Abstract: In one embodiment, the present invention is a method for reward-based learning of improved systems management policies. One embodiment of the inventive method involves supplying a first policy and a reward mechanism. The first policy maps states of at least one component of a data processing system to selected management actions, while the reward mechanism generates numerical measures of value responsive to particular actions (e.g., management actions) performed in particular states of the component(s). The first policy and the reward mechanism are applied to the component(s), and results achieved through this application (e.g., observations of corresponding states, actions and rewards) are processed in accordance with reward-based learning to derive a second policy having improved performance relative to the first policy in at least one state of the component(s).

Abstract: A method, apparatus, and computer instructions for updating a software component. A determination is made as to whether to update the software component. The software component is updated to form an updated software component in response to a determination to update the software component. The updated software component is automatically tested. A corrective action is performed in response to a failure in testing of the updated component.

Abstract: An apparatus, system and method for automatically making operation selling decisions are provided. The apparatus, system and method make use of selling policy rules established by human operators associated with a firm to guide the making of decisions to sell products and/or services. The actual decisions to sell are made automatically by the system without requiring human intervention. The decisions to sell are made by negotiating terms of sale with a customer using history information, exogenous preference information, information obtained from third parties, and the like. An initial offer of sale is provided to a customer who may then elect to modify the terms of sale of the product or service. If the customer elects to modify the terms of sale of the product or service, a negotiation engine of the present invention may automatically provide counteroffers to offers made by the customer until acceptable terms of sale are agreed upon.

Abstract: A method, computer program product, and data processing system for recognizing, tracing, diagnosing, and repairing problems in an autonomic computing system is disclosed. Rules and courses of actions to follow in logging data, in diagnosing faults (or threats of faults), and in treating faults (or threats of faults) are formulated using an adaptive inference and action system. The adaptive inference and action system includes techniques for conflict resolution that generate, prioritize, modify, and remove rules based on environment-specific information, accumulated time-sensitive data, actions taken, and the effectiveness of those actions. Thus, the present invention enables a dynamic, autonomic computing system to formulate its own strategy for self-administration, even in the face of changes in the configuration of the system.

Abstract: In one embodiment, the present invention is a method for allocation of finite computational resources amongst multiple entities, wherein the method is structured to optimize the business value of an enterprise providing computational services. One embodiment of the inventive method involves establishing, for each entity, a service level utility indicative of how much business value is obtained for a given level of computational system performance. The service-level utility for each entity is transformed into a corresponding resource-level utility indicative of how much business value may be obtained for a given set or amount of resources allocated to the entity. The resource-level utilities for each entity are aggregated, and new resource allocations are determined and executed based upon the resource-level utility information. The invention is thereby capable of making rapid allocation decisions, according to time-varying need or value of the resources by each of the entities.

Abstract: An improved method and system for performing dynamic online multi-parameter optimization for autonomic computing systems are provided. With the method and system of the present invention, a simplex, i.e. a set of points in the parameter space that has been directly sampled, is maintained. The system's performance with regard to a particular utility value is measured for the particular setting of configuration parameters associated with each point in the simplex. A new sample point is determined using the geometric transformations of the simplex. The method and system provide mechanisms for limiting the size of the simplex that is generated through these geometric transformations so that the present invention may be implemented in noisy environments in which the same configuration settings may lead to different results with regard to the utility value. In addition, mechanisms are provided for resampling a current best point in the simplex to determine if the environment has changed.

Abstract: A method, computer program product, and data processing system for providing an improved directory service for storing information about hardware and software components is disclosed. The directory service stores not only the information that other hardware and software components require to locate, and make use of, the components listed in the directory, but is also able to dynamically construct ‘meta services’ that fulfill a client's functionality requirements.

Abstract: A method, apparatus, and computer instructions for updating a software component. A determination is made as to whether to update the software component. The software component is updated to form an updated software component in response to a determination to update the software component. The updated software component is automatically tested. A corrective action is performed in response to a failure in testing of the updated component.

Abstract: A method, computer program product, and data processing system for recognizing, tracing, diagnosing, and repairing problems in an autonomic computing system is disclosed. Rules and courses of actions to follow in logging data, in diagnosing faults (or threats of faults), and in treating faults (or threats of faults) are formulated using an adaptive inference and action system. The adaptive inference and action system includes techniques for conflict resolution that generate, prioritize, modify, and remove rules based on environment-specific information, accumulated time-sensitive data, actions taken, and the effectiveness of those actions. Thus, the present invention enables a dynamic, autonomic computing system to formulate its own strategy for self-administration, even in the face of changes in the configuration of the system.

Abstract: An apparatus, system and method for automatically making operation selling decisions are provided. The apparatus, system and method make use of selling policy rules established by human operators associated with a firm to guide the making of decisions to sell products and/or services. The actual decisions to sell are made automatically by the system without requiring human intervention. The decisions to sell are made by negotiating terms of sale with a customer using history information, exogenous preference information, information obtained from third parties, and the like. An initial offer of sale is provided to a customer who may then elect to modify the terms of sale of the product or service. If the customer elects to modify the terms of sale of the product or service, a negotiation engine of the present invention may automatically provide counteroffers to offers made by the customer until acceptable terms of sale are agreed upon.

Abstract: An apparatus, system and method for automatically making operation purchasing decisions are provided. The apparatus, system and method make use of purchasing policy rules established by human operators associated with a firm to guide the making of decisions to purchase products and/or services. The actual decisions to purchase are made automatically by the system without requiring human intervention. The decisions to purchase are made by evaluating the possible vendors to identify a set of vendors from which the product or service may be obtained. From this set of vendors, one or more vendors are selected from which to purchase the desired product or service. The selection of these one or more vendors may be based on the established rules, information obtained about each vendor, and the results of negotiation with the vendors. Because the actual decisions are performed automatically without human intervention, the decisions may be made much more quickly than would have been done by a human being.

Abstract: Automatic electronic bidding for goods or services. In one embodiment, the history of bids or asks is examined to determine which have resulted in trades within a prescribed span of time. This information plus, possibly, some additional auxiliary information is used to estimate, for one or more candidate prices within a prescribed range, the likelihood for a bid or ask at that price to result in a trade; an optimal price is selected using this set of bid/ask prices and trade probabilities plus additional information about privately held information about reservation prices, etc. to compute an optimal bid/ask price or modify an existing bid/ask; and the auctioneer is sent a message conveying the chosen new or modified optimal bid/ask price.