# US 8,540,518 B2 · Training system and method based on cognitive models > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,540,518 B2 - Document ID: US8540518B2 - Status: Granted - Kind: B2 - Application number: 12/606,808 - Filed: 2009-10-27 - Published: 2011-04-28 - Granted: 2013-09-24 - Earliest claimed: 2009-10-27 - Assignees: Honeywell International Inc. - Applicants: Anand Tharanathan; Harl Thiruvengada - Inventors: Anand Tharanathan; Harl Thiruvengada - Web page: https://patentgrep.com/patent/US8540518B2 ## CPC - G09B 5/00: Electrically-operated educational appliances (working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F) - G09B 7/00: Electrically-operated teaching apparatus or devices working with questions and answers (mechanically operated G09B3/00; computing arrangements G06F) - G09B 19/00: Teaching not covered by other main groups of this subclass (teaching or practice apparatus for gun-aiming or gun-laying F41G3/26) - G09B: EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B) ## Abstract A training system and method for measuring, evaluating, and improving the functional efficiency of information processing stages associated with human cognition. Scene dependent and a-priori queries can be created as a part of a training curriculum and an appropriate measuring technique can be executed with respect to each scene to measure the functional efficiency of the cognitive information processing stages. Thereafter, a trainee's response with respect to such queries can be automatically evaluated. Feedback based on the response can then be generated. An adaptive training mechanism can be configured to enhance the functional efficiency of the cognitive information processing stages. ## Claims ### Claim 1 An automated training method, said method comprising: measuring a performance of a trainee with respect to a plurality of cognitive information processing stages and in association with a simulation environment and configuring at least one scene, wherein a-priori generated queries and scene dependent queries that are relevant to a current task are dynamically presented to measure said functional efficiency of said plurality of cognitive information processing stages by executing a non-transitory computer readable program instruction in a data processing apparatus, in order to derive performance data and thereafter evaluate a functional efficiency of said plurality of cognitive information processing stages in real-time based on an action of said trainee; automatically providing real-time feedback to said trainee based on said performance data with respect to said plurality of cognitive information processing stage by executing a non-transitory computer readable program instruction in a data processing apparatus; and dynamically generating at least one scene among a plurality of scenes with a level of complexity based on said measured performance data indicative of said functional efficiency of said plurality of cognitive information processing stages, wherein said at least one generated scene is configured to train a plurality of low level skills necessary for building toward a higher level skill, by executing a non-transitory computer readable program instruction in a data processing apparatus. ### Claim 2 (depends on 1) The method of claim 1 further comprising enhancing said functional efficiency of said plurality of cognitive information processing stages utilizing an adaptive training mechanism in order to dynamically generate said at least one scene among said plurality of scenes with said level of complexity based on said functional efficiency of said plurality of said cognitive information processing by executing a non-transitory computer readable program instruction in a data processing apparatus. ### Claim 3 (depends on 1) The method of claim 1 further comprising configuring said plurality of scenes to include said at least one scene that varies in skill type and complexity in order to train said trainee to achieve a high level skill. ### Claim 4 (depends on 3) The method of claim 3 further comprising integrating said plurality of scenes in a logical sequence to create a scenario for training said trainee to achieve said high level skill. ### Claim 5 (depends on 1) The method of claim 1 further comprising dynamic margins to assess a level of said functional efficiency with reference to an acceptable level. ### Claim 6 (depends on 1) The method of claim 1 further comprising storing a response to said a-priori generated queries in a database to record accuracy and latency associated with said response for future analysis by executing a non-transitory computer readable program instruction in a data processing apparatus. ### Claim 7 (depends on 1) The method of claim 1 further comprising evaluating said recorded response with respect to an ideal case of null error and null latency. ### Claim 8 (depends on 7) The method of claim 7 wherein providing an automated real-time feedback based on said performance data, further comprises: configuring said automated real-time feedback to benchmark said trainee performance against said ideal case of null error and null latency by executing a non-transitory computer readable program instruction in a data processing apparatus. ### Claim 9 (depends on 1) The method of claim 1 further comprising configuring said adaptive training mechanism to vary a complexity of said plurality of scenes depending on said functional efficiency of said cognitive information processing stages. ### Claim 10 (depends on 1) The method of claim 1 wherein said plurality of cognitive information processing stages includes at least one of the following stages: an information acquisition stage; an information analysis stage; and a decision making and action selection stage. ### Claim 11 An automated training system, said system comprising: a processor; a data bus coupled to said processor; and a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for: measuring a performance of a trainee with respect to a plurality of cognitive information processing stages and in association with a simulation environment in order to derive performance data and thereafter evaluate a functional efficiency of said plurality of cognitive information processing stages in real-time based an action of said trainee; modifying at least one scene, wherein a-priori generated queries and scene dependent queries that are relevant to a current task are dynamically presented to measure said functional efficiency of said plurality of cognitive information processing stages; automatically providing real-time feedback to said trainee based on said performance data with respect to said plurality of cognitive information processing stages; and dynamically generating at least one scene among a plurality of scenes with a level of complexity based on said measured performance data indicative of said functional efficiency of said plurality of cognitive information processing stages, wherein said at least one generated scene is configured to train a plurality of low level skills necessary for building toward a higher level skill. ### Claim 12 (depends on 11) The system of claim 11 wherein said instructions are further configured for: enhancing said functional efficiency of said plurality of cognitive information processing stages utilizing an adaptive training mechanism in order to dynamically generate said at least one scene among said plurality of scenes with said level of complexity based on said functional efficiency of said plurality of said cognitive information processing; configuring said plurality of scenes to include said at least one scene that varies in skill and complexity in order to train said trainee to achieve a high level skill; and integrating said plurality of scenes in a logical sequence to create a scenario for training said trainee to achieve said high level skill. ### Claim 13 (depends on 11) The system of claim 11 wherein said instructions are further configured for: storing a response to said a-priori generated queries in a database to record accuracy and latency associated with said response for future analysis; and evaluating said recorded response with respect to an ideal case of null error and null latency. ### Claim 14 (depends on 11) The system of claim 11 wherein said instructions for providing an automated real-time feedback based on said performance data are further configured for: modifying said automated real-time feedback to benchmark said trainee performance against said ideal case of null error and null latency. ### Claim 15 (depends on 11) The system of claim 11 wherein said instructions are further configured for modifying said adaptive training mechanism to vary a complexity of said plurality of scenes depending on said functional efficiency of said cognitive information processing stages. ### Claim 16 A non-transitory computer-usable medium for automated training, said computer-usable medium embodying computer program code, said computer program code comprising computer executable instructions configured for: measuring a performance of a trainee with respect to a plurality of cognitive information processing stages and in association with a simulation environment in order to derive performance data and thereafter evaluate a functional efficiency of said plurality of cognitive information processing stages in real-time based an action of said trainee; modifying at least one scene, wherein a-priori generated queries and scene dependent queries that are relevant to a current task are dynamically presented to measure said functional efficiency of said plurality of cognitive information processing stages; automatically providing real-time feedback to said trainee based on said performance data with respect to said plurality of cognitive information processing stages; and dynamically generating at least one scene among a plurality of scenes with a level of complexity based on said measured performance data indicative of said functional efficiency of said plurality of cognitive information processing stages, wherein said at least one generated scene is configured to train a plurality of low level skills necessary for building toward a higher level skill. ### Claim 17 (depends on 16) The computer-usable medium of claim 16 wherein said embodied computer program code further comprises computer executable instructions configured for enhancing said functional efficiency of said plurality of cognitive information processing stages utilizing an adaptive training mechanism in order to dynamically generate said at least one scene among said plurality of scenes with said level of complexity based on said functional efficiency of said plurality of said cognitive information processing. ### Claim 18 (depends on 16) The computer-usable medium of claim 16 wherein said embodied computer program code further comprises computer executable instructions configured for modifying said plurality of scenes to include said at least one scene that varies in skill type and complexity in order to train said trainee to achieve a high level skill.