem diferents tècniques i desenvolupem propostes que milloren l'operació de diferents sistemes de transport rodat considerant tres punts de vista: el de l'operador, el de l'usuari i, finalment, el de la sostenibilitat. En altres paraules, apuntem a obtindre sistemes amb major rendiment econòmic i qualitat de servei al mateix temps que un reduït impacte mediambiental. L'objectiu de la millora del transport rodat es duu a terme des de tres fronts. Primer, es proposa un marc de treball per al modelatge efectiu i la simulació de sistemes de transport. Esta aportació ens serveix com a eina per a l'experimentació de la resta de la investigació. Després, la investigació se centra en el transport urbà, cas d'ús per al qual modelem la ciutat com un escenari amb recursos compartits. Proposem l'ús de flotes de vehicles descentralitzats per a una major reactivitat del sistema. Mitjançant un modelatge d'autointerés, s'incentiva als vehicles a proveir d'un millor servei als usuaris alhora que eviten la congestió dels recursos. Finalment, amb la intenció d'aportar solucions innovadores també a les àrees rurals, s'adapten les nostres propostes prèvies per al cas d'ús del transport rural interurbà. En este cas, observem la necessitat de transport públic flexible i adaptat als usuaris, amb especial importància en la seua sostenibilitat econòmica. Les nostres propostes de sistema segueixen estos principis atés el paradigma del transport adaptable a la demanda. Els resultats d'esta tesi aporten solucions pràctiques per a la millora de diferents sistemes de transport rodat, contribuint a un futur de mobilitat flexible més sostenible i adaptada a l'usuari. Com a aportació en l'àmbit de la intel·ligència artificial, les tècniques desenvolupades tenen el potencial de ser adaptades a camps més enllà del transport com a solucions generals per a la distribució de tasques i la coordinació d'elements distribuïts. / [EN] The transportation of people and goods is both a complex problem and an essential service in modern society. Among the various modes of transportation, road transport offers unique advantages and challenges, thanks to its flexibility and operation in both urban and interurban areas. The growing social concern for the environment also affects road transportation, as motor vehicles are a major source of greenhouse gas emissions. However, the digitalisation of society and the emergence of new transport models indicate the potential for improvement in transportation, which could be better adapted to its users while operating in a more sustainable way. In this thesis, we address the improvement of road transportation by means of computational techniques and artificial intelligence. This includes the modelling of transportation through multi-agent systems and their subsequent simulation. The operation of transportation fleets is determined by the distribution of tasks, the planning of the actions of each vehicle and their subsequent coordination. We explore different techniques and develop proposals that improve the operation of different transportation systems by considering three points of view: that of the operator, that of the user and, finally, that of sustainability. In other words, we aim to obtain systems with higher economic performance and quality of service while reducing their environmental impact. The objective of improving road transportation is pursued on three fronts. First, a framework for the effective modelling and simulation of transportation systems is proposed. This contribution serves as a tool for the experimentation of the rest of the research. Next, the research focuses on urban transportation, a use case for which we model the city as a shared resource scenario. We propose the use of decentralised vehicle fleets for greater reactivity of the system. Through self-interested modelling, vehicles are incentivised to provide a better service to users while avoiding resource congestion. Finally, with the intention of bringing innovative solutions also to rural areas, our previous proposals are adapted to the use case of rural interurban transportation. In this case, we note the need for flexible and user-friendly public transportation, with special emphasis on its economic sustainability. Our system proposals follow these principles following the demand-responsive transportation paradigm. The results of this thesis provide practical solutions for the enhancement of different road transportation systems, contributing to a future of more sustainable and user-tailored flexible mobility. As a contribution to the field of artificial intelligence the developed techniques have the potential to be adapted to fields beyond transportation, providing general solutions for the task allocation and the coordination of distributed elements. / Martí Gimeno, P. (2024). Towards Sustainable and Efficient Road Transportation: Development of Artificial Intelligence Solutions for Urban and Interurban Mobility [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203076 / Compendio

Submitted by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T20:32:05Z No. of bitstreams: 3 Dissertação - Leonardo Afonso Amorim - 2014.pdf: 2774608 bytes, checksum: b212628d1bce8ef7bf3f80e7286db111 (MD5) Dissertação - Leonardo Afonso Amorim - 2014 - Projeto.zip: 11944741 bytes, checksum: 141e5b6b22a4f615ef5f5bee052d97b5 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T20:32:50Z (GMT) No. of bitstreams: 3 Dissertação - Leonardo Afonso Amorim - 2014.pdf: 2774608 bytes, checksum: b212628d1bce8ef7bf3f80e7286db111 (MD5) Dissertação - Leonardo Afonso Amorim - 2014 - Projeto.zip: 11944741 bytes, checksum: 141e5b6b22a4f615ef5f5bee052d97b5 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-02-05T20:32:50Z (GMT). No. of bitstreams: 3 Dissertação - Leonardo Afonso Amorim - 2014.pdf: 2774608 bytes, checksum: b212628d1bce8ef7bf3f80e7286db111 (MD5) Dissertação - Leonardo Afonso Amorim - 2014 - Projeto.zip: 11944741 bytes, checksum: 141e5b6b22a4f615ef5f5bee052d97b5 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-09-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Decision making in public management is associated with a high degree of complexity due to insufficient financial resources to meet all the demands emanating from various sectors of society. Often, economic activities are in conflict with social or environmental causes. Another important aspect in decision making in public management is the inclusion of various stakeholders, eg public management experts, small business owners, shopkeepers, teachers, representatives of social and professional classes, citizens etc. The goal of this master thesis is to present two computational agents to aid decision making in public management as part of ADGEPA project: Miner Agent (MA) and Agent Decision Support (DSA). The MA uses data mining techniques and DSA uses multi-criteria analysis to point out relevant issues. The context in which this work fits is ADGEPA project. The ADGEPA (which means Digital Assistant for Participatory Public Management) is an innovative practice to support participatory decision making in public resources management. The main contribution of this master thesis is the ability to assist in the discovery of patterns and correlations between environmental aspects that are not too obvious and can vary from community to community. This contribution would help the public manager to make systemic decisions that in addition to attacking the main problem of a given region would decrease or solve other problems. The validation of the results depends on actual data and analysis of public managers. In this work, the data were simulated. / Tomada de decisão em gestão pública é associada ao alto grau de complexidade devido à insuficiência de recursos financeiros para atender todas as demandas provindas de diversos setores da sociedade. Frequentemente, atividades econômicas estão em conflito com causas sociais ou ambientais. Outro aspecto importante em tomadas de decisão em gestão pública é a inclusão dos diversos stakeholders, por exemplo especialistas em gestão pública, pequenos empresários, pequenos comerciantes, professores, representantes de classes sociais e profissionais, os próprios cidadãos etc. Diante disto, o objetivo deste trabalho de mestrado é apresentar uma proposta de Agente Minerador (AM) e Agente de Suporte à Decisão (ASD) para Gestão Pública Participativa e como fazer a interface entre eles. O AM faz uso de técnicas de mineração de dados para se encontrar regras de associação entre dados socioambientais, temporais e espaciais e o ASD faz uso de análise multicritério para ranquear problemas socioambientais que devem ser solucionados com prioridade. O contexto em que este trabalho se insere é o projeto ADGEPA (Assistente Digital para Gestão Pública Participativa), um projeto inovador para suporte à tomada de decisão participativa em gestão pública. Entende-se que a contribuição principal deste trabalho de mestrado é a possibilidade de auxiliar na descoberta de padrões e correlações entre aspectos socioambientais que não são muito óbvias e que podem variar de comunidade para comunidade. Esta contribuição poderá auxiliar o gestor público a tomar decisões sistêmicas que além de atacar o problema principal de uma determinada região diminuirá ou solucionará também problemas de outros aspectos. A validação dos resultados depende de dados reais e de análise de gestores públicos. Neste trabalho os dados foram simulados.