Case-based Reasoning in Agent-based Decision Support System
... chaining algorithms. Forward chaining is an example of the general concept of data-driven reasoning - that is, reasoning in which the focus of attention starts with the known data. It can be used within an agent to derive conclusions from incoming percepts, often without a specific query in mind. Ne ...
... chaining algorithms. Forward chaining is an example of the general concept of data-driven reasoning - that is, reasoning in which the focus of attention starts with the known data. It can be used within an agent to derive conclusions from incoming percepts, often without a specific query in mind. Ne ...
Person Movement Prediction Using Neural Networks
... applications, where virtual images must be continuously stabilized in space against the user’s head motion in a head-mounted display. Latencies in head-motion compensation cause virtual objects to swim around instead of being stable in space. To address this problem, Aguilar et. al. used machine lea ...
... applications, where virtual images must be continuously stabilized in space against the user’s head motion in a head-mounted display. Latencies in head-motion compensation cause virtual objects to swim around instead of being stable in space. To address this problem, Aguilar et. al. used machine lea ...
Partially observable Markov decision processes for
... the musician is playing. There are 25 states, one for each musical key and an inactive state which indicates that the musician is not playing. The parameter O is a set containing the discrete observations that the agent can make. In the TIS, the observations are the possible outputs of the keyfindin ...
... the musician is playing. There are 25 states, one for each musical key and an inactive state which indicates that the musician is not playing. The parameter O is a set containing the discrete observations that the agent can make. In the TIS, the observations are the possible outputs of the keyfindin ...
Spinal Sensorimotor System: An Overview
... network organization of the system. Think of Part I as a sort of “systems level over-view” of the topic. In it I will try to identify some key issues for EC-based network design. Spinal Cord Organization It’s probably no surprise that we should begin with the spinal cord itself, since this structure ...
... network organization of the system. Think of Part I as a sort of “systems level over-view” of the topic. In it I will try to identify some key issues for EC-based network design. Spinal Cord Organization It’s probably no surprise that we should begin with the spinal cord itself, since this structure ...
Heterogeneous Suppression of Sequential Effects in Random
... deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of par ...
... deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of par ...
artificial neural network circuit for spectral pattern recognition
... Different applications often have different requirements, especially when it comes to speed. One of the circuits implemented in this thesis is plant disease classification using reflectance spectra. The ANN is trained to look at reflectance spectra of the leaves and decide if the leaves are healthy ...
... Different applications often have different requirements, especially when it comes to speed. One of the circuits implemented in this thesis is plant disease classification using reflectance spectra. The ANN is trained to look at reflectance spectra of the leaves and decide if the leaves are healthy ...
Visual Event Classification via Force Dynamics Jeffrey Mark Siskind
... These systems follow the tradition of linguists and cognitive scientists, such as Leech (1969), Miller (1972), Schank (1973), Jackendoff (1983), or Pinker (1989), that represent the lexical semantics of verbs via the causal, aspectual, and directional qualities of motion. Some linguists and cognitiv ...
... These systems follow the tradition of linguists and cognitive scientists, such as Leech (1969), Miller (1972), Schank (1973), Jackendoff (1983), or Pinker (1989), that represent the lexical semantics of verbs via the causal, aspectual, and directional qualities of motion. Some linguists and cognitiv ...
Multi-objective optimization of support vector machines
... b` − `/Lc i.i.d. patterns. Although the bias is low, the variance may not be, in particular for large L. Therefore, and for reasons of computational complexity, moderate choices of L (e.g., 5 or 10) are usually preferred [31]. It can be reasonable to split the classification performance into false n ...
... b` − `/Lc i.i.d. patterns. Although the bias is low, the variance may not be, in particular for large L. Therefore, and for reasons of computational complexity, moderate choices of L (e.g., 5 or 10) are usually preferred [31]. It can be reasonable to split the classification performance into false n ...
as a PDF - Idiap Publications
... weighted log-likelihoods of the client and the world output distributions. Since the discriminative criterion is mainly based on the idea that the predominant information in the measured features is relative to the speaker, a problem exists when decoding with a silence. These parts of the signal do ...
... weighted log-likelihoods of the client and the world output distributions. Since the discriminative criterion is mainly based on the idea that the predominant information in the measured features is relative to the speaker, a problem exists when decoding with a silence. These parts of the signal do ...
Aalborg Universitet Inference in hybrid Bayesian networks
... models, the analyst can employ different sources of information, e.g., historical data or expert judgement. Since both of these sources of information can have low quality, as well as come with a cost, one would like the modelling framework to use the available information as efficiently as possible ...
... models, the analyst can employ different sources of information, e.g., historical data or expert judgement. Since both of these sources of information can have low quality, as well as come with a cost, one would like the modelling framework to use the available information as efficiently as possible ...
PDF
... enough to fulfill the switching role we seek. As a result, neuromodulation is not generally considered to be a candidate mechanism for rapid and precise switching of complex neural circuits and responses. Nevertheless, it is good to keep in mind that this standard wisdom may be wrong (see Sherman an ...
... enough to fulfill the switching role we seek. As a result, neuromodulation is not generally considered to be a candidate mechanism for rapid and precise switching of complex neural circuits and responses. Nevertheless, it is good to keep in mind that this standard wisdom may be wrong (see Sherman an ...
position tracking system to find shortest path to object using
... stochastic problem with an additional probabilistic weight on each node. Peter Hart, Nils Nilssons and Bertram Raphael in 1968 gave the A* search algorithm that solves for single pair shortest path using heuristic to try to speed up the search. Donald B. Johnson in 1977 gave the Johnson’s algorithm ...
... stochastic problem with an additional probabilistic weight on each node. Peter Hart, Nils Nilssons and Bertram Raphael in 1968 gave the A* search algorithm that solves for single pair shortest path using heuristic to try to speed up the search. Donald B. Johnson in 1977 gave the Johnson’s algorithm ...
Text - ETH E
... Fig. 1. (A) Temporal stimulus representation. A stimulus uðtÞ is represented as a signal that is one during presentation of this stimulus and zero otherwise. The temporal stimulus representation of this stimulus u(t ) consists of a series of phasic signals x1 ðtÞ; x2 ðtÞ; x3 ðtÞ; … that cover trial ...
... Fig. 1. (A) Temporal stimulus representation. A stimulus uðtÞ is represented as a signal that is one during presentation of this stimulus and zero otherwise. The temporal stimulus representation of this stimulus u(t ) consists of a series of phasic signals x1 ðtÞ; x2 ðtÞ; x3 ðtÞ; … that cover trial ...