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5 results about "Reward system" patented technology
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The reward system is a group of neural structures responsible for incentive salience (i.e., motivation and "wanting", desire, or craving for a reward), associative learning (primarily positive reinforcement and classical conditioning), and positively-valenced emotions, particularly ones which involve pleasure as a core component (e.g., joy, euphoria and ecstasy). Reward is the attractive and motivational property of a stimulus that induces appetitive behavior, also known as approach behavior, and consummatory behavior. In its description of a rewarding stimulus (i.e., "a reward"), a review on reward neuroscience noted, "any stimulus, object, event, activity, or situation that has the potential to make us approach and consume it is by definition a reward". In operant conditioning, rewarding stimuli function as positive reinforcers; however, the converse statement also holds true: positive reinforcers are rewarding.
Model training method and device, task execution method and device, electronic equipment and storage medium
According to the model training method and device, the task execution method and device, the electronic equipment and the storage medium, in the method, the prompt content, the reply content output by the target model for the prompt content and the process data for generating the reply content can be firstly obtained, and then the prompt content, the reply content and the process data are input into the reward system; therefore, the reward value of each reasoning step in the process data is obtained, and finally, the target model is iteratively trained based on the reward value of each reasoning step. The reward system of the method no longer generates the reward value for the token of the sample, but generates the reward value for each reasoning step in the process data, so that the target model can pay attention to the integrity and logicality of the reply content in the training process, and then the performance and stability of the target model in a complex task and the robustness of the model are improved.
Owner:ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
System and methods for detecting and mitigating neuro-deficiencies using brain imaging data
Disclosed herein are systems and methods for evaluating the underlying molecular (e.g., brain reward system molecules) cause for a depressive disorder and developing a treatment plan based on the identified molecular cause. In one or more examples, the systems and methods described herein can utilize any combination of brain imaging techniques, subjective emotion data taken from a patient, and / or one or more algorithms for translating emotional states to brain reward system molecules (e.g., neurotransmitters) to determine an underlying molecular cause for a depressive disorder of a patient. Once the underlying molecular cause of the depressive disorder of the patient is determined, a treatment plan that includes both behavioral and pharmacological aspects can be selected based on the identity of the reward system molecule that is determined to be deficient and the level of deficiency.
Owner:MATTER NEUROSCIENCE INC
system
We provide the system. [Solution] A means for generating a customized learning program based on the user's learning progress and goals, A means of calculating and notifying the optimal review timing based on the forgetting curve, A means of analyzing users' learning progress and providing information to maintain feedback and motivation, To streamline financial transactions, a means of managing electronic transactions linked to learning plans, A system that includes means for implementing a reward system to provide compensation based on progress.
Owner:SOFTBANK GROUP CORP
Smoothed reward system transfer for actor- critic reinforcement learning models
Methods and systems for smoothening the transition of reward systems or datasets for actor-critic reinforcement learning models. A reinforcement model such as an actor-critic model is trained on a first dataset and a first reward system. The weights of the actor model and the critic model are frozen. While these weights are frozen, an affine transformation layer is attached to a final layer of the critic model, and the affine transformation layer is trained with a second dataset and a second reward system in order to adjust a weight of the final layer of the critic model. Then, the weights of the critic model are unfrozen which allows the adjusted weight of the final layer of the critic model to be implemented. The reinforcement learning model is retrained on the second dataset and second reward system, first with just the critic weights unfrozen, and then with both actor and critic weights unfrozen.
Owner:ROBERT BOSCH GMBH
Automated executive function coaching platform
PendingUS20260051261A1Data processing applicationsElectrical appliancesReward systemKnowledge management
A system for an automated and on-demand executive function coaching platform for the development of executive functions and STEM learning in school-aged children, and specifically for children with learning disabilities. The system includes a generative artificial intelligence module to provide automated coaching, wherein the coaching includes lessons, programs, activities, and / or assessments, with an easy to integrate application program interface. The system may also include motivational interviewing, gamification of learning, and a rewards system for the completion of coaching lessons.
Owner:HOTKEYS HOLDING LLC