53 resultados para Applied artificial intelligence


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L'objectiu principal del projecte és la creació d'una aplicació per a telèfons intel·ligents que intenti predir la volatilitat no atribuïble al mercat per tal de permetre a l'usuari crear portfolios òptims utilitzant tècniques d'intel·ligència artificial com són les Support Vector Machines (SVM). Una vegada s'hagi predit aquesta volatilitat es crearà un portfolio òptim amb el pes adequat de cada un dels valors, per tal d'obtenir una inversió amb el mínim risc possible.

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Des dels inicis dels ordinadors com a màquines programables, l’home ha intentat dotar-los de certa intel•ligència per tal de pensar o raonar el més semblant possible als humans. Un d’aquests intents ha sigut fer que la màquina sigui capaç de pensar de tal manera que estudiï jugades i guanyi partides d’escacs. En l’actualitat amb els actuals sistemes multi tasca, orientat a objectes i accés a memòria i gràcies al potent hardware del que disposem, comptem amb una gran varietat de programes que es dediquen a jugar a escacs. Però no hi ha només programes petits, hi ha fins i tot màquines senceres dedicades a calcular i estudiar jugades per tal de guanyar als millors jugadors del món. L’objectiu del meu treball és dur a terme un estudi i implementació d’un d’aquests programes, per això es divideix en dues parts. La part teòrica o de l’estudi, consta d’un estudi dels sistemes d’intel•ligència artificial que es dediquen a jugar a escacs, estudi i cerca d’una funció d’avaluació vàlida i estudi dels algorismes de cerca. La part pràctica del treball es basa en la implementació d’un sistema intel•ligent capaç de jugar a escacs amb certa lògica. Aquesta implementació es porta a terme amb l’ajuda de les llibreries SDL, utilitzant l’algorisme minimax amb poda alfa-beta i codi c++. Com a conclusió del projecte m’agradaria remarcar que l’estudi realitzat m’ha deixat veure que crear un joc d’escacs no era tan fàcil com jo pensava però m’ha aportat la satisfacció d’aplicar tot el que he après durant la carrera i de descobrir moltes altres coses noves.

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Aquest projecte documenta la realització d'un videojoc anomenat TriviaRace per a la consola Xbox 360. Els jugadors han de competir per ser els primers en arribar al final de l'escenari i contestar correctament a una pregunta que se'ls formula. Per arribar-hi abans que els seus contrincants, poden utilitzar objectes per a molestar-los. Poden jugar 4 jugadors simultàniament, ja siguin controlats per persones reals o per la consola, mitjançant una senzilla intel·ligència artificial. El desenvolupament del joc s'ha realitzat mitjançant XNA, unes eines de Microsoft orientades a la creació de videojocs per a vàries plataformes, inclosa la consola Xbox 360.

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In this work, we present the cultural evolution that has allowed to overcome many problems derived from the limitations of the human body. These limitations have been solved by a"cyborization" process that began since early anthropogenesis. Originally, it was envisioned to deal with some diseases, accidents or body malfunctions. Nowadays, augmentations improve common human capabilities; one of the most notable is the increase of brain efficiency by using connections with a computer. A basic social question also addressed is which people will and should have access to these augmentations. Advanced humanoid robots (with human external aspect, artificial intelligence and even emotions) already exist and consequently a number of questions arise. For instance, will robots be considered living organisms? Could they be considered as persons? Will we confer the human status to robots? These questions are discussed. Our conclusions are that the advanced humanoid robots display some actions that may be considered as life-like, yet different to the life associated with living organisms, also, to some extend they could be considered as persons-like, but not humans.

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El imaginario colectivo actual, reflejado sobre todo en el cine, muestra una profunda transformación de las características esenciales de la humanidad. La racionalidad ha sido desplazada por otros aspectos tradicionalmente relegados a lo irracional, lo animal, lo corporal, como la emotividad, el deseo, las pasiones. La ciencia-ficción y el cine expresan perfectamente esta deriva, pero no son las únicas manifestaciones. Juntamente con algunos ejemplos cinematográficos, este artículo extrae otros provenientes de la filosofía o la literatura modernas, así como de las barbaries sociales contemporáneas -genocidio, colonialismo¿ y alguna otra nota del campo de la neurología científica y la inteligencia artificial.

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We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.

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Organisations in Multi-Agent Systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents'relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits.

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We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddllanguage by extracting and using different classes of lower bounds, along with various heuristic-search algorithms. The lower bounds are extracted from deterministic relaxations of the mdp where alternativeprobabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms, on the other hand, use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state with the greedy policy.

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Planning with partial observability can be formulated as a non-deterministic search problem in belief space. The problem is harder than classical planning as keeping track of beliefs is harder than keeping track of states, and searching for action policies is harder than searching for action sequences. In this work, we develop a framework for partial observability that avoids these limitations and leads to a planner that scales up to larger problems. For this, the class of problems is restricted to those in which 1) the non-unary clauses representing the uncertainty about the initial situation are nvariant, and 2) variables that are hidden in the initial situation do not appear in the body of conditional effects, which are all assumed to be deterministic. We show that such problems can be translated in linear time into equivalent fully observable non-deterministic planning problems, and that an slight extension of this translation renders the problem solvable by means of classical planners. The whole approach is sound and complete provided that in addition, the state-space is connected. Experiments are also reported.

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El present TFM té per objectiu aplicar tècniques d'intel·ligència artificial per analitzar la incidència de l'esforç d'alta intensitat en la generació d'IncRNA.

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El present TFM té per objectiu aplicar tècniques d'intel·ligència artificial per realitzar el seguiment de les extremitats dels ratolins i les vibrisses del seu musell. Aquest objectiu es deriva de la necessitat per part dels realitzadors d'experiments optogenètics de registrar els moviments dels ratolins.

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DDM is a framework that combines intelligent agents and artificial intelligence traditional algorithms such as classifiers. The central idea of this project is to create a multi-agent system that allows to compare different views into a single one.

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In order to improve the management of copyright in the Internet, known as Digital Rights Management, there is the need for a shared language for copyright representation. Current approaches are based on purely syntactic solutions, i.e. a grammar that defines a rights expression language. These languages are difficult to put into practise due to the lack of explicit semantics that facilitate its implementation. Moreover, they are simple from the legal point of view because they are intended just to model the usage licenses granted by content providers to end-users. Thus, they ignore the copyright framework that lies behind and the whole value chain from creators to end-users. Our proposal is to use a semantic approach based on semantic web ontologies. We detail the development of a copyright ontology in order to put this approach into practice. It models the copyright core concepts for creation, rights and the basic kinds of actions that operate on content. Altogether, it allows building a copyright framework for the complete value chain. The set of actions operating on content are our smaller building blocks in order to cope with the complexity of copyright value chains and statements and, at the same time, guarantee a high level of interoperability and evolvability. The resulting copyright modelling framework is flexible and complete enough to model many copyright scenarios, not just those related to the economic exploitation of content. The ontology also includes moral rights, so it is possible to model this kind of situations as it is shown in the included example model for a withdrawal scenario. Finally, the ontology design and the selection of tools result in a straightforward implementation. Description Logic reasoners are used for license checking and retrieval. Rights are modelled as classes of actions, action patterns are modelled also as classes and the same is done for concrete actions. Then, to check if some right or license grants an action is reduced to check for class subsumption, which is a direct functionality of these reasoners.

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The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

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Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in ourunderstanding of problem hardness, beyond standard worst-case complexity. We consider random problem distributions from a highly structured problem domain that generalizes the Quasigroup Completion problem (QCP) and Quasigroup with Holes (QWH), a widely used domain that captures the structure underlying a range of real-world applications. Our problem domain is also a generalization of the well-known Sudoku puz- zle: we consider Sudoku instances of arbitrary order, with the additional generalization that the block regions can have rectangular shape, in addition to the standard square shape. We evaluate the computational hardness of Generalized Sudoku instances, for different parameter settings. Our experimental hardness results show that we can generate instances that are considerably harder than QCP/QWH instances of the same size. More interestingly, we show the impact of different balancing strategies on problem hardness. We also provide insights into backbone variables in Generalized Sudoku instances and how they correlate to problem hardness.