DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to the application filed on 12/09/2024.
Claim Objections
Claim 17 is objected to because of the following informalities:
“input waters” should read “input wagers”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a system and method which is one of the statutory categories of invention.
[STEP2A PRONG 1] The claims recite limitations which have been constructed as certain methods of organizing human activity. 1 recites an online gaming platform, 8 recite a method, and claim 17 recites a system including at least one processor; at least one input device; a game server; a random number generator; and at least one memory device, for performing steps including retrieving and displaying wager data corresponding to one or more live sporting events; receiving from a user a first wager input and a second wager input; receiving a selection of an odds booster game that changes the wager line and wager odds; generating adjusted wager lines and odds; receiving favorable or challenging odds tailored to the user.
Under the broadest reasonable interpretation, the claims recite steps of managing wagers and conducting wagering transactions, including presenting betting options, adjusting wager terms, resolving a wagering event, and recording the resulting wager data. Such activities constitute certain methods of organizing human activity, including fundamental economic practices and managing interactions between people (see MPEP 2106.04(a)(2)). Courts have recognized that rules for playing games and managing wagers constitute abstract ideas. Accordingly, claim(s) 1-120 recite abstract ideas.
[STEP2A PRONG II] The judicial exception is not integrated into a practical application because the claims do not recite additional elements that are significantly more than the judicial exception or meaningfully limit the practice of the judicial exception. The additional elements including the “processor,” “touch screen input device,” “random number generator,” and “memory,” “video controller,” under their broadest reasonable interpretation, are generic computer components performing conventional functions of receiving, processing, storing, and transmitting data (see MPEP 2106.05(d)(II)). The additional limitations merely implement the abstract idea on a computer and do not impose any meaningful limits on practicing the abstract idea. Furthermore, the claimed limitations generally link the use of the judicial exception to a particular technological environment, namely a gaming environment, which is insufficient to integrate the exception into a practical application (see MPEP 2106.05(h)).
[STEP2B] The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements are generic computer components that are known to one of ordinary skill in the art. The recitation of these additional elements do not amount to significantly more than the judicial exception, but rather adds mere instructions to implement the abstract idea on a computer as a tool to perform the abstract idea.
Dependent claims 2-7, 9-16, and 18-20 further recite features that either narrow the abstract idea or invoke additional generic computing environments (e.g., a “mobile device” in claims 6, 13, and 18; a “gaming terminal with a housing” in claims 7, 14, and 19). None of these limitations, alone or in combination with the independent claims, integrates the abstract idea into practical application or provides an inventive concept sufficient to transform the abstract idea into eligible subject matter. Therefore, claims 1-20 are found to be directed to a grouping of abstract ideas without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gonzalez et al. (US 20230290223 A1), herein after Gonzalez in view of Barragan (US 9613485 B2), and further in view of Huke et al. (WO 2023064563 A1), hereinafter Huke.
In regards to claim(s) 1, 8, and 17, Gonzalez teaches the online gaming platform comprising:
a display device for displaying the dynamic content (Par. [0084]; “FIG. 3 illustrates one embodiment of a slot machine graphic 300 that can be rendered on a display of the client device 106.” ), wherein the dynamic content is associated with an opportunity to input wagers related to one or more live sporting events (Par. [0006]; “a method for increasing user engagement with sports betting can comprise receiving, at a server, a request from a client device to place a bet on at least one sporting event having odds associated with the sporting event”);
a touch screen input; a processor coupled to the display device and the touch screen input (Par. [0003]; “Sports enthusiasts in jurisdictions that allow for online sports betting can now simply place a bet on an upcoming or live sporting event with a few taps on the touchscreens of their smartphones.”);
a memory coupled to the processor (Par. [0030]; “The server 102 can comprise one or more server processors, server memory units, and a server communication unit. The one or more server processors can be coupled to the server memory units”), the memory comprising machine-readable instructions that (Par. [0032]; “The server memory units can store software, data, logs, or a combination thereof.”), when executed by the processor, cause the processor to: receive, by a video controller, the dynamic content (Par. [0061]; “As shown in FIG. 2A, the bet placement GUI 200 can display odds 114 associated with several possible outcomes of the sporting event 202.” ). Under the broadest reasonable interpretation, video controller reads on a display that receives and renders visual content on the display. The bet placement GUI receiving and rendering live event odds on the client device display corresponds to receipt of dynamic content via the display content.
retrieve, from a data storage device, wager data corresponding to the one or more live sporting events, betting lines, and wagers (Par. [0039]; “In some embodiments, the server 102 can also receive a request from the client device 106 to place a bet 112 on multiple sporting events 202.”) and (Par. [0040]; “Once the server 102 has verified that the user of the client device 106 is eligible to place the bet (e.g., the user has enough funds in an account associated with the user to place the bet 112 at the requested bet amount 116), the odds 114 and the bet amount 116 are passed to a bet spinner module 118 of the server 102.”). Gonzalez discloses that the odds and bet amounts are retrieved from the database and passed to server modules for processing.
cause display, on the display device, the wager data associated with the opportunity to input wagers related to the one or more live sporting events (Par. [0062]; “The user can apply a user input to a graphic displaying the 4.37 odds if the user wishes to place a bet 112 on Team A winning at home.”);
receive, based on the opportunity to input wagers, from a graphical user interface (GUI) on the display device, and associated with a user, a first wager input and a second wager input corresponding to the one or more live sporting events, wherein the first wager input includes a selection of a wager team, a wager line, and a wager odds from the wager data, and the second wager input includes a wagering amount (Par. [0061]-[0062]; “As shown in FIG. 2A, the bet placement GUI 200 can display odds 114 associated with several possible outcomes of the sporting event 202. In some embodiments, the odds 114 displayed can be decimal odds…In placing a bet 112, the user selects the odds 114 associated with one outcome of the sporting event 202.”) and (Par. [0065]; “The user can input a bet amount 116 for the bet 112 by typing in the bet amount 116 into a bet amount input window 204 of the bet placement GUI 200.”) and (Par. [0075]; “For example, the margin can be calculated using an equation that factors in not only the odds 114 associated with the outcome selected by the user (e.g., Team A winning at home) but also the odds 114 associated with the other outcomes (e.g., Team B winning on the road and the match ending in a draw).”). Gonzalez discloses that the user selects a team outcome and a decimal odds pairing, and then separately enters a bet amount.
after receiving the first wager input and the second wager input, receive, from the GUI, a selection of an odds booster game, wherein the odds booster game changes the wager line and the wager odds (Par. [0071]; “In response to the user confirming the bet 112, the bet spinner module 118 can pass the odds 114 and the bet amount 116 received from the client device 106 as inputs to the multiplier calculation engine 120 of the server 102. As previously discussed, the multiplier calculation engine 120 can use the bet amount 116 and the odds 114 as inputs to determine whether the user should be awarded a multiplier 302 (see, e.g., FIG. 3 ) to boost the user’s possible winnings.”);
cause, on the GUI of the display device, display of a graphic representation of a first spinning wheel comprising a plurality of line adjustments (Par. [0057]; “the slot machine graphic 300 can comprise a plurality of reels 306 that appear to rotate graphically.”) and (Par. [0087]; “The slot machine graphic 300 can be rendered such that the reels 306 appear to rotate or spin graphically.”). Under the broadest reasonable interpretation, spinning wheel comprising a plurality of line adjustments reads on a rotating graphical adjuster with a various adjustment positions applied to a wager parameter.
Gonzalez does not explicitly teach in response to a first user input to spin the first spinning wheel, generate, via a random number generator implementing a machine learning algorithm, an adjusted wager line, wherein the machine learning algorithm comprises a semi-supervised learning mechanism.
However, Huke teaches a machine learning algorithm comprising a semi-supervised learning mechanism (Huke, ‘563, Par. [0074]; A machine learning betting system may fall between a supervised machine learning algorithm and an unsupervised one…A semi- supervised machine learning betting system may use that to identify other users in the cohort who are desirable.).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gonzalez’s random number generator bet spinner module to incorporate Huke’s semi-supervised machine learning betting system. Gonzalez identifies increased user engagement as a design objective while maintaining control over incentives and protecting the platform’s financial health (Gonzalez, Abstract) while maintaining fair incentives and protecting the platform’s financial health (Par. [0004]; “Furthermore, such incentivization structures should also be well-controlled such that the financial health of the online sports betting platform is not put at risk as a result of unforeseen betting outcomes.”). Huke teaches using semi-supervised machine learning with wager outputs and cohort user behavior data to personalize odds or parameter adjustments (Par. [0874]; “A machine learning betting system may fall between a supervised machine learning algorithm”). One of ordinary skill in the art would have recognized that applying Huke’s known technique for wager personalization to Gonzalez’s bet spinner module would provide a user and cohort informed betting adjustments.
Gonzalez further teaches cause, on the GUI of the display device, display of the first spinning wheel indicating a selection of the adjusted wager line (Par. [0090]; “The multiplier 302 awarded can be revealed to the user by graphically rotating all of the reels 306 and each of the reels 306 can successively stop (e.g., beginning with the far left reel 306) on the symbol 308 associated with the awarded multiplier 302.”). Under the broadest reasonable interpretation, the reels stopping on award multiplier symbol correspond to displaying the spinning wheel indicating the selection of the adjusted parameter.
Gonzalez does no teach cause, on the GUI of the display device, display of a graphic representation of a second spinning wheel comprising a plurality of odds adjustments.
However, Barragan teaches a second spinning wheel random outcome provider operating independently from the first spinning wheel (Abstract) and (Col. 2, lines 23-27; “An at least three-wheel gaming system is provided wherein there are three physical and/or virtual wheels that have at least thirty-six symbol positions on each wheel that may be used to independently and collectively determine game event outcomes on each of the three wheels.”) and (Col. 4, lines 62-65; “Each wager operates or stands separately, in that a wager does not have to be won on the first wheel as a trigger or qualifier for a wager to be won against any other wheel.”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gonzalez’s single bet spinner design to include a second independent spinning wheel as taught by Barragan. Barragan teaches multiple independent virtual spinning wheels, each operating by a separate random number generator outcome and associated with a respective wager parameter, to provide distinct wagering possibilities and increase player choice (Barragan, Abstract). One of ordinary skill in the art would have been motivated to add Barragan’s second spinning wheel to Gonzalez’s odds boost mechanism to separately and visibly adjust two wager parameters.
Barragan further teaches monitor, via the GUI of the display device, information on live user interactions with the first spinning wheel and the second spinning wheel (Col. 7, lines 62-65; “The screen 32 is a touchscreen having player input areas for wagering on each wheel separately 12 a 12 b and 12 c”) and (Col. 8, lines 13-16; “Area 12 b only is contacted to select the second wheel 20 b as the underlying game object…The start button 34 is pressed and the three wheel 20 a 20 b and 20 c are virtually spun”).
Similarly, Huke teaching monitoring live user interactions via the GUI (Huke, Par. [0926]; “A user interaction module 1526 collects user interactions with a user device 1518 and saves the collected data to the user interaction database 1526, at element 1526. A user interaction database 1528 stores user interaction data collected by the user interaction module 1526 including user inputs from buttons, touch screen display, keyboard, camera, accelerometer, or capacitive sensors which may indicate any of the user's knowledge, preferences, attentiveness and level of engagement with the user device 1518, at element 1528.”).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Barragan and Huke. Barragan already captures per wheel user inputs at the GUI. Huke discloses collecting and storing similar input device interactions in a user interaction database to indicate user preferences and engagement. One of ordinary skill in the art would recognize that applying Huke’s interaction monitoring to Barragan’s multiple wheel touchscreen interface would convert Barragan’s capture inputs into a record of user engagement that could be used to support personalized odds adjustments.
Gonzalez and Barragan do not teach provide, as input to the machine learning algorithm, historical weighting betting and odds booster information associated with the user and the information on the live user interactions.
However, Huke teaches providing historical user wager data and user interaction data as input to the machine learning algorithm (Huke, Par. [0871]; “A supervised machine learning betting system may be provided a dataset of historical sporting events, the odds of various outcomes of those sporting events, and the action waged on those outcomes, and use that data to predict the action on future outcomes by identifying similar historical outcomes. A machine learning betting system may utilize recommendation algorithms to learn user preferences”).
Huke further teaches receive, as output from the machine learning algorithm, favorable odds that increase the user’s potential winnings, or challenging odds that add an element of risk and unpredictability, wherein the favorable odds or the challenging odds are tailored for the user based on the dynamic content and the live user interactions. (Huke, ‘563, Par. [0131]; “Thus, there is a need within the prior art to provide a method for indirect odds making by using the historical data from users from similar wagers to determine how the user will wager in an upcoming wager market.”), (Par. [2209]; “indirect odds making”). (Par. [1321]; “Figure 138 illustrates the cross database 13716. The cross database 13716 contains the output of the betting algorithms module 13724, the cross module 13726, the Al comparison module 13728, the final odds module 13730, and the machine learning module 13732, as well as the mechanisms of the odds making formulas used to by the betting algorithms module 13724. The wagering network 13708 may use some number of odds making formulas.”). Huke further teaches that betting is personalized to the user (Par. [0847]; ““Customized betting” allow customers to have tailored personalized betting experiences with sophisticated tracking and analysis of players' behavior. “Customized betting” can be integrated into the embodiments in a variety of manners.”) and (Par. [1170]; “ Further, embodiments may include a user behavior module 10618 that analyzes a user’s behavior by comparing the user’s current betting habits or patterns with historical user data from the user database 10610.”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Huke’s semi-supervised machine learning betting system and per user real time odds into the Gonzalez and Barragan combination. Huke identifies personalization and semi-supervised machine learning as a mechanism to increase engagement similar to Gonzalez’s engagement objective. One of ordinary skill in the art would have recognized that incorporating the random number generator output selection of the Gonzalez and Barragan wheel booster with a semi-supervised machine learning recommendation engine would provide real time, per user adjustments based on preferences and engagement patterns.
Barragan further teaches in response to a second user input to spin the second spinning wheel, generate, via the random number generator and in real time, an adjusted wager odds comprising the favorable odds or the challenging odds (Col. 8, lines 15-18; “The start button 34 is pressed and the three wheel 20 a 20 b and 20 c are virtually spun, a random number generator (not shown) in the processor system (not shown) determining ultimate virtual wheel positions”) and (Col. 11, lines 5-9; “each of the three spinning wheel random outcome provider consists of a virtual spinning wheel with a virtual axis or rotation perpendicular to the face of the spinning virtual wheel outcome provider which is displayed on a video display system upon execution of code by a processor”). Barragan discloses that each independent virtual spinning wheel is resolved by a random number generator in real time upon spin trigger.
cause, on the GUI of the display device, display of the second spinning wheel indicating a selection of the adjusted wager odds (Col. 8, lines 23-26; “In FIG. 1, a final position for the spin outcomes for the three wheels 20 a 20 b and 20 c are shown as G (Green) for wheel 20 a, B (Blue) for wheel 20 b and B (Blue) for wheel 20 c.”). Barragan discloses that the second wheel (20 b) visibly stops the random number generator selected outcome, indicated by pointer (30 b), which corresponds to displaying the second spinning wheel with the selection of the adjusted wager odds.
Gonzalez further teaches on a final result screen of the GUI, display of final wager data that includes the wager team, the adjusted wager line, the adjusted wager odds, and the wagering amount (Par. [0099]; “FIG. 4A illustrates one embodiment of a pop-up window 400 that can be displayed to a user via the client device 106 showing certain taxes factored into the calculation of the user’s boosted possible payout amount 304”). Gonzalez discloses a pop-up window 400 shown after the bet spinner resolves renders the wager team, the boosted payout parameters, and the bet amount.
and send, via a communication interface and to the data storage device, the final wager data comprising the wager team, the adjusted wager line, the adjusted wager odds, and the wagering amount (Par. [0033]; “The server communication unit can include one or more wired or wireless communication interfaces.”) and (Par. [0036]; “The server 102 can store data and information received from the client devices 106 in one or more databases 108.”).
Claim(s) 8 and 17 recites a method and system, respectively, whose steps recite the same limitations as claim 1, performed by a computing device and video controller. Therefore, claims 8 and 17 are rejected for the reasons set forth above with respect to claim 1.
In regards to claim(s) 2, 9, and 20, Barragan teaches the online gaming platform, wherein the first spinning wheel comprises a line differential wheel that includes the plurality of line adjustments to the wager line as calculated using random line adjustment numbers generated by the random number generator executing within the processor (Col. 8, lines 15-18; “a random number generator (not shown) in the processor system (not shown) determining ultimate virtual wheel positions”) and (Col. 14, lines 1-11; “each of the three spinning wheel random outcomes provided on the virtual spinning wheel is selected from a specific wager multiplier… the probability of occurrence of multiplier values is weighted by the processor with declining probabilities as size of the multiplier increases.”). Under the broadest reasonable interpretation, line differential wheel reads on any spinning wheel that bears a plurality of random number generator generated adjustment values applied to a wager parameter.
The motivation to combine with respect to claim 1 is applied here. It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to configure Gonzalez’s spinning wheel as Barragan’s virtual, weighted, random number generator operated wheel of adjustment values. The modification would apply Barragan’s probabilistic weighting mechanism to control payout risk, consistent with Gonzalez’s objective of maintaining the platform’s financial health (Gonzalez, Par. [0004]; “Furthermore, such incentivization structures should also be well-controlled such that the financial health of the online sports betting platform is not put at risk as a result of unforeseen betting outcomes.”).
Claim(s) 9, and 20 is/are dependent on claims 8 and 17, respectively. The claims recite the same limitation as claim 2. Therefore claim 9 and 20 is/are rejected for the same reasons as claim 2.
In regards to claim(s) 3, 10, and 20, Gonzalez and Barragan do not teach both positive and negative line adjustments. However, Huke teaches bidirectional wager parameter adjustment via the odds module. Specifically, Huke teaches that the odds module both increases and decreases odds relative to a baseline in response to user, situational, and historical data (Par. [3281]; “In the embodiments, machine learning can be applied to the historical data in order to improve the betting odds. Correlations between event outcomes and available parameters can be analyzed in advance and in real time by an "Odds Module" to give accurate and up-to-date odds.”). Providing outputs that adjust the wager parameter both upward and downward reads on the plurality of line adjustments to the wager line includes one or more positive line adjustments to the wager line and one or more negative line adjustments to the wager line. Under the broadest reasonable interpretation, two directional outputs of the machine learning alter odds module when applied to the line adjustment wheel reads on positive and negative line adjustments.
The motivation to combine with respect to claim 1 is applied here. It would have been obvious to one of ordinary skill to configure the line adjustment wheel of the Gonzalez and Barragan combination with both positive and negative values as taught by Huke. Huke teaches that machine learning driven bidirectional odds adjustments provide (“accurate and up-to-date odds” as stated in Par. [3218]) and personalize user engagement (Par. [0847]; “Customized betting” allow customers to have tailored personalized betting experiences ”). The combination amounts to the use if a known technique to yield predictable results.
Claim(s) 10, and 20 is/are dependent on claims 8 and 17, respectively. The claims recite the same limitation as claim 3. Therefore claim 10 and 20 is/are rejected for the same reasons as claim 3.
In regards to claim(s) 4, 11, and 20, Barragan teaches the online gaming platform, wherein the second spinning wheel comprises an odds wheel that includes the plurality of odds adjustments to the wager odds as calculated using random odds adjustment numbers generated by the random number generator executing within the processor (Col. 8, lines 15-18; “a random number generator (not shown) in the processor system (not shown) determining ultimate virtual wheel positions ”) and (Col. 14, lines 1-11; “each of the three spinning wheel random outcomes provided on the virtual spinning wheel is selected from a specific wager multiplier…the probability of occurrence of multiplier values is weighted by the processor with declining probabilities as size of the multiplier increases.”).
The motivation to combine with respect to claim 1 is applied here. It would have been obvious to one of ordinary skill to configure Gonzalez’s second spinning wheel as Barragan’s virtual, weighted, random number generator configured wheel of odds and multiplier adjustment values for the same reasons discussed with respect to claim 2.
Claim(s) 11, and 20 is/are dependent on claims 8 and 17, respectively. The claims recite the same limitation as claim 4. Therefore claim 10 and 20 is/are rejected for the same reasons as claim 4.
In regards to claim(s) 5 and 12, Gonzalez teaches the online gaming platform, wherein the wager data comprises a home/away indication and event time/date information (Par. [0075]; “Going off the example bet shown in FIGS. 2A and 2B, the margin (also referred to as a bookmaker’s margin or betting margin) can be calculated using one or more equations that take into account all of the odds associated with the sporting event 202. For example, the margin can be calculated using an equation that factors in not only the odds 114 associated with the outcome selected by the user (e.g., Team A winning at home) but also the odds 114 associated with the other outcomes (e.g., Team B winning on the road and the match ending in a draw).”)
Claim 12 is dependent on claim 8, and recites the same limitation as claim 5. Therefore claim 12 is rejected for the same reasons as claim 5.
In regards to claim(s) 6, 13, and 18, Gonzalez teaches the online gaming platform, wherein the display device, the touch screen input, and the processor are included within a mobile device (Par. [0003]; “Sports enthusiasts in jurisdictions that allow for online sports betting can now simply place a bet on an upcoming or live sporting event with a few taps on the touchscreens of their smartphones.”).
Claims 13 and 18 is/are dependent on claims 8 and 17, respectively. The claims recite the same limitation as claim 6. Therefore claim 13 and 18 is/are rejected for the same reasons as claim 6.
In regards to claims 7, 14, and 19, Gonzalez teaches (Par. [0027]; “FIG. 1 illustrates one embodiment of a system 100 for increasing user engagement with online sports betting. In some embodiments, the system 100 can refer to certain modules or engines of an online sports betting platform. For example, the system 100 can comprise certain modules and engines of a server 102 of the online sports betting platform”). Similarly, Huke teaches (Par. [0848]; “ Kiosks are devices that offer interactions with customers clients and users with a wide range of modular solutions for both retail and online sports gaming. Kiosks can be integrated into the embodiments in a variety of manners.”), thereby teaching the online gaming platform further including a gaming terminal with a housing that encloses the display device, the touch screen input, and the processor
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to house the combined system of Gonzalez and Huke in a gaming terminal kiosk as disclosed by Huke because kiosk sports wagering is identified by Huke as an established and well-known form factor for both retail and online sports gaming. One of ordinary skill in the art would have recognized that implementing a kiosk would achieve deployment flexibility for retail environments.
Claim 14 and 19 is/are dependent on claims 8 and 17, respectively. The claims recite the same limitation as claim 7. Therefore claim 14 and 19 is/are rejected for the same reasons as claim 7.
In regards to claim 15, Huke teaches the method of claim 8, further comprising: training the machine learning algorithm implemented on the random number generator based on real-time user interaction with the first and second spinning wheels; and using the trained machine learning algorithm to recalibrate the adjusted wager odds in real-time (Par. [0869]; “A machine learning betting system will measure error once the model is trained… A machine learning betting system may go through several cycles of training, validation, and testing until the error in the model is brought within an acceptable range.”) and (Par. [3281]; “machine learning can be applied to the historical data in order to improve the betting odds.”).
The motivation to combine with respect to claim 1 is applied here. Incorporating Huke’s iterative training loop into the Gonzalez and Barragan combination produces the predictable result of real time recalibration of odds to match user behavior.
In regards to claim 16, Huke further teaches the method of claim 8, wherein the machine learning algorithm implemented on the random number generator learns trends and improves analyzing, calculating, identifying, and weighting the adjusted wager odds from historical determinations (Par. [3281]; “In the embodiments, machine learning can be applied to the historical data in order to improve the betting odds. Correlations between event outcomes and available parameters can be analyzed in advance and in real time by an "Odds Module" to give accurate and up-to-date odds.”).
The motivation to combine set forth above with respect to claim 15 applies here.
Conclusion
Accordingly, claims 1-20 are rejected.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BUSHIRA MUSA whose telephone number is (571)272-9156. The examiner can normally be reached Mon-Fri 7:30am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached at 5712701344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/B.M./Examiner, Art Unit 3715
/KANG HU/Supervisory Patent Examiner, Art Unit 3715
