Abstract: A method for generating optimized tinnitus masks includes, for example, presenting stimuli in succession to a user, receiving the user's rating of the effectiveness of each presented stimulus in reducing tinnitus, selecting a subset of the stimuli to maintain as tinnitus masks, and, generating variant stimuli from the subset of the stimuli that is maintained as tinnitus masks.

Abstract: One aspect of the invention is a method for identifying at least one property of data. An example of the method includes receiving data, and making assessments regarding the data. The method also includes applying at least one behavioral operator, and outputting results. The method further comprises receiving feedback concerning system performance. Additionally, the method includes adjusting at least one parameter based on the feedback received concerning system performance, wherein the at least one parameter is a parameter of a machine learning method.

Abstract: One aspect of the invention is a method for assigning categorical data to a plurality of clusters. The method may include identifying a plurality of categories associated with the data. The method also may include, for each category in the plurality of categories, identifying at least one element associated with the category. The method also may include specifying a number of clusters to which the data may be assigned. The method additionally may include assigning at least some of the data, wherein each assigned datum is assigned to a respective one of the clusters. The method further may include, for at least one of the clusters, determining, for at least one category, the frequency in data assigned to the cluster of at least one element associated with the category. Further, the invention may provide for detecting outliers, anomalies, and exemplars in the categorical data.

Abstract: One aspect of the invention is a method for identifying at least one property of data. An example of the method includes receiving data, and making assessments regarding the data. The method also includes applying at least one behavioral operator, and outputting results. The method further comprises receiving feedback concerning system performance. Additionally, the method includes adjusting at least one parameter based on the feedback received concerning system performance, wherein the at least one parameter is a parameter of a machine learning method.

Abstract: One aspect of the invention is a method for identifying at least one property of data. An example of the method includes receiving data, and making assessments regarding the data. The method also includes applying at least one behavioral operator, and outputting results. The method further comprises receiving feedback concerning system performance. Additionally, the method includes adjusting at least one parameter based on the feedback received concerning system performance, wherein the at least one parameter is a parameter of a machine learning method.

Abstract: One aspect of the invention is a method for assigning categorical data to a plurality of clusters. An example of the method includes identifying a plurality of categories associated with the data. This example also includes, for each category in the plurality of categories, identifying at least one element associated with the category. This example also includes specifying a number of clusters to which the data may be assigned. This example additionally includes assigning at least some of the data, wherein each assigned datum is assigned to a respective one of the clusters. This example further includes, for at least one of the clusters, determining, for at least one category, the frequency in data assigned to the cluster of at least one element associated with the category. Further, some examples of the invention provide for detecting outliers, anomalies, and exemplars in the categorical data.

Abstract: One aspect of the invention is a method for assigning categorical data to a plurality of clusters. An example of the method includes identifying a plurality of categories associated with the data. This example also includes, for each category in the plurality of categories, identifying at least one element associated with the category. This example also includes specifying a number of clusters to which the data may be assigned. This example additionally includes assigning at least some of the data, wherein each assigned datum is assigned to a respective one of the clusters. This example further includes, for at least one of the clusters, determining, for at least one category, the frequency in data assigned to the cluster of at least one element associated with the category. Further, some examples of the invention provide for detecting outliers, anomalies, and exemplars in the categorical data.

Abstract: One aspect of the invention is a method for assigning categorical data to a plurality of clusters. The method includes identifying a plurality of categories associated with the data. The method also includes, for each category in the plurality of categories, identifying at least one element associated with the category. The method also includes specifying a number of clusters to which the data may be assigned. The method additionally includes assigning at least some of the data, wherein each assigned datum is assigned to a respective one of the clusters. The method further includes, for at least one of the clusters, determining, for at least one category, the frequency in data assigned to the cluster of at least one element associated with the category. Further, the invention provides for detecting outliers, anomalies, and exemplars in the categorical data.

Abstract: One aspect of the invention is a method for identifying at least one property of data. An example of the method includes receiving data, and making assessments regarding the data. The method also includes applying at least one behavioral operator, and outputting results. The method further comprises receiving feedback concerning system performance. Additionally, the method includes adjusting at least one parameter based on the feedback received concerning system performance, wherein the at least one parameter is a parameter of a machine learning method.

Abstract: A computer program that indicates lexical impact of various words and phrases in a text, measures the overall lexical impact of the text, and suggests alternatives for various words and phrases of the text. The computer program may include a ranked thesaurus for listing alternative words and phrases (e.g., synonyms, antonyms, related), along with an indication of their relative lexical impacts. The thesaurus may alternatively rank words and phrases according to other ranking systems.

Abstract: One aspect of the invention is a method for identifying at least one property of data. An example of the method includes receiving data, and making assessments regarding the data. The method also includes applying at least one behavioral operator, and outputting results. The method further comprises receiving feedback concerning system performance. Additionally, the method includes adjusting at least one parameter based on the feedback received concerning system performance, wherein the at least one parameter is a parameter of a machine learning method.

Abstract: A method for generating optimized tinnitus masks includes, for example, presenting stimuli in succession to a user, receiving the user's rating of the effectiveness of each presented stimulus in reducing tinnitus, selecting a subset of the stimuli to maintain as tinnitus masks, and, generating variant stimuli from the subset of the stimuli that is maintained as tinnitus masks.

Abstract: One aspect of the invention is a method for presenting a virtual reality setting for an interaction. An example of the method includes presenting a streaming video of a real-world background scene, and presenting a series of individual video clips that are joined into the appearance of a continuous streaming image of a real-world character. The method also includes inputting an operator's choice of action or inaction, and updating a current state based on the operator's action or inaction. The method further includes using the current state by a decision logic to determine a response in the setting by the character, and using the current state by the decision logic to determine a selection of how to control video of the character and how to control video of the background. The method may also include simultaneously presenting a three-dimensional representation and a two-dimensional representation of a playing area.

Abstract: A server-based video game system maintains a number of video game characters having computer-simulated genetic (“digenetic”) structures that prescribe a number of physical and cognitive performance traits and characteristics for the video game characters. The system allows end users to establish remote online access to the game characters (via, e.g., the Internet). The results of competitions and training activities are based upon the game characters' digenetics, the conditions of the game environment, and the game characters' current levels of physical and cognitive development. The game characters' performance capabilities and cognition are updated continuously in response to the results of competitions and training activities. Competition and training results can be processed by the game servers and transmitted to the end user presentation devices for graphics rendering. In this manner, the video game system need not be burdened by network latency and other delays.

Abstract: A server-based video game system maintains a number of video game characters having computer-simulated genetic (“digenetic”) structures that prescribe a number of physical and cognitive performance traits and characteristics for the video game characters. The system allows end users to establish remote online access to the game characters (via, e.g., the Internet). The results of competitions and training activities are based upon the game characters' digenetics, the conditions of the game environment, and the game characters' current levels of physical and cognitive development. The game characters' performance capabilities and cognition are updated continuously in response to the results of competitions and training activities. Competition and training results can be processed by the game servers and transmitted to the end user presentation devices for graphics rendering. In this manner, the video game system need not be burdened by network latency and other delays.

Abstract: A computer program that indicates lexical impact of various words and phrases in a text, measures the overall lexical impact of the text, and suggests alternatives for various words and phrases of the text. The computer program may include a ranked thesaurus for listing alternative words and phrases (e.g., synonyms, antonyms, related), along with an indication of their relative lexical impacts. The thesaurus may alternatively rank words and phrases according to other ranking systems.

Abstract: A computer program that indicates lexical impact of various words and phrases in a text, measures the overall lexical impact of the text, and suggests alternatives for various words and phrases of the text. The computer program may include a ranked thesaurus for listing alternative words and phrases (e.g., synonyms, antonyms, related), along with an indication of their relative lexical impacts. The thesaurus may alternatively rank words and phrases according to other ranking systems.

Abstract: A server-based video game system maintains a number of video game characters having computer-simulated genetic (“digenetic”) structures that prescribe a number of physical and cognitive performance traits and characteristics for the video game characters. The system allows end users to establish remote online access to the game characters (via, e.g., the Internet). The results of competitions and training activities are based upon the game characters' digenetics, the conditions of the game environment, and the game characters' current levels of physical and cognitive development. The game characters' performance capabilities and cognition are updated continuously in response to the results of competitions and training activities. Competition and training results can be processed by the game servers and transmitted to the end user presentation devices for graphics rendering. In this manner, the video game system need not be burdened by network latency and other delays.

Abstract: A server-based video game system maintains a number of video game characters having computer-simulated genetic (“digenetic”) structures that prescribe a number of physical and cognitive performance traits and characteristics for the video game characters. The system allows end users to establish remote online access to the game characters (via, e.g., the Internet). The results of competitions and training activities are based upon the game characters' digenetics, the conditions of the game environment, and the game characters' current levels of physical and cognitive development. The game characters' performance capabilities and cognition are updated continuously in response to the results of competitions and training activities. Competition and training results can be processed by the game servers and transmitted to the end user presentation devices for graphics rendering. In this manner, the video game system need not be burdened by network latency and other delays.

Abstract: A method and apparatus for training neural networks using evolutionary programming. A network is adjusted to operate in a weighted configuration defined by a set of weight values and a plurality of training patterns are input to the network to generate evaluations of the training patterns as network outputs. Each evaluation is compared to a desired output to obtain a corresponding error. From all of the errors, an overall error value corresponding to the set of weight values is determined. The above steps are repeated with different weighted configurations to obtain a plurality of overall error values. Then, for each set of weight values, a score is determined by selecting error comparison values from a predetermined variable probability distribution and comparing them to the corresponding overall error value. A predetermined number of the sets of weight values determined to have the best scores are selected and copies are made.