Abstract: Disclosed is a method and system for the use of virtual robots (Bots) to assist in the answering of inquiries from persons over the Internet, telephone, wireless, or other form of electrical, digital, or electronic communication. Such method and system consists of (1) a Bot processor consisting of (a) a connection interface capable of receiving, directly or indirectly, inputs from a user in natural or machine language, which the Bot processor then responds to in natural or machine language, and (b) an engine capable of recognizing an input and providing a response; and (2) a service desk consisting of (a) a human being, (b) a connection interface that connects directly or indirectly to the Bot processor and to the front end, and (c) a display where the human being can see, in humanly comprehensible form, information transmitted by the user and/or the Bot processor.

Abstract: A programmable logic unit (e.g., an ASIC or FPGA) having a feedforward linear associative memory (LAM) neural network checking circuit which classifies input vectors to a faulty hardware block as either good or not good and, when a new input vector is classified as not good, blocks a corresponding output vector of the faulty hardware block, enables a software work-around for the new input vector, and accepts the software work-around input as the output vector of the programmable logic circuit. The feedforward LAM neural network checking circuit has a weight matrix whose elements are based on a set of known bad input vectors for said faulty hardware block. The feedforward LAM neural network checking circuit may update the weight matrix online using one or more additional bad input vectors. A discrete Hopfield algorithm is used to calculate the weight matrix W.

Abstract: In an embodiment, a system and method provide a constraint on a genetic algorithm, and further provide dynamic programming capability to the genetic algorithm. The system and method then allocate load demand over a finite number of time intervals among a number of power generating units as a function of the constraint on the genetic algorithm and the dynamic programming capability of the genetic algorithm.

Abstract: A method for the autonomic management of autonomic systems can include monitoring a managed system and recommending a course of action to be performed in the managed system. It can be determined whether the recommended course of action has been performed by an administrator. Responsive to the determination, it further can be determined whether an outcome from the course of action comports with a predicted outcome. If so, a point count can be changed responsive to a further determination that the outcome from the course of action comports with the predicted outcome. Conversely, the point count can be oppositely changed responsive to a further determination that the outcome from the course of action does not comports with the predicted outcome. In any case, when the point count crosses a threshold value, the management of the managed system can be transitioned to an adaptive component.

Abstract: An improvement in a computer-implemented rule processing method that provides conflict or selection advice to help guide a user achieve satisfiability of a business or engineering rule represented by a zero-suppressed binary decision diagram (ZDD) rule model. The improvement comprises obtaining at least one Exclude ZDD rule component from the ZDD rule model, identifying covers within the Exclude ZDD rule component, removing covers identified in the identifying step thereby to produce abridged Exclude ZDD rule component, determining satisfiability of the rule model utilizing the abridged Exclude ZDD component, and utilizing results of the determining step during automated decision support to help guide the user to attain satisfiability of the rule. An apparatus that implements the aforementioned method is also disclosed.

Abstract: In one embodiment, a computer system performs a method for verifying the validity or invalidity of a software routine by learning appropriate invariants at each program point. A computer system chooses an abstract domain that is sufficiently precise to express the appropriate invariants. The computer system associates an inconsistency measure with any two abstract elements of the abstract domain. The computer system searches for a set of local invariants configured to optimize a total inconsistency measure which includes a sum of local inconsistency measures. The computer system optimizes the total inconsistency measure for all input/output pairs of the software routine. In one embodiment, the optimization of total inconsistency is achieved by the computer system which repeatedly replaces a locally inconsistent invariant with a new invariant, randomly selected among the possible invariants which are locally less inconsistent with the current invariants at the neighboring program points.

Abstract: Embodiments herein provide a method, computer program product, etc. of measuring a large population of web pages for compliance to content standards that require human judgment to evaluate. The method performs an automated analysis of a web space, comprising gathering information about structure and content of the web space. The performing of the automated analysis further comprises creating first data and second data. Specifically, the creating of the first data comprises creating page-relationship data based on a directory tree structure of servers in the web space or link distances amongst pages in the web space. The creating of the second data comprises analyzing web page content, comprising creating compliance-indicating data and/or content structure data for pages in the web space. In addition, the performing of the automated analysis can comprise performing the automated analysis on a web space that lacks objective standards violations that can be identified using software.

Abstract: Conventional robot apparatus etc. can not perform name-learning naturally. Learning the name of an object is performed such a manner that the name of a target object is obtained through dialog with a human being, the name is stored in association with plural items of different characteristic data detected for the target object, and a new object is recognized based on the stored data and associative information, the name and characteristic data of the new person are obtained and this associative information is stored.

Abstract: Method of and system for analysing a set of exhaustive and exclusive hypotheses, including assessing and assigning base rates for each hypothesis; determining a set of items of evidence that are relevant to, have a causal influence on, or would disconfirm more than one hypothesis; assessing and assigning base rates for each item of evidence; deciding, for each item of evidence, whether the item should be treated as being a causal influence or diagnostic indicator with respect to the set of the hypotheses; if the item of evidence is to be treated as a causal influence—making a judgement as to the likelihood of each hypothesis, both if the evidence were true, and also if the evidence were false; if the item of evidence is to be treated as a diagnostic indicator—making a judgement as to the evidence being true if the hypothesis were true; assessing the belief for each item of evidence being true; deciding a set of interim beliefs in each hypothesis for each individual item of evidence by: employing a conditio

Abstract: Embodiments of the present invention introduce a novel recursive assembly process to automatically create a library of components. It starts with simple components used as building blocks and proceeds by repeatedly combining these randomly into more complex ones. The utility and quality of these random combinations of components are measured against a set of functional goals. Useful combinations then become new components in the library that can be used as building blocks for further random combination. This description is not intended to be a complete description of, or limit the scope of, the invention. Other features, aspects, and objects of the invention can be obtained from a review of the specification, the figures, and the claims.

Abstract: A computer implemented data processor system automatically disambiguates a contextual meaning of natural language symbols to enable precise meanings to be stored for later retrieval from a natural language database, so that natural language database design is automatic, to enable flexible and efficient natural language interfaces to computers, household appliances and hand-held devices.

Abstract: An agent engine includes a definition process, the definition process operable to define a data set associated with an objective, a library storing a set of components, the components comprising at least one of a pre-programmed application, object, algorithm, function, and data set definition, and an agent generator process, the agent generator process operable to define at least one agent that includes at least one component from the library, the at least one generated agent defined to perform a function related to the objective.

Abstract: The present invention relates to a method for generating a decision tree using an inference engine in a ubiquitous environment. In the method, a data table for a data event set is generated based on information collected by at least one sensor. Subsequently, a weight value of the data event set is established, and an entropy is calculated based on the established weight value (here, the entropy is a scale for classifying the information collected by the sensor into respective classes). In addition, the decision tree for the collected information is formed based on the calculated entropy.

Abstract: Techniques are disclosed that implement algorithms for rapidly finding the leave-one-out (LOO) error for regularized least squares (RLS) problems over a large number of values of the regularization parameter ?. Algorithms implementing the techniques use approximately the same time and space as training a single regularized least squares classifier/regression algorithm. The techniques include a classification/regression process suitable for moderate sized datasets, based on an eigendecomposition of the unregularized kernel matrix. This process is applied to a number of benchmark datasets, to show empirically that accurate classification/regression can be performed using a Gaussian kernel with surprisingly large values of the bandwidth parameter ?. It is further demonstrated how to exploit this large ? regime to obtain a linear-time algorithm, suitable for large datasets, that computes LOO values and sweeps over ?.

Abstract: A method for optimizing an explicative rule including constructing an explicative rule including at least one logical combination of at least one elementary conclusion, each elementary conclusion including a restriction of the domain of a variable; calculating at least one modified explicative rule optimizing the value of one or more quality indicators on a database of examples; and displaying a representation of the rules and corresponding quality indicators.

Abstract: A controller for a plant having a fixed-weight recurrent neural network with at least one external input signal representative of a desired condition of the plant and actual condition of the plant, and an output connected as a control signal to the plant. The fixed recurrent neural network includes a set of nodes with fixed weight interconnections between the nodes and at least one feedback input interconnecting an output from at least one of the nodes to an input of at least one node. These nodes collectively determine the value of the output from the neural network as a function of the input signal and the feedback input. The controller also includes an adaptive neural network having a plurality of nodes with variable weight interconnections between the nodes. A cost input from the plant is connected to the adaptive neural network while an output from the adaptive neural network is coupled as a processed feedback signal to nodes of the fixed-weight recurrent neural network.

Abstract: A system for finding and presenting content items in response to keystrokes entered by a user on an input device having a known layout of overloaded keys selected from a set of key layouts. The system includes (1) a database containing content items and terms characterizing the content items; (2) input logic for receiving keystrokes from the user and building a string corresponding to incremental entries by the user, each item in the string having the set of alphanumeric symbols associated with a corresponding keystroke; (3) mapping logic to map the string to the database to find the most likely content items corresponding to the incremental entries, the mapping logic operating in accordance with a defined error model corresponding to the known layout of overloaded keys; and (4) presentation logic for ordering the most likely content items identified by the mapping logic and for presenting the most likely content items.

Abstract: Natural language dialog elements may be dynamically generated in a virtual world when an interaction is initiated between a user and a computer-controlled character. The dialog elements may be generated by combining abstract semantic representations from a knowledgebase of a computer-controlled character involved in the interaction, with abstract semantic representations from a current state of the virtual world. For example, the abstract semantic representations from the current state of the virtual world may describe the user's progress in accomplishing a set of interrelated goals. A program enables developers of games and other virtual worlds to provide dynamic dialog generation after simply entering natural language descriptions of potential game states and computer-controlled character knowledge.

Abstract: A real time data processing system, method and program product for processing a stream of data events. A system is provided that includes: a running profile processing system for updating a running profile each time a new data event value is inputted, wherein the running profile includes percentile data; and an analysis system for analyzing the running profile, wherein the analysis system performs a composite analysis that utilizes: (a) results obtained from comparing a new data event value to the percentile data, and (b) stored results obtained from previous compare operations.

Abstract: A method and system for capturing emotional preference of human subjects, generating machine-readable emotional code and using the code to optimize computerized searching and matching operations between entities is disclosed. The entity can be a human user, a product, or a service. The emotional code can thus be a universal language expressing human emotion that communicates among entities. After understanding the sending parties' emotional profile, the receiving party can adapt its operation to achieve more optimum results.