Modeling Affection Mechanisms using Deep and Self
... emotion concepts in artificial systems to improve the way they perform a task, like communication or learning. One of the most important aspects of affective computing is how to make computational systems recognize and learn emotion concepts from different experiences, for example in human communica ...
... emotion concepts in artificial systems to improve the way they perform a task, like communication or learning. One of the most important aspects of affective computing is how to make computational systems recognize and learn emotion concepts from different experiences, for example in human communica ...
osborne
... due to a mixture of poor experimental technique, poor experimenter/subject communication and an inability to appreciate the full implications of other psychologists work. These problems have cast doubt on a number of his ideas. It is important to examine these criticisms to ensure that the more rele ...
... due to a mixture of poor experimental technique, poor experimenter/subject communication and an inability to appreciate the full implications of other psychologists work. These problems have cast doubt on a number of his ideas. It is important to examine these criticisms to ensure that the more rele ...
Epistasis, polygenic effects, and the missing heritability problem : a
... Epistasis, Polygenic Effects, and the Missing Heritability Problem: A Review of Machine Learning as Applied to Genetic Association Studies In this review, I focus on the application of machine learning methods to the discovery of epistasis and polygenic effects in complex diseases. The definition o ...
... Epistasis, Polygenic Effects, and the Missing Heritability Problem: A Review of Machine Learning as Applied to Genetic Association Studies In this review, I focus on the application of machine learning methods to the discovery of epistasis and polygenic effects in complex diseases. The definition o ...
questions and answers: reasoning and querying in description logic
... of frame systems and semantic networks. An object oriented database audience can look at DLs as the static (declarative) part of a data definition language, while a logician could look at them as a syntactic variant of a multi-modal modal logic. Given this intuition, dipping into the literature reve ...
... of frame systems and semantic networks. An object oriented database audience can look at DLs as the static (declarative) part of a data definition language, while a logician could look at them as a syntactic variant of a multi-modal modal logic. Given this intuition, dipping into the literature reve ...
Learning and memory in zebrafish larvae
... well as its behavioral consequences, is significantly less restricted, and therefore less mechanistically informative, than in the larval zebrafish. The readiness with which zebrafish larvae lend themselves to optogenetics and other molecular tools (each with its own distinct efficacy across develop ...
... well as its behavioral consequences, is significantly less restricted, and therefore less mechanistically informative, than in the larval zebrafish. The readiness with which zebrafish larvae lend themselves to optogenetics and other molecular tools (each with its own distinct efficacy across develop ...
Revisiting Evolutionary Fuzzy Systems
... the application of MOEAs to fuzzy systems. Nowadays, researchers agree on the need to consider two groups of interpretability measures, complexity-based and semantic-based ones. While the first group is related to the dimensionality of the system (simpler is better) the second one is related to the c ...
... the application of MOEAs to fuzzy systems. Nowadays, researchers agree on the need to consider two groups of interpretability measures, complexity-based and semantic-based ones. While the first group is related to the dimensionality of the system (simpler is better) the second one is related to the c ...
Deep learning in neural networks: An overview
... present state of the art. I acknowledge the limitations of attempting to achieve this goal. The DL research community itself may be viewed as a continually evolving, deep network of scientists who have influenced each other in complex ways. Starting from recent DL results, I tried to trace back the ...
... present state of the art. I acknowledge the limitations of attempting to achieve this goal. The DL research community itself may be viewed as a continually evolving, deep network of scientists who have influenced each other in complex ways. Starting from recent DL results, I tried to trace back the ...
CS2053
... Representation Issues Knowledge acquisition – Heuristic Search: Techniques for Heuristic search Heuristic Classification -State Space Search: Strategies Implementation of Graph Search Search based on Recursion Patent -directed Search Production System and Learning. ...
... Representation Issues Knowledge acquisition – Heuristic Search: Techniques for Heuristic search Heuristic Classification -State Space Search: Strategies Implementation of Graph Search Search based on Recursion Patent -directed Search Production System and Learning. ...
Introduction: Aspects of Artificial General Intelligence
... possible for the system to be an integration of several techniques, so as to be generalpurpose without a single g-factor. Also, AGI does not exclude individual difference. It is possible to implement multiple copies of the same AGI design, with different parameters and innate capabilities, and the ...
... possible for the system to be an integration of several techniques, so as to be generalpurpose without a single g-factor. Also, AGI does not exclude individual difference. It is possible to implement multiple copies of the same AGI design, with different parameters and innate capabilities, and the ...
Mind Design II : Philosophy, Psychology, Artificial Intelligence
... Rationality here means: acting so as best to satisfy your goals overall, given what you know and can tell about your situation. Subject to this constraint, we can surmise what a system wants and believes by watching what it does—but, of course, not in isolation. From all you can tell in isolation, a ...
... Rationality here means: acting so as best to satisfy your goals overall, given what you know and can tell about your situation. Subject to this constraint, we can surmise what a system wants and believes by watching what it does—but, of course, not in isolation. From all you can tell in isolation, a ...
Mind Design II : Philosophy, Psychology, Artificial Intelligence
... Rationality here means: acting so as best to satisfy your goals overall, given what you know and can tell about your situation. Subject to this constraint, we can surmise what a system wants and believes by watching what it does—but, of course, not in isolation. From all you can tell in isolation, a ...
... Rationality here means: acting so as best to satisfy your goals overall, given what you know and can tell about your situation. Subject to this constraint, we can surmise what a system wants and believes by watching what it does—but, of course, not in isolation. From all you can tell in isolation, a ...
Machine Learning I - Mit - Massachusetts Institute of Technology
... more formally in the next section. Slide 2.1.25 Imagine that you were given all these points, and you needed to guess a function of their x, y coordinates that would have one output for the red ones and a different output for the black ones. ...
... more formally in the next section. Slide 2.1.25 Imagine that you were given all these points, and you needed to guess a function of their x, y coordinates that would have one output for the red ones and a different output for the black ones. ...
Case Representation Issues for Case
... measured using leave-one-out testing. To produce an ensemble this process is repeated for each classifier and at the end all the classifiers are aggregated to form the ensemble. This is the approach used to produce the results shown in Table 1. The algorithm used to produce the results in Table 2 go ...
... measured using leave-one-out testing. To produce an ensemble this process is repeated for each classifier and at the end all the classifiers are aggregated to form the ensemble. This is the approach used to produce the results shown in Table 1. The algorithm used to produce the results in Table 2 go ...
The Twenty-Ninth International Florida Artificial Intelligence
... Johnson (Florida Institute for Human & Machine Cognition, USA), and Kristin Tolle (Microsoft Research Outreach, USA). In addition, our Special Track Invited Speakers are Diana Inkpen (University of Ottawa, Canada), Christophe Gonzales (University Paris 6, France), and Xingquan Zhu (Florida Atlantic ...
... Johnson (Florida Institute for Human & Machine Cognition, USA), and Kristin Tolle (Microsoft Research Outreach, USA). In addition, our Special Track Invited Speakers are Diana Inkpen (University of Ottawa, Canada), Christophe Gonzales (University Paris 6, France), and Xingquan Zhu (Florida Atlantic ...
Philosophical Aspects in Pattern Recognition Research
... rationally”) [96]. However, beyond differences, it seems that AI definitions cannot avoid talking about intelligence either as a phenomenon that we can experience or as an abstract problem. Indeed, it is not by chance that a typical AI class starts with some general questions (e.g., what is intellig ...
... rationally”) [96]. However, beyond differences, it seems that AI definitions cannot avoid talking about intelligence either as a phenomenon that we can experience or as an abstract problem. Indeed, it is not by chance that a typical AI class starts with some general questions (e.g., what is intellig ...
WordNet::Similarity - Measuring the Relatedness of Concepts
... lexical database, pages 265–283. MIT Press. D. Lin. 1998. An information-theoretic definition of similarity. In Proceedings of the International Conference on Machine Learning, Madison, August. D. McCarthy, R. Koeling, and J. Weeds. 2004. Ranking WordNet senses automatically. Technical Report CSRP 5 ...
... lexical database, pages 265–283. MIT Press. D. Lin. 1998. An information-theoretic definition of similarity. In Proceedings of the International Conference on Machine Learning, Madison, August. D. McCarthy, R. Koeling, and J. Weeds. 2004. Ranking WordNet senses automatically. Technical Report CSRP 5 ...
Chapter 02 Neuroscience and Behavior
... As the impulse travels along the axon, the movement of ions causes a change in charge from positive to neutral in successive sections of the axon. ...
... As the impulse travels along the axon, the movement of ions causes a change in charge from positive to neutral in successive sections of the axon. ...
A Landform-based Approach for the
... by their outlines, i.e. the limit between the sky and Earth. A qualitative representation of a 2D-shape is influenced by the level of resolution that determines the geometric primitives of salient features. For instance, let us assume that the category ‘mountain’ is modelled by a sequence of a right ...
... by their outlines, i.e. the limit between the sky and Earth. A qualitative representation of a 2D-shape is influenced by the level of resolution that determines the geometric primitives of salient features. For instance, let us assume that the category ‘mountain’ is modelled by a sequence of a right ...
link - Worcester Polytechnic Institute
... improving the accuracy with which future student performance can be predicted. The second focus is to predict how different educational content and tutorial strategies will influence learning. The two focuses are complimentary but are approached from slightly different directions. I have found that ...
... improving the accuracy with which future student performance can be predicted. The second focus is to predict how different educational content and tutorial strategies will influence learning. The two focuses are complimentary but are approached from slightly different directions. I have found that ...
Sample chapter - Computer Science and Software Engineering
... Our definition of landmarks is purely functional: being a landmark is a role that objects from any category can play. It emphasizes that landmarks are mental constructs. In alignment with Meaning 1 and 2 from above it covers for objects that stand out in an environment such that they have made (or c ...
... Our definition of landmarks is purely functional: being a landmark is a role that objects from any category can play. It emphasizes that landmarks are mental constructs. In alignment with Meaning 1 and 2 from above it covers for objects that stand out in an environment such that they have made (or c ...
Profiles in Innovation: Artificial Intelligence
... One of the more exciting aspects of the AI inflection is that “real-world” use cases abound. While deep-learning enabled advances in computer vision and such technologies as natural language processing are dramatically improving the quality of Apple’s Siri, Amazon’s Alexa, and Google’s photo recogni ...
... One of the more exciting aspects of the AI inflection is that “real-world” use cases abound. While deep-learning enabled advances in computer vision and such technologies as natural language processing are dramatically improving the quality of Apple’s Siri, Amazon’s Alexa, and Google’s photo recogni ...
Here - School of Computer Science, University of Birmingham.
... is guided by strategic interactions between solutions in the population, which can be naturally framed as game playing. We study two important issues in coevolutionary learning—generalization performance and diversity—using games. The first one is concerned with the coevolutionary learning of strate ...
... is guided by strategic interactions between solutions in the population, which can be naturally framed as game playing. We study two important issues in coevolutionary learning—generalization performance and diversity—using games. The first one is concerned with the coevolutionary learning of strate ...
Introduction to The Soar Papers - Autonomous Learning Laboratory
... implementation of Soar, and the basis for the implementation of the earliest version of Soar-style chunking. Soar’s chunking mechanism arose out of earlier work on models of human practice. This work progressed from an analysis of the data on human practice ! in particular, the power-law shape of pr ...
... implementation of Soar, and the basis for the implementation of the earliest version of Soar-style chunking. Soar’s chunking mechanism arose out of earlier work on models of human practice. This work progressed from an analysis of the data on human practice ! in particular, the power-law shape of pr ...
Ch 16. Artificial Intelligence
... A particular data item becomes part of the knowledge of the chair if there are processing operations related to the chair that references that item ...
... A particular data item becomes part of the knowledge of the chair if there are processing operations related to the chair that references that item ...
Contents | Zoom in | Zoom out Search Issue | Next Page For
... omputational intelligence is at the heart of many new technological developments. For example, recently there are a lot of deliberations, even in popular media such as The New York Times, about the need to handle Big Data. This is an area that the industry is particularly interested in, with huge po ...
... omputational intelligence is at the heart of many new technological developments. For example, recently there are a lot of deliberations, even in popular media such as The New York Times, about the need to handle Big Data. This is an area that the industry is particularly interested in, with huge po ...