This paper advances the theory that information pressure is the overarching driver for evolution in all its aspects. It proposes that there are 4 natural selection ‘factors’ that account for all species variation: 1. Information gathering... more
This paper advances the theory that information pressure is the overarching driver for evolution in all its aspects. It proposes that there are 4 natural selection ‘factors’ that account for all species variation:
1. Information gathering
2. Information storage
3. Information processing
4. Information usage
It proposes that language – when stored external to the human brain - is replacing DNA as the mechanism for both recording and causing variation in the human species. It further proposes that tools are, in fact, evolutionary variations of the human species in spite of not being part of the physical human organism.   
It then goes on to predict that a ‘silo’ effect produced by growing information pressures on the human brain will produce the next significant step in evolution beyond humans. Finally, it speculates on the intermediate steps between humans and the next species, the attributes that species may have, the advantages it may exhibit over humans, and the future of humans in the presence of the next higher species.
The paper is in 2 parts. The first part lays out a theory on what drives the evolution of animals with focus on brain evolution and ongoing human evolution. The second part assumes the theory to be true and speculates on what the next major step in evolution is after humans.
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In many navigational domains the traversability of cells is conditioned on the path taken. This is often the case in videogames, in which a character may need to acquire a certain object (i.e., a key or a flying suit) to be able to... more
In many navigational domains the traversability of cells is
conditioned on the path taken. This is often the case in videogames, in which a character may need to acquire a certain object (i.e., a key or a flying suit) to be able to traverse specific locations (e.g., doors or high walls). In order for non-player characters to handle such scenarios we present InvJPS, an “inventory-driven” pathfinding approach based on the highly successful grid-based Jump-Point-Search (JPS) algorithm.
We show, formally and experimentally, that the InvJPS reserves
JPS’s optimality guarantees and its symmetry breaking advantages in inventory-based variants of game maps.
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Recently a conference on robots and sex was cancelled by the police in Singapore.  This is a topic whose time as come.  I invite comments and insights from all fields.
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Semantic interoperability requires consistent use of controlled terminologies. However, non-terminology experts (although perhaps experts in a particular domain) are prone to produce variant coding. We examine this problem by... more
Semantic interoperability requires consistent use of controlled terminologies. However, non-terminology experts (although perhaps experts in a particular domain) are prone to produce variant coding. We examine this problem by investigating SNOMED CT coding variation for other findings reported on case report forms from a clinical research study on urea cycle disorders. The natural language findings from the forms were normalized, and the associated SNOMED CT concept descriptions were compared. The subset of normalized strings associated with two different concept descriptions were further compared to determine the relationship among the associated SNOMED CT concepts. We found 45% of the concept description pairs were associated with two hierarchically related concepts or with the same concept, while 55% were associated with two unrelated concepts. Clearer guidelines for use of SNOMED CT in particular contexts, or structured data entry tools tailored to the needs of non-expert coders...
This paper introduces and evaluates the use of Gaussian mixture models (GMMs) for multiple limb motion classification using continuous myoelectric signals. The focus of this work is to optimize the configuration of this classification... more
This paper introduces and evaluates the use of Gaussian mixture models (GMMs) for multiple limb motion classification using continuous myoelectric signals. The focus of this work is to optimize the configuration of this classification scheme. To that end, a complete experimental evaluation of this system is conducted on a 12 subject database. The experiments examine the GMMs algorithmic issues including the model order selection and variance limiting, the segmentation of the data, and various feature sets including time-domain features and autoregressive features. The benefits of postprocessing the results using a majority vote rule are demonstrated. The performance of the GMM is compared to three commonly used classifiers: a linear discriminant analysis, a linear perceptron network, and a multilayer perceptron neural network. The GMM-based limb motion classification system demonstrates exceptional classification accuracy and results in a robust method of motion classification with low computational load.
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A number of possibilities arise from the question: (i) new quantified versions of multi-agent epistemic logic capture locutions involving object identification, giving rise to applications in representing knowledge in multi-agent systems... more
A number of possibilities arise from the question: (i) new quantified versions of multi-agent epistemic logic capture locutions involving object identification, giving rise to applications in representing knowledge in multi-agent systems and parallel processing. (ii) The framework of game-theoretic semantics for the ensuing logics enjoys increased cognitive plausibility as the true semantics for epistemic notions. (iii) Recent findings in cognitive neuroscience pertaining to awareness and explicit versus implicit processing contribute to logical studies. These three connections are explored from both logical and cognitive perspectives. Neuroscientific research suggests new epistemic logics that handle unconscious and unaware information processing in the brain, making formalism thus amenable to knowledge representation in complex multi-agent configurations.
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In offline handwritten signature verification process, preprocessing of the signature is the very fast and most essential part. In some cases the raw signature can include extra pixel known as noises or may not be in proper form where... more
In offline handwritten signature verification process, preprocessing of the signature is the very fast and most essential part. In some cases the raw signature can include extra pixel known as noises or may not be in proper form where preprocessing is mandatory. If a signature is preprocessed correctly, it leads to a better result for both signature matching and forgery detection. Pre-processing includes binarization, noise removal, thinning, orientation etc. Many experiments and techniques have already been proposed for implementing these processes and some of them have shown exclusive and spectacular results. Regarding to this situation we have studied several pre-processing steps, signature features, feature detectors and also implemented some of them using MATLAB software. We have studied several image processing algorithms, and proposed an algorithm to correct the alignment of the input signature which can be used at the preprocessing stage to achieve better results in the signature detection process. We have tried to find a baseline of the handwritten signature and align it with respect to the baseline. Though there are some limitations involved but the experimentations have shown very promising results.
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This paper explores what has been termed artificial consciousness (AC) (a.k.a., synthetic consciousness or artificial sentience). Related to its companion, artificial intelligence (AI), the subject might sound more like science fiction or... more
This paper explores what has been termed artificial consciousness (AC) (a.k.a., synthetic consciousness or artificial sentience). Related to its companion, artificial intelligence (AI), the subject might sound more like science fiction or fantasy than possibility. Though humans have been speculating about nonhuman consciousness for centuries, it was in the 1960s when computer science promised the rise of machines with human-level abilities. While the real-world challenges persist, we went ahead and built autonomous, fictional entities like HAL 9000 and the Terminator. This task has been relatively simple for standard narrative, by merely placing anthropomorphic character over a machine. In reality, constructing the human platform, through silicon or otherwise, is more than a matter of physical engineering or reshuffling human qualities. In fact, a truly artificial agent has very little need to replicate human intelligence or other capabilities. Consequently, the potential emergence of real-world AC could have less to do with our machines than with the success or failure of our minds to comprehend it. Given the typical portrayal of AI in fiction, as talking bipedal robots and doomsday machines, and our centuries of misunderstanding organic life forms, including our own, we might simply be incapable of imagining where the future is headed.
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... eye movements to investigate the picture superiority effect in spatial memory 34 – 49 Zaira Cattaneo, Mitchell Rosen, Tomaso Vecchi, Jeff B ... Last but not least Self-reported Magic Eye™ stereogram skill predicts stereoacuity 1297 –... more
... eye movements to investigate the picture superiority effect in spatial memory 34 – 49 Zaira Cattaneo, Mitchell Rosen, Tomaso Vecchi, Jeff B ... Last but not least Self-reported Magic Eye™ stereogram skill predicts stereoacuity 1297 – 1300. Jeremy B Wilmer, Benjamin T Backus. ...
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