A computer-implemented method includes recording, with a three-dimensional camera, one or more demonstrations of a user performing one or more reaching tasks. Training data is computed to describe the one or more demonstrations. One or more weights of a neural network are learned based on the training data, where the neural network is configured to estimate a goal location of the one or more reaching tasks. A partial trajectory of a new reaching task is recorded. An estimated goal location is computed, by a computer processor, by applying the neural network to the partial trajectory of the new reaching task.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method comprising: recording, with a three-dimensional camera, one or more demonstrations of a user performing one or more reaching tasks; computing training data describing the one or more demonstrations; learning one or more weights of a neural network based on the training data, the neural network being configured to estimate a goal location of the one or more reaching tasks; recording a partial trajectory of a new reaching task; and computing, by a computer processor, an estimated goal location of the new reaching task by applying the neural network to the partial trajectory of the new reaching task. 2. The computer-implemented method of claim 1, further comprising executing an online learning algorithm to update the one or more weights of the neural network based at least in part on the estimated goal location of the new reaching task. 3. The computer-implemented method of claim 2, wherein the online learning algorithm is configured to adapt the neural network to varying initial positions of an arm performing one or more future reaching tasks. 4. The computer-implemented method of claim 1, wherein computing the estimated goal location comprises iteratively calculating the estimated goal location based on the neural network and a previous calculation of the estimated goal location. 5. The computer-implemented method of claim 1, wherein computing the estimated goal location comprises solving a parameter inference problem by way of an expectation-maximization algorithm. 6. The computer-implemented method of claim 1, further comprising identifying an object reached for in the new reaching task. 7. The computer-implemented method of claim 1, further comprising instructing a robot based on the estimated goal location. 8. A system comprising: a memory having computer readable instructions; and one or more processors for executing the computer readable instructions, the computer readable instructions comprising: recording, with a three-dimensional camera, one or more demonstrations of a user performing one or more reaching tasks; computing training data describing the one or more demonstrations; learning one or more weights of a neural network based on the training data, the neural network being configured to estimate a goal location of the one or more reaching tasks; recording a partial trajectory of a new reaching task; and computing an estimated goal location of the new reaching task by applying the neural network to the partial trajectory of the new reaching task. 9. The system of claim 8, the computer readable instructions further comprising executing an online learning algorithm to update the one or more weights of the neural network based at least in part on the estimated goal location of the new reaching task. 10. The system of claim 9, wherein the online learning algorithm is configured to adapt the neural network to varying initial positions of an arm performing one or more future reaching tasks. 11. The system of claim 8, wherein computing the estimated goal location comprises iteratively calculating the estimated goal location based on the neural network and a previous calculation of the estimated goal location. 12. The system of claim 8, wherein computing the estimated goal location comprises solving a parameter inference problem by way of an expectation-maximization algorithm. 13. The system of claim 8, the computer readable instructions further comprising identifying an object reached for in the new reaching task. 14. The system of claim 8, the computer readable instructions further comprising instructing a robot based on the estimated goal location. 15. A computer program product for inferring an intention, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: recording, with a three-dimensional camera, one or more demonstrations of a user performing one or more reaching tasks; computing training data describing the one or more demonstrations; learning one or more weights of a neural network based on the training data, the neural network being configured to estimate a goal location of the one or more reaching tasks; recording a partial trajectory of a new reaching task; and computing an estimated goal location of the new reaching task by applying the neural network to the partial trajectory of the new reaching task. 16. The computer program product of claim 15, the method further comprising executing an online learning algorithm to update the one or more weights of the neural network based at least in part on the estimated goal location of the new reaching task. 17. The computer program product of claim 16, wherein the online learning algorithm is configured to adapt the neural network to varying initial positions of an arm performing one or more future reaching tasks. 18. The computer program product of claim 15, wherein computing the estimated goal location comprises iteratively calculating the estimated goal location based on the neural network and a previous calculation of the estimated goal location. 19. The computer program product of claim 15, wherein computing the estimated goal location comprises solving a parameter inference problem by way of an expectation-maximization algorithm. 20. The computer program product of claim 15, the method further comprising identifying an object reached for in the new reaching task.