Thinking Machines Corporation

G7 Research LLC

Stephen J Smith

Frederick Myers

Brij M Masand

A system and method for optimizing learning and retention of items learned over time maps bodies of knowledge to physical metaphors in an education computer game or simulation. Entire structured curricula or curriculum frameworks are mapped to isomorphic physical metaphor hierarchies. Recommended sequences through subject matter are mapped to sequences in the physical metaphor of the game or simulation. Various algorithms for computing the well-known Ebbinghaus 'spacing effect' for reviewing items that are about to be forgotten by a student to optimize his or her retention of subject matter are mapped to physical metaphors in the game or simulation. The use of a 'predator-prey' computer algorithm to find students' subject matter knowledge weak points is mapped to a physical metaphor in the game or simulation. Similarly, devices to enhance the student's learning curve, such as to induce perseverance, or raise motivation via competition, or via praise from an authority figure, are mapped to physical metaphors in the game or simulation.

System and method for optimizing learning by correlating structured knowledge and learning techniques with physical metaphors in an educational computer game

A partition establishment arrangement for use in a computer system comprising a plurality of processors interconnected by a communications network. The communications network comprises a plurality of communications nodes connected in a series of levels, with the nodes of at least some of the levels being controllable to connect to multiple ones of the nodes in a subsequent level. The partition establishment arrangement determines the controlling of the communication nodes to facilitate the partitioning of the processors into a plurality of partitions. The partition establishment arrangement, in a plurality of iterations, identifies conflict sets of processors to be assigned to respective partitions at a level, each conflict set identifying partitions for which, at a selected level, a processor may be connected to the same communications nodes in the next level. In each iteration, a level processing portion determines a control value for controlling the communications nodes in response to the conflict sets identified for the level. The operations continue through each of the successive levels.

System and method for partitioning a massively parallel computer system

Classification of natural language data wherein the natural language data has an open-ended range of possible values or the data values do not have a relative order. A training database stores training records, wherein each training record includes predictor data fields. Each predictor data field containes a feature, wherein each feature is a natural language term, and a target data field containing a target value representing a classification of the record. Features may also include conjunctions of natural language terms and each feature may also be a member of a category subset of features. The training database stores, for each feature, a probability weight value representing the probability that a record will have the target value contained in the target data field if a feature contained in a corresponding predictor data field occurs in the record. Features are extracted from a new record and each feature from the new record is used to query the training records to determine the probability weights from the training records having matching features. The probability weights are accumulated for each training record to determine a comparison score representing the probability that the training record matches the new record and provide an output indicating the training records most probability matching the new record.

Classification of data records by comparison of records to a training

A character recognition system for recognizing a character associated with a query character. The query character has a query character image defined by a query character image array having a pattern of array elements defining on pixels and off pixels for said query character image, in response to training character images also represented by patterns of on and off pixels. The system generates, for each image array, a distance array having a pattern of array elements each identifying a distance value to pixels of selected conditions, thereby identifying distances to artifacts in the respective images. In addition, the system generates distance scores for both the query character and the training character, using the distance arrays, representing the consolidated deviation between the query character image and the training character images. The system includes a massively-parallel processor including a plurality of processing elements to process the training character image arrays in parallel.

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Lynnfield, MA, United States of America

Stephen J Smith