Dynamic and adaptive systems and methods for rewarding and/or disincentivizing behaviors
The present disclosure generally relates to dynamic and adaptive systems and methods for rewarding and/or disincentivizing behaviors.
1. A system comprising a plurality of different devices, sensors, sensor arrays, and/or communications networks, the system configured to determine, through a plurality of measurements/readings taken by the plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs, behavior(s) of at least one entity and context(s) associated with the behavior(s) of the at least one entity, and wherein:
the system is further configured to dynamically and adaptively determine a reward for incentivizing behavior and context of the at least one entity and facilitate redemption of the reward; and/or
the system is further configured to dynamically and adaptively determine a disincentive for disincentivizing behavior and context of the at least one entity and facilitate redemption of the disincentive; and wherein the system is configured to assess, evaluate, and predict a risk of a future occurrence(s) of a behavior(s) within a predetermined time frame and associated context(s) by the at least one entity; and wherein:
the system is configured to dynamically and adaptively determine the reward to incentivize behavior and context that lowers the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs; and
the system is configured to dynamically and adaptively determine the disincentive to disincentivize behavior and context that increases the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs.
2. The system of claim 1 , wherein:
the system is configured to dynamically and adaptively determine the reward type, level, and amount based upon how, where, and by how much the risk was reduced by the incentivized behavior and context; and the system is configured to dynamically and adaptively determine the disincentive type, level, and amount based upon how, where, and by how much the risk was increased by the disincentivized behavior and context.
3. The system of claim 1 , wherein:
the system is configured to dynamically monitor for and detect the incentivized behavior and context that reduces the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs; and the system is configured to dynamically monitor for and detect the disincentivized behavior and context that increases the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs.
4. The system of claim 1 , wherein the system is configured to:
determine whether at least one trigger indicative of a risk of a future occurrence(s) of the behavior(s) by the at least one entity is active or present based on the behavior(s) of the at least one entity and the context(s) associated with the behavior(s) of the at least one entity, as determined through the plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs; determine a reward for incentivizing behavior and context that eliminates or reduces the at least one trigger; and facilitate redemption of the reward.
5. The system of claim 1 , wherein the system is configured to:
determine whether at least one or more of an Anger trigger, an Anxiety trigger, a Boredom trigger, a Depression trigger, a Fear trigger, and a Frustration trigger that are indicative of a risk of a future occurrence(s) of the behavior(s) by the at least one entity is active or present based on the behavior(s) of the at least one entity and the context(s) associated with the behavior(s) of the at least one entity, as determined through the plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs; determine a reward for incentivizing behavior and context that eliminates or reduces the at least one or more of an Anger trigger, an Anxiety trigger, a Boredom trigger, a Depression trigger, a Fear trigger, and a Frustration trigger; and facilitate redemption of the reward.
6. The system of claim 1 , wherein the system is configured to assess, evaluate, and predict a likelihood of a future occurrence(s) of a behavior(s) within a predetermined time frame and associated context(s) by the at least one entity, and wherein:
the system is configured to dynamically and adaptively determine the reward to incentivize behavior and context that increases the likelihood of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs; and/or
the system is configured to dynamically and adaptively determine the disincentive to disincentivize behavior and context that decreases the likelihood of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs.
7. The system of claim 6 , wherein:
the system is configured to dynamically and adaptively determine the reward type, level, and amount based upon how, where, and by how much the likelihood was increased by the incentivized behavior and context; and/or
the system is configured to dynamically and adaptively determine the disincentive type, level, and amount based upon how, where, and by how much the likelihood was decreased by the disincentivized behavior and context.
8. The system of claim 6 , wherein:
the system is configured to dynamically monitor for and detect the incentivized behavior and context that increases the likelihood of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs; and/or
the system is configured to dynamically monitor for and detect the disincentivized behavior and context that decreases the likelihood of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs.
9. The system of claim 6 , wherein the system is configured to:
determine whether at least one trigger indicative of a likelihood of a future occurrence(s) of the behavior(s) by the at least one entity is active or present based on the behavior(s) of the at least one entity and the context(s) associated with the behavior(s) of the at least one entity, as determined through the plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs;
determine a reward for incentivizing behavior and context that produces or increases the at least one trigger; and
facilitate redemption of the reward including one or more of a material reward, a physical reward, a financial reward, a monetary reward, an electronic reward, a virtual reward, a non-material reward, and non-financial reward.
10. The system of claim 1 , wherein the system is configured to:
determine whether at least one trigger is active or present based on the behavior(s) of the at least one entity and the context(s) associated with the behavior(s) of the at least one entity, as determined through the plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs;
determine a reward for incentivizing behavior and context that caused or created the at least one trigger to be active or present; and
facilitate redemption of the reward including one or more of a material reward, a physical reward, a financial reward, a monetary reward, an electronic reward, a virtual reward, a non-material reward, and non-financial reward.
11. The system of claim 10 , wherein the at least one trigger comprises at least one positive trigger including one or more of an aspiration trigger, a goal trigger, a happiness trigger, or other positive trigger associated with behavior to be incentivized and encouraged by the system.
12. The system of claim 1 , wherein the system is configured to dynamically and adaptively:
determine a reward for incentivizing at least one positive trigger associated with behavior and context of the at least one entity; and
facilitate redemption of the reward to thereby incentivize and encourage the behavior and context of the at least one entity including one or more of a material reward, a physical reward, a financial reward, a monetary reward, an electronic reward, a virtual reward, a non-material reward, and non-financial reward.
13. The system of claim 12 , wherein the at least one positive trigger comprises one or more of an aspiration trigger, a goal trigger, a happiness trigger, or other positive trigger associated with the behavior to be incentivized and encouraged by the system.
14. The system of claim 1 , wherein the at least one entity comprises one or more of a robot, an artificial intelligence, an animal, a virtual agent, a corporation, a business entity, a nation, a network, and/or a governmental entity.
15. The system of claim 1 , wherein:
the incentivized behavior and context includes one or more of a sustained behavior, an improved behavior, an environmental context change, and a change of circumstances of the at least one entity; and
the disincentivized behavior and context includes one or more of a discouraged behavior, an environmental context change, and a change of circumstances of the at least one entity.
16. The system of claim 1 , wherein the system is configured to use blockchain or other distributed ledger technology to track, manage, and redeem reward(s) and disincentive(s).
17. The system of claim 1 , wherein:
the system is configured to dynamically and adaptively determine a new reward for incentivizing behavior and context of the at least one entity, which said new reward is not predetermined, predefined, or fixed in the system; and
the system is configured to dynamically and adaptively determine a new disincentive for disincentivizing behavior and context of the at least one entity, which said new disincentive is not predetermined, predefined, or fixed in the system.
18. The system of claim 17 , wherein:
the system is configured to dynamically and adaptively determine a reward that is predetermined, predefined, or fixed in the system for incentivizing behavior and context of the at least one entity; and
the system is configured to dynamically and adaptively determine a disincentive that is predetermined, predefined, or fixed in the system for disincentivizing behavior and context of the at least one entity.
19. The system of claim 1 , wherein the system is configured to dynamically and adaptively:
determine the reward for incentivizing behavior and context of the at least one entity, and facilitate redemption of the reward; and
determine the disincentive for disincentivizing behavior and context of the at least one entity, and facilitate redemption of the disincentive.
20. The system of claim 1 , wherein the system is configured to dynamically and adaptively determine the reward and/or the disincentive by using one or more of machine learning, a neural network, a quantum network, and/or an artificial intelligence.
21. The system of claim 1 , wherein the system is configured to dynamically and adaptively determine the reward and/or the disincentive without requiring manual human intervention to create, define, manage, and administer the reward and/or the disincentive by using one or more of machine learning, a neural network, a quantum network, and an artificial intelligence.
22. The system of claim 1 , wherein the system is configured to dynamically and adaptively determine rewards and/or disincentives by adapting types and levels of the rewards and/or the disincentives to the behavior(s) and associated context(s) of the at least one entity.
23. The system of claim 1 , wherein the system is configured to use a proof blockchain system or other distributed ledger technology consensus mechanism for privacy protection and security.
24. The system of claim 1 , wherein the system is configured to use a blockchain system or other distributed ledger technology for data anonymization.
25. The system of claim 1 , wherein the system is configured to use one or more blockchain components including at least one of a distributed network, a wallet, and/or a user profile.
26. The system of claim 1 , wherein the system is configured to use artificial intelligence to observe and examine a blockchain trail to make predictions identifying behaviors and/or behavior patterns.
27. The system of claim 1 , wherein the system is configured to:
determine a blockchain verifiable and/or cybercurrency based reward for incentivizing behavior and context of the at least one entity; and
facilitate redemption of the blockchain verifiable and/or cybercurrency based reward.
28. The system of claim 1 , wherein the context(s) associated with the behavior(s) of the at least one entity includes at least one of:
a physical location of the at least one entity and a context of the at least one entity at the physical location; and
a virtual location of the at least one entity and a context of the at least one entity at the virtual location.
29. The system of claim 1 , wherein the system is configured to utilize blockchain or other distributed ledger technology to capture transactions of the at least one entity and to retroactively determine and facilitate one or more rewards based on and/or associated with one or more of the transactions of the at least one entity captured by the blockchain or other distributed ledger technology.
30. The system of claim 1 , wherein:
the system is configured to utilize blockchain or other distributed ledger technology to capture transactions of the at least one entity; and
the system is configured to provide data to and obtain data from one or more other reward programs which data is based on and/or associated with one or more of the transactions of the at least one entity captured by the blockchain or other distributed ledger technology.
31. The system of claim 1 , wherein:
the system is configured to utilize blockchain or other distributed ledger technology to capture transactions of the at least one entity;
the system is configured to obtain data from one or more other reward programs which data is based on and/or associated with one or more of the transactions of the at least one entity captured by the blockchain or other distributed ledger technology; and
the system is configured to identify one or more triggers, actions, and/or patterns using the data obtained from the one or more other reward programs.
32. The system of claim 1 , wherein the system is configured to determine customized rewards and customized disincentives tailored to the behavior and associated context(s) by the at least one entity.
33. A method comprising determining, via a plurality of measurements/readings taken by a plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from inputs, behavior(s) of at least one entity and context(s) associated with the behavior(s) of the at least one entity; and assessing, evaluating, and predicting a risk of a future occurrence(s) of a behavior(s) within a predetermined time frame and associated context(s) by the at least one entity, wherein the method further comprises:
dynamically and adaptively determining a reward for incentivizing behavior and context of the at least one entity that lowers the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs and facilitating redemption of the reward; and
dynamically and adaptively determining a disincentive for disincentivizing behavior and context of the at least one entity that increases the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs and facilitating redemption of the disincentive.
34. A non-transitory computer-readable storage media comprising computer-executable instructions, which when executed by at least one processor, cause the at least one processor to determine, through a plurality of measurements/readings taken by a plurality of different devices, sensors, sensor arrays, and/or communications networks and/or inferred through information from system inputs, behavior(s) of at least one entity and context(s) associated with the behavior(s) of the at least one entity, and to assess, evaluate, and predict a risk of a future occurrence(s) of a behavior(s) within a predetermined time frame and associated context(s) by the at least one entity, and cause the at least one processor to:
dynamically and adaptively determine a reward for incentivizing behavior and context of the at least one entity that lowers the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs and facilitate redemption of the reward; and
dynamically and adaptively determine a disincentive for disincentivizing behavior and context of the at least one entity that increases the risk of a future occurrence(s) of the behavior(s) by the at least one entity before the behavior(s) occurs and facilitate redemption of the disincentive.
35. The system of claim 1 , wherein the at least one entity comprises a human and/or a machine.