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    AGI
    2015
    19views Artificial Intelligence» more  AGI 2015»
    Decision-Making During Language Understanding by Intelligent Agents
    8 years 6 months ago
    Decision-Making During Language Understanding by Intelligent Agents
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    In cognitive modeling and intelligent agent design, a widely accepted architectural pipeline is Perception–Reasoning–Action. But language understanding, while a type of percept...
    Marjorie McShane, Sergei Nirenburg
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    AGI
    2015
    34views Artificial Intelligence» more  AGI 2015»
    Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognitio
    8 years 6 months ago
    Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognitio
    Download  agi-conf.org
    Abstract. We outline a proposal for a research program leading to a new paradigm, architectural framework, and prototypical implementation, for the cognitively inspired anchoring o...
    Tarek Richard Besold, Kai-Uwe Kühnberger, Art...
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    AGI
    2015
    29views Artificial Intelligence» more  AGI 2015»
    Assumptions of Decision-Making Models in AGI
    8 years 6 months ago
    Assumptions of Decision-Making Models in AGI
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    This paper analyzes the assumptions of the decision making models in the context of artificial general intelligence (AGI). It is argued that the traditional approaches, exemplifi...
    Pei Wang, Patrick Hammer
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    AGI
    2015
    21views Artificial Intelligence» more  AGI 2015»
    Modeling Motivation in MicroPsi 2
    8 years 6 months ago
    Modeling Motivation in MicroPsi 2
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    The MicroPsi architecture combines neuro-symbolic representations with autonomous decision making and motivation based learning. MicroPsi’s motivational system reflects cognitive...
    Joscha Bach
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    AGI
    2015
    13views Artificial Intelligence» more  AGI 2015»
    Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning
    8 years 6 months ago
    Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning
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    General reinforcement learning is a powerful framework for artificial intelligence that has seen much theoretical progress since introduced fifteen years ago. We have previously ...
    Peter Sunehag, Marcus Hutter
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    AGI
    2015
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    On the Limits of Recursively Self-Improving AGI
    8 years 6 months ago
    On the Limits of Recursively Self-Improving AGI
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    Self-improving software has been a goal of computer scientists since the founding of the field of Artificial Intelligence. In this work we analyze limits on computation which might...
    Roman V. Yampolskiy
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    AGI
    2015
    16views Artificial Intelligence» more  AGI 2015»
    Inferring Human Values for Safe AGI Design
    8 years 6 months ago
    Inferring Human Values for Safe AGI Design
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    Abstract. Aligning goals of superintelligent machines with human values is one of the ways to pursue safety in AGI systems. To achieve this, it is first necessary to learn what hu...
    Can Eren Sezener
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    AGI
    2015
    17views Artificial Intelligence» more  AGI 2015»
    Observation, Communication and Intelligence in Agent-Based Systems
    8 years 6 months ago
    Observation, Communication and Intelligence in Agent-Based Systems
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    The intelligence of multiagent systems is known to depend on the communication and observation abilities of its agents. However it is not clear which factor has the greater influe...
    Nader Chmait, David L. Dowe, David G. Green, Yuan-...
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    AGI
    2015
    35views Artificial Intelligence» more  AGI 2015»
    Are There Deep Reasons Underlying the Pathologies of Today's Deep Learning Algorithms?
    8 years 6 months ago
    Are There Deep Reasons Underlying the Pathologies of Today's Deep Learning Algorithms?
    Download  goertzel.org
    Abstract. Some currently popular and successful deep learning architectures display certain pathological behaviors (e.g. confidently classifying random data as belonging to a fami...
    Ben Goertzel
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    AGI
    2015
    15views Artificial Intelligence» more  AGI 2015»
    Emotional Concept Development
    8 years 6 months ago
    Emotional Concept Development
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    Abstract. Artificial emotions of different varieties have been used for controlling behavior, e.g. in cognitive architectures and reinforcement learning models. We propose to use ...
    Claes Strannegård, Simone Cirillo, Johan Wes...
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