Systems and methods to provide training guidance

1. A computer based method for an adaptive computer based training simulator to automatically determine and communicate a training environment and a training content to a trainee, the method comprising:

receiving, at an assessment subsystem, a training requirement comprising a training outcome and a training configuration:

wherein the training outcome is selected from a plurality of predetermined training outcomes, and

wherein the step of selecting the training outcome from a plurality of predetermined training outcomes comprises:

selecting a training configuration from a list of predetermined training configurations, and

each of the predetermined training configurations having a relevancy value to each of the plurality of predetermined training outcomes whereby selecting the training configuration selects the training outcome;

the training configuration defining a trainee state;

determining, at the assessment subsystem, a training environment based on a relevancy function of the training environment to the training outcome;

the relevancy function of the training environment to the training outcome defining a relevancy value for each of the predetermined training outcomes to each of a plurality of the training environments,

the step of determining the training environment based on a relevancy function of the training environment to the training outcome comprises selecting the training environment having the highest relevancy value to the training outcome, and

wherein the relevancy function of the training environment to the training outcome comprises a best fit curve;

determining, with a training management subsystem, a training content based on a relationship function of the training content to the trainee state;

wherein the relationship function of the training content to the trainee state defining a relationship value for the trainee state to each of a plurality of the training contents,

wherein the step of determining the training content based on a relationship function of the training content to the trainee state comprises selecting the training content having the highest relationship value to the trainee state,

wherein the highest relationship value to the trainee state is defined by the relationship function of the training content to the trainee state, and

wherein the relationship function of the training content to the trainee state comprises a Partially Observable Markov Decision Process (POMDP) model;

determining a training solution comprising the training environment and the training content:

wherein the training solution comprises a computer based training simulator having a training configuration configured to communicate the training environment and the training content to the trainee through a user interface of the computer based training simulator;

communicating the training environment and the training content to the trainee through the user interface of the computer based training simulator;

receiving, through the user interface of the computer based training simulator, a response of the trainee to the training content;

communicating, to the training management subsystem, the response as an observation of the trainee to the training content;

updating, with the training management subsystem, the trainee state to an updated trainee state based on the observation and a relationship function of the trainee state to the observation;

determining, with the training management subsystem, a subsequent training content based on the updated trainee state and the POMDP model;

determining, with the assessment subsystem, a subsequent training environment based on the updated trainee state and a relationship function of the training environment to the trainee state;

communicating the subsequent training environment and the subsequent training content to the trainee through the user interface of the computer based training simulator;

the computer based training simulator having a characteristic of a fidelity of the computer based training simulator; and

the relevancy function of the training environment to the training outcome defining a relevancy value for the fidelity of the computer based training simulator to the training outcome.

2. The computer based method of claim 1 wherein the training configuration comprises one selected from a group of predetermined training configurations consisting of:

a platform;

a role and experience;

a training type; and

an experience.

3. The computer based method of claim 1 wherein the training outcome comprises one selected from a group of predetermined training requirements consisting of:

a competency;

a knowledge and skill; and

a training content.

4. The computer based method of claim 1 further comprising:

receiving a performance value of the training solution; and

updating the relationship function of the training content to the trainee state using a machine learning technique and the performance value.

5. A training guidance system for determining a training solution, the training guidance system comprising:

a processor;

a non-transitory computer readable medium having a computer readable program code embodied therein, said computer readable program code configured to be executed to implement the method to automatically determine a training simulator to communicate a training environment and a training content to a trainee of claim 1 .

6. The computer based method of claim 1 , wherein:

the training environment comprises an interface to a computer based training simulator; and

the training content comprises a computer based scenario presented by the user interface.

7. The computer based method of claim 1 wherein the step of receiving a training requirement comprises receiving a training requirement from a learning management system.

8. The computer based method of claim 1 further comprising:

receiving a performance value of the training solution; and

updating the relevancy function of the training environment to the trainee state using the performance value and a machine learning technique.

9. The training guidance system of claim 5 , the training guidance system further comprising:

receiving a performance value of the training solution; and

updating the relevancy function of the training environment to the trainee state using the performance value and a machine learning technique.

10. The computer based method of claim 1 wherein the step of updating, with the training management subsystem, the trainee state to an updated trainee state based on the observation and a relationship function of the trainee state to the observation comprises:

updating the trainee state to an updated trainee state wherein the observation comprises a representation of the response of the trainee;

wherein the relationship function of the trainee state to the observation comprises an observation probability function of O(o|s′, a, s′) wherein:

o is the observation;

s′ is the updated trainee state;

a is the training content; and

solving the observation probability function for s′ as an output representing the updated trainee state.

11. The computer based method of claim 1 wherein the step of determining, with the training management subsystem, a subsequent training content based on the updated trainee state and a relationship function of the training content to the trainee state comprises:

determining the subsequent training content based on the updated trainee state wherein

the relationship function of the training environment to the trainee state comprises a reward function of R(s′, a) wherein:

s′ is the updated trainee state;

a is the training content; and

determining a reward function value for the updated trainee state given the training content; and

selecting the training content with a highest reward function value as the subsequent training content.

12. The computer based method of claim 1 wherein the step of determining, with the assessment subsystem, a subsequent training environment based on the updated trainee state and a relationship function of the training environment to the trainee state comprises:

determining the subsequent training content based on the updated trainee state;

determining the subsequent training environment based on the relationship function of the training environment to the trainee state; and

the relationship function of the training environment to the trainee state comprises a best fit curve of the subsequent training configuration to the subsequent training content.