�ݺ�ߣshows by User: array2001

�ݺ�ߣshows by User: array2001 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: array2001 / Tue, 02 Sep 2014 05:47:10 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: array2001 BotPrize 2014 Results. Human-Like Bots Competition at IEEE CIG /slideshow/arrabales-bot-prize2014v2/38594802 arrabalesbotprize2014v2-140902054710-phpapp02
Human-Like Bots Competition (BotPrize 2014) presented by Raul Arrabales at IEEE CIG - Computational Ingelligence and Artificial Intelligence in Games. The BotPrize is a Turing Test for First-Person Shooter video game bots.]]>
Human-Like Bots Competition (BotPrize 2014) presented by Raul Arrabales at IEEE CIG - Computational Ingelligence and Artificial Intelligence in Games. The BotPrize is a Turing Test for First-Person Shooter video game bots.]]> Tue, 02 Sep 2014 05:47:10 GMT /slideshow/arrabales-bot-prize2014v2/38594802 array2001@slideshare.net(array2001) BotPrize 2014 Results. Human-Like Bots Competition at IEEE CIG array2001 Human-Like Bots Competition (BotPrize 2014) presented by Raul Arrabales at IEEE CIG - Computational Ingelligence and Artificial Intelligence in Games. The BotPrize is a Turing Test for First-Person Shooter video game bots. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbotprize2014v2-140902054710-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Human-Like Bots Competition (BotPrize 2014) presented by Raul Arrabales at IEEE CIG - Computational Ingelligence and Artificial Intelligence in Games. The BotPrize is a Turing Test for First-Person Shooter video game bots.

BotPrize 2014 Results. Human-Like Bots Competition at IEEE CIG from Accenture Analytics

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0 Integrating BI - Data Warehouse and Big Data /slideshow/arrabales-bi-bigdatav2/37327036 arrabalesbibigdatav2-140724112807-phpapp02
Towards the integration of traditional Business Intelligence Systems and Big Data. An introduction for young big data fans.]]>
Towards the integration of traditional Business Intelligence Systems and Big Data. An introduction for young big data fans.]]> Thu, 24 Jul 2014 11:28:07 GMT /slideshow/arrabales-bi-bigdatav2/37327036 array2001@slideshare.net(array2001) Integrating BI - Data Warehouse and Big Data array2001 Towards the integration of traditional Business Intelligence Systems and Big Data. An introduction for young big data fans. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbibigdatav2-140724112807-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Towards the integration of traditional Business Intelligence Systems and Big Data. An introduction for young big data fans.

Integrating BI - Data Warehouse and Big Data from Accenture Analytics

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0 The Big Data Dream Team /slideshow/arrabales-big-datadreamteamv3/36993422 arrabalesbigdatadreamteamv3-140715055435-phpapp02
Demystifying the Big Data Superheroes Mindset]]>
Demystifying the Big Data Superheroes Mindset]]> Tue, 15 Jul 2014 05:54:35 GMT /slideshow/arrabales-big-datadreamteamv3/36993422 array2001@slideshare.net(array2001) The Big Data Dream Team array2001 Demystifying the Big Data Superheroes Mindset <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbigdatadreamteamv3-140715055435-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Demystifying the Big Data Superheroes Mindset

The Big Data Dream Team from Accenture Analytics

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0 CERA-CRANIUM: A Test Bed for Machine Consciousness Research /slideshow/ceracranium-a-test-bed-for-machine-consciousness-research/3318325 arrabalesiwmc2009v7-100302122214-phpapp02
This paper describes a novel framework designed as a test bed for machine consciousness cognitive models (MCCM). This MCCM experimentation framework is based on a general-purpose cognitive architecture that can be integrated in different environments and confronted with different problem domains. The definition of a generic cognitive control system for abstract agents is the root of the versatility of the presented framework. The proposed control system, which is inspired in the major cognitive theories of consciousness, provides mechanisms for both sensory data acquisition and motor action execution. Sensory and motor data is represented in the proposed architecture using different level workspaces where percepts and actions are generated thanks to the competition and collaboration of specialized processors. Additionally, this cognitive architecture provides the means to modulate perception and behavior; in other words, it offers an interface for a higher control layer to drive the way percepts and actions are generated and how they interact with each other. This mechanism permits the experimentation with virtually any high level cognitive model of consciousness. An illustrative application scenario, autonomous explorer robots, is also reviewed in this work.]]>
This paper describes a novel framework designed as a test bed for machine consciousness cognitive models (MCCM). This MCCM experimentation framework is based on a general-purpose cognitive architecture that can be integrated in different environments and confronted with different problem domains. The definition of a generic cognitive control system for abstract agents is the root of the versatility of the presented framework. The proposed control system, which is inspired in the major cognitive theories of consciousness, provides mechanisms for both sensory data acquisition and motor action execution. Sensory and motor data is represented in the proposed architecture using different level workspaces where percepts and actions are generated thanks to the competition and collaboration of specialized processors. Additionally, this cognitive architecture provides the means to modulate perception and behavior; in other words, it offers an interface for a higher control layer to drive the way percepts and actions are generated and how they interact with each other. This mechanism permits the experimentation with virtually any high level cognitive model of consciousness. An illustrative application scenario, autonomous explorer robots, is also reviewed in this work.]]> Tue, 02 Mar 2010 12:21:56 GMT /slideshow/ceracranium-a-test-bed-for-machine-consciousness-research/3318325 array2001@slideshare.net(array2001) CERA-CRANIUM: A Test Bed for Machine Consciousness Research array2001 This paper describes a novel framework designed as a test bed for machine consciousness cognitive models (MCCM). This MCCM experimentation framework is based on a general-purpose cognitive architecture that can be integrated in different environments and confronted with different problem domains. The definition of a generic cognitive control system for abstract agents is the root of the versatility of the presented framework. The proposed control system, which is inspired in the major cognitive theories of consciousness, provides mechanisms for both sensory data acquisition and motor action execution. Sensory and motor data is represented in the proposed architecture using different level workspaces where percepts and actions are generated thanks to the competition and collaboration of specialized processors. Additionally, this cognitive architecture provides the means to modulate perception and behavior; in other words, it offers an interface for a higher control layer to drive the way percepts and actions are generated and how they interact with each other. This mechanism permits the experimentation with virtually any high level cognitive model of consciousness. An illustrative application scenario, autonomous explorer robots, is also reviewed in this work. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesiwmc2009v7-100302122214-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> This paper describes a novel framework designed as a test bed for machine consciousness cognitive models (MCCM). This MCCM experimentation framework is based on a general-purpose cognitive architecture that can be integrated in different environments and confronted with different problem domains. The definition of a generic cognitive control system for abstract agents is the root of the versatility of the presented framework. The proposed control system, which is inspired in the major cognitive theories of consciousness, provides mechanisms for both sensory data acquisition and motor action execution. Sensory and motor data is represented in the proposed architecture using different level workspaces where percepts and actions are generated thanks to the competition and collaboration of specialized processors. Additionally, this cognitive architecture provides the means to modulate perception and behavior; in other words, it offers an interface for a higher control layer to drive the way percepts and actions are generated and how they interact with each other. This mechanism permits the experimentation with virtually any high level cognitive model of consciousness. An illustrative application scenario, autonomous explorer robots, is also reviewed in this work.

CERA-CRANIUM: A Test Bed for Machine Consciousness Research from Accenture Analytics

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0 Establishing a Roadmap and Metrics for Conscious Machines Development /slideshow/establishing-a-roadmap-and-metrics-for-conscious-machines-development/3318304 arrabalesicci2009v2-100302121953-phpapp02
From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.]]>
From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.]]> Tue, 02 Mar 2010 12:19:19 GMT /slideshow/establishing-a-roadmap-and-metrics-for-conscious-machines-development/3318304 array2001@slideshare.net(array2001) Establishing a Roadmap and Metrics for Conscious Machines Development array2001 From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesicci2009v2-100302121953-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.

Establishing a Roadmap and Metrics for Conscious Machines Development from Accenture Analytics

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0 ConsScale: A Cognitive Scale Inspired on Consciousness /slideshow/consscale-a-cognitive-scale-inspired-on-consciousness/3318288 arrabalescogsys2010-100302121645-phpapp02
Arrabales, R. Ledezma, A. and Sanchis, A. "ConsScale: A Cognitive Scale Inspired on Consciousness". 4th International Conference on Cognitive Systems (CogSys 2010). Zürich. Switzerland. January 2010.]]>
Arrabales, R. Ledezma, A. and Sanchis, A. "ConsScale: A Cognitive Scale Inspired on Consciousness". 4th International Conference on Cognitive Systems (CogSys 2010). Zürich. Switzerland. January 2010.]]> Tue, 02 Mar 2010 12:16:40 GMT /slideshow/consscale-a-cognitive-scale-inspired-on-consciousness/3318288 array2001@slideshare.net(array2001) ConsScale: A Cognitive Scale Inspired on Consciousness array2001 Arrabales, R. Ledezma, A. and Sanchis, A. "ConsScale: A Cognitive Scale Inspired on Consciousness". 4th International Conference on Cognitive Systems (CogSys 2010). Zürich. Switzerland. January 2010. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalescogsys2010-100302121645-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Arrabales, R. Ledezma, A. and Sanchis, A. "ConsScale: A Cognitive Scale Inspired on Consciousness". 4th International Conference on Cognitive Systems (CogSys 2010). Zürich. Switzerland. January 2010.

ConsScale: A Cognitive Scale Inspired on Consciousness from Accenture Analytics

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0 Towards Conscious-like Behavior in Computer Game Characters /slideshow/towards-consciouslike-behavior-in-computer-game-characters/3318263 arrabalescig2009pptv1-100302160035-phpapp02
The main sources of inspiration for the design of more engaging synthetic characters are existing psychological models of human cognition. Usually, these models, and the associated Artificial Intelligence (AI) techniques, are based on partial aspects of the real complex systems involved in the generation of human-like behavior. Emotions, planning, learning, user modeling, set shifting, and attention mechanisms are some remarkable examples of features typically considered in isolation within classical AI control models. Artificial cognitive architectures aim at integrating many of these aspects together into effective control systems. However, the design of this sort of architectures is not straightforward. In this paper, we argue that current research efforts in the young field of Artificial Consciousness (AC) could contribute to tackle complexity and provide a useful framework for the design of more appealing synthetic characters. This hypothesis is illustrated with the application of a novel consciousness-based cognitive architecture to the development of a First Person Shooter video game character.]]>
The main sources of inspiration for the design of more engaging synthetic characters are existing psychological models of human cognition. Usually, these models, and the associated Artificial Intelligence (AI) techniques, are based on partial aspects of the real complex systems involved in the generation of human-like behavior. Emotions, planning, learning, user modeling, set shifting, and attention mechanisms are some remarkable examples of features typically considered in isolation within classical AI control models. Artificial cognitive architectures aim at integrating many of these aspects together into effective control systems. However, the design of this sort of architectures is not straightforward. In this paper, we argue that current research efforts in the young field of Artificial Consciousness (AC) could contribute to tackle complexity and provide a useful framework for the design of more appealing synthetic characters. This hypothesis is illustrated with the application of a novel consciousness-based cognitive architecture to the development of a First Person Shooter video game character.]]> Tue, 02 Mar 2010 12:13:40 GMT /slideshow/towards-consciouslike-behavior-in-computer-game-characters/3318263 array2001@slideshare.net(array2001) Towards Conscious-like Behavior in Computer Game Characters array2001 The main sources of inspiration for the design of more engaging synthetic characters are existing psychological models of human cognition. Usually, these models, and the associated Artificial Intelligence (AI) techniques, are based on partial aspects of the real complex systems involved in the generation of human-like behavior. Emotions, planning, learning, user modeling, set shifting, and attention mechanisms are some remarkable examples of features typically considered in isolation within classical AI control models. Artificial cognitive architectures aim at integrating many of these aspects together into effective control systems. However, the design of this sort of architectures is not straightforward. In this paper, we argue that current research efforts in the young field of Artificial Consciousness (AC) could contribute to tackle complexity and provide a useful framework for the design of more appealing synthetic characters. This hypothesis is illustrated with the application of a novel consciousness-based cognitive architecture to the development of a First Person Shooter video game character. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalescig2009pptv1-100302160035-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> The main sources of inspiration for the design of more engaging synthetic characters are existing psychological models of human cognition. Usually, these models, and the associated Artificial Intelligence (AI) techniques, are based on partial aspects of the real complex systems involved in the generation of human-like behavior. Emotions, planning, learning, user modeling, set shifting, and attention mechanisms are some remarkable examples of features typically considered in isolation within classical AI control models. Artificial cognitive architectures aim at integrating many of these aspects together into effective control systems. However, the design of this sort of architectures is not straightforward. In this paper, we argue that current research efforts in the young field of Artificial Consciousness (AC) could contribute to tackle complexity and provide a useful framework for the design of more appealing synthetic characters. This hypothesis is illustrated with the application of a novel consciousness-based cognitive architecture to the development of a First Person Shooter video game character.

Towards Conscious-like Behavior in Computer Game Characters from Accenture Analytics

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0 Assessing and Characterizing the Cognitive Power of Machine Consciousness Implementations /slideshow/assessing-and-characterizing-the-cognitive-power-of-machine-consciousness-implementations/3318052 arrabalesbica2009-100302114856-phpapp01
Many aspects can be taken into account in order to assess the power and potential of a cognitive architecture. In this paper we argue that ConsScale, a cognitive scale inspired on the development of consciousness, can be used to characterize and evaluate cognitive architectures from the point of view of the effective integration of their cognitive functionalities. Additionally, a graphical characterization of the cognitive power of artificial agents is proposed as a helpful tool for the analysis and comparison of Machine Consciousness implementations. This is illustrated with the application of the scale to a particular problem domain in the context of video game synthetic bots. Also, the problem of defining general architectural and behavioral criteria and their relation with the possibility of machine phenomenal states is briefly discussed.]]>
Many aspects can be taken into account in order to assess the power and potential of a cognitive architecture. In this paper we argue that ConsScale, a cognitive scale inspired on the development of consciousness, can be used to characterize and evaluate cognitive architectures from the point of view of the effective integration of their cognitive functionalities. Additionally, a graphical characterization of the cognitive power of artificial agents is proposed as a helpful tool for the analysis and comparison of Machine Consciousness implementations. This is illustrated with the application of the scale to a particular problem domain in the context of video game synthetic bots. Also, the problem of defining general architectural and behavioral criteria and their relation with the possibility of machine phenomenal states is briefly discussed.]]> Tue, 02 Mar 2010 11:48:52 GMT /slideshow/assessing-and-characterizing-the-cognitive-power-of-machine-consciousness-implementations/3318052 array2001@slideshare.net(array2001) Assessing and Characterizing the Cognitive Power of Machine Consciousness Implementations array2001 Many aspects can be taken into account in order to assess the power and potential of a cognitive architecture. In this paper we argue that ConsScale, a cognitive scale inspired on the development of consciousness, can be used to characterize and evaluate cognitive architectures from the point of view of the effective integration of their cognitive functionalities. Additionally, a graphical characterization of the cognitive power of artificial agents is proposed as a helpful tool for the analysis and comparison of Machine Consciousness implementations. This is illustrated with the application of the scale to a particular problem domain in the context of video game synthetic bots. Also, the problem of defining general architectural and behavioral criteria and their relation with the possibility of machine phenomenal states is briefly discussed. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbica2009-100302114856-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Many aspects can be taken into account in order to assess the power and potential of a cognitive architecture. In this paper we argue that ConsScale, a cognitive scale inspired on the development of consciousness, can be used to characterize and evaluate cognitive architectures from the point of view of the effective integration of their cognitive functionalities. Additionally, a graphical characterization of the cognitive power of artificial agents is proposed as a helpful tool for the analysis and comparison of Machine Consciousness implementations. This is illustrated with the application of the scale to a particular problem domain in the context of video game synthetic bots. Also, the problem of defining general architectural and behavioral criteria and their relation with the possibility of machine phenomenal states is briefly discussed.

Assessing and Characterizing the Cognitive Power of Machine Consciousness Implementations from Accenture Analytics

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0 https://cdn.slidesharecdn.com/profile-photo-array2001-48x48.jpg?cb=1529938694 Soy un profesional interdisciplinar comprometido con la innovación y la excelencia en los ámbitos de la tecnología, la ciencia, la formación de postgrado, el desarrollo de negocio y la gestión empresarial. Aporto una sólida experiencia profesional de más de 15 años en diferentes roles: - Emprendedor e Intraemprendedor (MBA): en los últimos años he liderado proyectos y start-ups de base tecnológica ostentando diferentes puestos, desde Jefe de Proyecto a CEO, en compañías como IBM, nCUBE (C-COR, ARRIS), T-Online, UC3M, Comaware, U-tad, Altran y Accenture. - Docente Universitario (Doctor acreditado ANECA): disfruto enseñando y aprendiendo con mis alumnos, fomentando el crecim www.conscious-robots.com https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbotprize2014v2-140902054710-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/arrabales-bot-prize2014v2/38594802 BotPrize 2014 Results.... https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbibigdatav2-140724112807-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/arrabales-bi-bigdatav2/37327036 Integrating BI - Data ... https://cdn.slidesharecdn.com/ss_thumbnails/arrabalesbigdatadreamteamv3-140715055435-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/arrabales-big-datadreamteamv3/36993422 The Big Data Dream Team