FIELD OF THE INVENTION

The present inventions relate to architectures, systems and methods for programmatically controlled entertainment state systems. More particularly, architectures, systems and methods for program control utilizing cognitive computing, including but not limited to artificial intelligence and machine learning, and optionally including analytics. Systems, methods and architectures are provided for game and entertainment operations are provided utilizing decentralized systems, including blockchain, optionally in peer to peer systems. More particularly, systems and methods for implementing a lottery, game or entertainment utilizing cryptocurrency, such as bitcoin, in a decentralized system.

BACKGROUND OF THE INVENTION

History shows that many trusted systems have evolved in order to provide for efficient functioning of society and business. Generally, these have involved central control of systems in order to ensure compliance with rules. Within the gaming space, examples include lotteries and regulated gaming. By way of example, the Nevada Gaming Control Board monitors institutions within the state for compliance with laws and regulations, and ensures the fair and efficient functioning of the industry.

Consider the entertainment and gaming system background. A lottery is a ‘State’ Function and serves as a form of ‘trusted agent’. The classic definition of the elements of a lottery are prize, chance and consideration. When these elements are reordered into a more chronologically correct order, namely first, receipt and holding of the consideration (e.g., ticket purchases), chance (e.g., ensuring a fair and accurate random number generator) and prize (i.e., paying the prize to the true winner.) Therefore, the State acts as a ‘trusted agent’ as it holds the consideration, guarantees randomness of the ‘chance’, and pays out the prize (title transfer). ‘Trust’ is based on the Integrity and Trustworthiness of People Operating the System and the Regulators Who Oversee the System. Lotteries or State Regulators are often former law enforcement. The degree of trust in the Regulators is often based on time and track record, e.g., the State of Nevada Regulatory system is considered highly trustworthy and effective, based in part on a multi-decade long track record. Additionally, a State with the most business to lose from a loss of trust in the regulatory process is most motivated to provide regulation. Such systems are based on central control of the system.

A casino is a ‘state regulated’ function and a form of ‘trusted agent’ with ‘verification’. They are licensed by the State and subject to state inspection.

Various advancements have been made in the gaming and entertainment environment. The following are assigned to the assignee of this, and are hereby incorporated by Reference as if fully set forth herein: Games, And Methods For Improved Game Play In Games Of Chance And Games Of Skill, U.S. Pat. No. 6,565,084, Games, and Methods and Apparatus for Game Play in Games of Chance, U.S. Pat. No. 6,488,280, Games, and Methods and Apparatus for Game Play in Games of Chance, U.S. Pat. No. 6,811,484, Apparatus and Method for Game Play in an Electronic Environment, U.S. Pat. No. 8,393,946, Apparatus, Systems and Methods for Implementing Enhanced Gaming and Prizing Parameters in an Electronic Environment, U.S. Pat. No. 7,798,896, Apparatus, Systems and Methods for Implementing Enhanced Gaming and Prizing Parameters in an Electronic Environment, U.S. Pat. No. 8,241,110, Methods and Apparatus for Enhanced Play in Lottery and Gaming Environments, U.S. Pat. No. 8,727,853, Methods and Apparatus for Enhanced Interactive Game Play in Lottery and Gaming Environments, U.S. Pat. No. 8,241,100, Method and System for Electronic Interaction In A Multi-Player Gaming System, U.S. Pat. No. 8,535,134. Generally, they comprise a suite of tools to make systems more engaging, and to optimize results.

One vexing problem in larger systems results from systems incompatibility. Various components often come from various vendors. There is often a lack of interoperability and incompatibility. Various systems in the gaming ecosystem need to interoperate, including but not limited to: gaming operations, marketing, CRM (Customer Relationship Management), loyalty programs, Ancillary Points or Credits, System Analytics and Optimization, and account and audit functions.

Software Defined Systems are a collection of modules interoperated under a higher level of software control. These manage network services through abstraction of lower level functionality. Generally, there is an Application Plane, a Control Plane and a Data Plane. Examples include Software Defined Networks having a Control Plane which provides intelligent control of data plane composed of relatively less intelligent switches, routers, storage. Yet another example is software defined radio. The control plane monitors and supervises use of frequency bands in the data plane.

Yet another component is the use of static interfaces and tools. For example, APIs or Application Programming Interfaces generally comprise a static interface. They define a format for an information request. ‘If you ask for X in a specific way, we will provide Y’. Generally, no access is provided by requestor to the system other than via API. Yet another system are SDKs or Software Development Kit. They may be static. Tools are provided to achieve desired results. GDKs or Game Development Kit also may be static and provide tools for game development.

The design of entertainment or games is often driven by metrics driven design. This often involves AB Testing comparing the results or favorability as between multiple systems. Further, they often monitor multivariate response systems.

One aspect of lotteries and Lotto style games is that they tend to be static. At the most extreme example, they are literally printed on cardstock. More generally, once a format for a lottery game has been chosen, such as a 6 out of 49 format, it is difficult to change. Public perception of change is that the game has become less favorable to the player.

Problem gambling issues have plagued the gaming industry. It is a significant issue for society. While users can solicit help (e.g., 1-800-Gambling), there is often denial and an unwillingness to seek help. Various attempts have been made to limit abuse, such as use rate limits in some on-line games.

In the move from bricks and mortar to on-line and cyber spheres, identity issues proliferate. Issues include: are you who you purport to be and will the user's identity be compromised?

Significant advances have been made in cognitive intelligence and adaptive intelligence. For example, IBM Watson won a Jeopardy competition 2011 against highly skilled players. Deep learning and pattern recognition has occurred. Current trends include big data, pattern recognition and machine learning.

Recent advances have also been made in object detection, both in 2D and 3D space. A challenge in the Large Scale Visual Recognition Challenge (LSVRC) provides for Object Detection in ImageNet 2016. The error rate of automatic labeling of ImageNet declined to less than 3%, compared to human performance of about 5%.

Significant advances have also been made in machine based game play performance. In 2015, Google DeepMind used an artificial intelligence reinforcement learning system to learn how to play 49 Atari games. In 2016, AlphaGo system from Google DeepMind beat one of the world's greatest Go players 4-1. In 2017, Carnegie Mellon University's Libratus program defeated top human players in a statistically significant manner.

Further advances have been made in cloud based systems. Functions have been migrating from local servers and storage to remote ‘cloud’ storage. These systems provide for easy scalability. Clouds based systems may run multiple ‘instances’ simultaneously. They also may combine software as a service, including Artificial Intelligence (“AI”).

The Internet of Things (“IoT”) utilizes devices capable of sending data to remote location, and receiving command data. Various voice controlled devices use AI or machine learning (“ML”), e.g., Amazon Alexa, Google Dot.

FIG. 1shows an exemplary prior art centralized system.FIG. 2shows an exemplary prior art distributed system.

Advancements have been made in trusted distributed systems such as in the use of blockchain based systems. The initial disclosure of the blockchain technology is attributed to Satoshi Nakamoto in a paper published October, 2008. This system provides for automatic trust or system trust. The blockchain paradigm provides for a decentralized system utilizing decentralized consensus. This can be done in a peer-to-peer manner without an intermediary. The system may be viewed as a network of nodes running software on a programmable distributed network. It is sometimes referred to as a transaction singleton machine with shared state, a transaction based state machine, a message passing framework, a trustful object messaging compute framework and trusted computing.

A decentralized consensus is established by a combination of blockchain and cryptography. Authority and trust is provided by the decentralized virtual network. Consensus logic is generally separate from the application. It may comprise the first layer of a decentralized architecture.

Blockchain utilizes a distributed ledger. A ‘block’ comprises a new group of accepted transactions. A batch of transactions is released in a block to be validated by the network of participating computers. Continuous, sequential transaction record on a public block creates a unique “chain” or blockchain. This block is published to all other nodes. The publication occurs periodically, e.g. every 10 minutes.

Etherium is an open source platform for smart contracts. As currently operated, Etherium is a decentralized platform that runs smart contracts: applications that run exactly as programmed without any possibility of downtime, censorship, fraud or third party interference. The applications run on a custom built blockchain, an extremely powerful shared global infrastructure that can move the value and represent ownership of the property. This allows developers to create markets, store debt or promise records, move funds according to long-standing instructions (such as a will or a futures contract), without the counterparty risk. Etherium also states that its goal is to create a tradeable digital token that can be used as a currency, a representation of an asset, a virtual share, a proof of membership or anything at all. These tokens use a standard coin API, so the contract will be automatically compatible with any wallet, other contract or exchange also using this standard. The total amount of tokens in circulation can be set to a simple fixed amount or fluctuate based on any programmed ruleset. In summary, Etherium states that it enables building a tradeable token with a fixed supply, a central bank that can issue money and a puzzle-based cryptocurrency.

There are many disadvantages to the current systems. They are slow to change and innovate. They often involve proprietary systems that do not interoperate. There is often governmental and or institutional bias. There may be a cumbersome regulatory environment. Finally, there are often high transaction costs.

Thus, there is a need for interoperability among inconsistent, often proprietary systems. There is a need for gambling limitation on a more global basis, including geo-limitation and global use rate monitoring for problem gambling. There is a need for problem gambling detection and remediation. There is a need for improved distributed systems.

SUMMARY OF THE INVENTION

In one aspect, the inventions comprise a system for control of an entertainment state system having segregated secure functions and public functions for use by one or more users of the system. First, a public interface portal receives instructions regarding operation of the entertainment state system from the one or more users. The interface portal includes a first interface to receive instructions from and communicate to the one or more end users, a processor, a graphical user interface (GUI) coupled to the processor, a control unit in operative communication with the processor and graphical user interface, and a second interface providing an application program interface (API). Secondly, a secure entity unit is provided, the secure entity unit including a receive interface, the receive interface adapted to receive a call from the application program interface (API) of the interface portal, a send interface, the send interface adapted to provide a response to the interface portal interface, a game engine, and a financial engine. Preferably the financial engine is coupled to the game engine, the receive interface and the send interface.

Systems and methods are provided for training an artificial intelligence system including the use of one or more human subject responses to stimuli as input to the artificial intelligence system. One or more displays are oriented toward the human subjects to present the stimuli to the human subjects. One or more detectors serve to monitor the reaction of the human subjects to the stimuli, the detectors including at least motion detectors, the detectors providing an output. An analysis system is coupled to receive the output of the detectors, the analysis system providing an output corresponding to whether the reaction of the human subjects was positive or negative. A neural network utilizes the output of the analysis system to provide a positive weighting for training of the neural network when the output of the analysis system was positive, and a negative weighting for training of the neural network when the output of the analysis system was negative.

