EfficientIDC: A Faster Incremental Dynamic Controllability Algorithm
... initial list of modified edges is processed in order of distance to the temporal reference, but all edges derived by FastIDC itself are handled recursively and depth-first. The small example in figure 3 shows why this is a suboptimal strategy for selecting focus edges. In this example the positive e ...
... initial list of modified edges is processed in order of distance to the temporal reference, but all edges derived by FastIDC itself are handled recursively and depth-first. The small example in figure 3 shows why this is a suboptimal strategy for selecting focus edges. In this example the positive e ...
Document
... corresponds to Rule 1, receives inputs from neurons A1 and B1. In a neuro-fuzzy system, intersection can be implemented by the product operator. Thus, the output of neuron i in Layer 3 is obtained as: ...
... corresponds to Rule 1, receives inputs from neurons A1 and B1. In a neuro-fuzzy system, intersection can be implemented by the product operator. Thus, the output of neuron i in Layer 3 is obtained as: ...
A Functional Programming Approach to AI Search Algorithms
... In the seminars, the instructors show the same algorithms written in a high-level programming language, which used to be Pascal and C, but nowadays we use Java and C#. However, the highlevel language code is merely another representation of the pseudocode, so students with little programming backgro ...
... In the seminars, the instructors show the same algorithms written in a high-level programming language, which used to be Pascal and C, but nowadays we use Java and C#. However, the highlevel language code is merely another representation of the pseudocode, so students with little programming backgro ...
A Parallel Approach to Syntax for Generation 1 Introduction
... That the generation task requires parallelism has not been generally recognized. A historical reason for this might be the pervasive focus on structure rather than process. It is common to start work from a notion of the inputs that a generator must deal with, or from a (typically structuralist) the ...
... That the generation task requires parallelism has not been generally recognized. A historical reason for this might be the pervasive focus on structure rather than process. It is common to start work from a notion of the inputs that a generator must deal with, or from a (typically structuralist) the ...
Motif distribution, dynamical properties, and computational
... ‘‘neural users”, i.e., to pyramidal neurons in layer 2/3 (which typically project to higher cortical areas) and to pyramidal neurons in layer 5 (which typically project to lower cortical areas or to subcortical structures, but also project for example from V1 back to nonspecific thalamus, i.e. to the ...
... ‘‘neural users”, i.e., to pyramidal neurons in layer 2/3 (which typically project to higher cortical areas) and to pyramidal neurons in layer 5 (which typically project to lower cortical areas or to subcortical structures, but also project for example from V1 back to nonspecific thalamus, i.e. to the ...
Introduction to Artificial Intelligence (Undergraduate Topics in
... not covered in detail. The field of image processing, which is important for all of computer science, is a stand-alone discipline with very good textbooks, such as [GW08]. Natural language processing has a similar status. In recognizing and generating text and spoken language, methods from logic, pr ...
... not covered in detail. The field of image processing, which is important for all of computer science, is a stand-alone discipline with very good textbooks, such as [GW08]. Natural language processing has a similar status. In recognizing and generating text and spoken language, methods from logic, pr ...
An efficient approach for finding the MPE in belief networks
... duction problems, and then the best-search techniques are applied to find MPE in the WBFDAGs. Since the number of the nodes in the converted graph is expo nential in the size of the original belief network, effi ciency of this technique seems not comparable with some algorithms directly evaluating ...
... duction problems, and then the best-search techniques are applied to find MPE in the WBFDAGs. Since the number of the nodes in the converted graph is expo nential in the size of the original belief network, effi ciency of this technique seems not comparable with some algorithms directly evaluating ...
Laminar Selectivity of the Cholinergic Suppression of Synaptic
... experimental data (Levy et al., 1990) and for stability during learning in analytical descriptions (Grossberg, 1976). While long-term potentiation has been demonstrated in s. l-m (Levy and Colbert, 1992) these synapses were not modified in the simulations presented here. In other simulations, modifi ...
... experimental data (Levy et al., 1990) and for stability during learning in analytical descriptions (Grossberg, 1976). While long-term potentiation has been demonstrated in s. l-m (Levy and Colbert, 1992) these synapses were not modified in the simulations presented here. In other simulations, modifi ...
Module 2
... It was started from the mid 1960 and continues until the mid 1970. During this period people were interested in making machine understand, that is usually mean the understanding of natural language. During this period the knowledge representation technique “semantic net” was developed. 3. Modern Per ...
... It was started from the mid 1960 and continues until the mid 1970. During this period people were interested in making machine understand, that is usually mean the understanding of natural language. During this period the knowledge representation technique “semantic net” was developed. 3. Modern Per ...
Pathfinding - cse.scu.edu
... It might take processing lots of “obviously” uninteresting nodes before we can process the goal node Dijkstra works well to find minimum paths to all nodes, but not so well for finding a minimum path to a specific node ...
... It might take processing lots of “obviously” uninteresting nodes before we can process the goal node Dijkstra works well to find minimum paths to all nodes, but not so well for finding a minimum path to a specific node ...
Neural Networks
... However, the aspects covered by Snipe are not entirely congruent with those covered by this manuscript. Some of the kinds of neural networks are not supported by Snipe, while when it comes to other kinds of neural networks, Snipe may have lots and lots more capabilities than may ever be covered in t ...
... However, the aspects covered by Snipe are not entirely congruent with those covered by this manuscript. Some of the kinds of neural networks are not supported by Snipe, while when it comes to other kinds of neural networks, Snipe may have lots and lots more capabilities than may ever be covered in t ...
Neural Networks
... However, the aspects covered by Snipe are not entirely congruent with those covered by this manuscript. Some of the kinds of neural networks are not supported by Snipe, while when it comes to other kinds of neural networks, Snipe may have lots and lots more capabilities than may ever be covered in t ...
... However, the aspects covered by Snipe are not entirely congruent with those covered by this manuscript. Some of the kinds of neural networks are not supported by Snipe, while when it comes to other kinds of neural networks, Snipe may have lots and lots more capabilities than may ever be covered in t ...
Context-Dependent Incremental Intention Recognition through Bayesian Network Model Construction
... In this work, we use Bayesian Networks (BN) as the intention recognition model. The flexibility of BNs for representing probabilistic dependencies and the efficiency of inference methods for BN have made them an extremely powerful and natural tool for problem solving under uncertainty [16, 17]. We p ...
... In this work, we use Bayesian Networks (BN) as the intention recognition model. The flexibility of BNs for representing probabilistic dependencies and the efficiency of inference methods for BN have made them an extremely powerful and natural tool for problem solving under uncertainty [16, 17]. We p ...
Knowledge Acquisition Via Incremental Conceptual Clustering
... level categories (e.g., bird) are retrieved more quickly than either more general (e.g., animal) or more specific (e.g., robin) classes during object recognition. More generally, basic level categories are hypothesized to be where a number of inference-related abilities are maximized in humans (Merv ...
... level categories (e.g., bird) are retrieved more quickly than either more general (e.g., animal) or more specific (e.g., robin) classes during object recognition. More generally, basic level categories are hypothesized to be where a number of inference-related abilities are maximized in humans (Merv ...
Improving Efficiency in Mobile Robot Task Planning through World
... planners that use abstraction in some way to reduce computational cost are commonly called hierarchical planners. A hierarchical planner first solves a problem in a simpler abstract domain2 and then refines the abstract solution, inserting details that were ignored in the more abstract domain. This ...
... planners that use abstraction in some way to reduce computational cost are commonly called hierarchical planners. A hierarchical planner first solves a problem in a simpler abstract domain2 and then refines the abstract solution, inserting details that were ignored in the more abstract domain. This ...
Na¨ıve Inference viewed as Computation
... quiring additional assumptions, naı̈ve inference may then have a use as a least-commitment approach to inference in the presence of conditional cycles. The regime also makes connections with noninferential models of mechanism. Accommodation of cycles means that naı̈ve inference can exhibit looping. ...
... quiring additional assumptions, naı̈ve inference may then have a use as a least-commitment approach to inference in the presence of conditional cycles. The regime also makes connections with noninferential models of mechanism. Accommodation of cycles means that naı̈ve inference can exhibit looping. ...
Drums and Bass Interlocking - Music Technology Group
... Algorithmic composition (AC) is not a recent research topic and has been quite broadly explored. By algorithmic composition we will refer to the computational implementation of algorithms to compose music. Previous to the existence of computers, musicians already used algorithms to compose music (e. ...
... Algorithmic composition (AC) is not a recent research topic and has been quite broadly explored. By algorithmic composition we will refer to the computational implementation of algorithms to compose music. Previous to the existence of computers, musicians already used algorithms to compose music (e. ...
Simple Stochastic Temporal Constraint Networks
... and tools of constraint satisfaction [Montanari, 1974; Tsang, 1993]. In particular, Van Beek [1992a, 1992b] and Ladkin and Reinefeld [1992] provided effective solutions to some temporal reasoning tasks involving topological, i.e. qualitative, temporal relations introduced earlier by Allen [1983]. Ma ...
... and tools of constraint satisfaction [Montanari, 1974; Tsang, 1993]. In particular, Van Beek [1992a, 1992b] and Ladkin and Reinefeld [1992] provided effective solutions to some temporal reasoning tasks involving topological, i.e. qualitative, temporal relations introduced earlier by Allen [1983]. Ma ...
Paper - FB3
... inexpressive concrete domain based on the natural numbers and providing for equality and incrementation predicates is undecidable, see also the survey paper [23]. In view of this discouraging result, it is a natural question whether there are any useful concrete domains that can be combined with gen ...
... inexpressive concrete domain based on the natural numbers and providing for equality and incrementation predicates is undecidable, see also the survey paper [23]. In view of this discouraging result, it is a natural question whether there are any useful concrete domains that can be combined with gen ...
Baseball Prediction Using Ensemble Learning by Arlo Lyle (Under
... work in performance prediction uses purely statistical methods, this thesis showcases research in combining multiple machine learning techniques to improve on current prediction systems by increasing the accuracy of projections in several key offensive statistical categories. By using the statistics ...
... work in performance prediction uses purely statistical methods, this thesis showcases research in combining multiple machine learning techniques to improve on current prediction systems by increasing the accuracy of projections in several key offensive statistical categories. By using the statistics ...
Folie 1
... outputs. Each neuron computes a weighted sum of the incoming signals, to yield a net input, and passes this value through its sigmoidal activation function to yield the neuron's activation value. Unlike the perceptron, an MLP can solve linearly ...
... outputs. Each neuron computes a weighted sum of the incoming signals, to yield a net input, and passes this value through its sigmoidal activation function to yield the neuron's activation value. Unlike the perceptron, an MLP can solve linearly ...
Neural Networks
... to start playing you don’t need to know! – many tools, both freeware and commercial off-the-shelf products – some let you train networks and use them with no more knowledge than needed for the real estate appraisal example Slide 29 ...
... to start playing you don’t need to know! – many tools, both freeware and commercial off-the-shelf products – some let you train networks and use them with no more knowledge than needed for the real estate appraisal example Slide 29 ...
Cortical areas are linked through pathways which originate and
... Structural analysis as defined in this study classifies areas into a few cortical types, determined by the number of identifiable layers in each area and by how distinct the layers are from each other. By contrast, cytoarchitectonic analysis is a more detailed process, which identifies cortical type ...
... Structural analysis as defined in this study classifies areas into a few cortical types, determined by the number of identifiable layers in each area and by how distinct the layers are from each other. By contrast, cytoarchitectonic analysis is a more detailed process, which identifies cortical type ...
An Introduction to Variational Methods for Graphical Models
... 1996; Shachter, Andersen, & Szolovits, 1994; Shenoy, 1992); these algorithms take systematic advantage of the conditional independencies present in the joint distribution as inferred from the pattern of missing edges in the graph. We often also wish to calculate marginal probabilities in graphical m ...
... 1996; Shachter, Andersen, & Szolovits, 1994; Shenoy, 1992); these algorithms take systematic advantage of the conditional independencies present in the joint distribution as inferred from the pattern of missing edges in the graph. We often also wish to calculate marginal probabilities in graphical m ...
Hierarchical temporal memory
Hierarchical temporal memory (HTM) is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world.Jeff Hawkins states that HTM does not present any new idea or theory, but combines existing ideas to mimic the neocortex with a simple design that provides a large range of capabilities. HTM combines and extends approaches used in Sparse distributed memory, Bayesian networks, spatial and temporal clustering algorithms, while using a tree-shaped hierarchy of nodes that is common in neural networks.