{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9852587","patent":{"patent_number":"US-9852587","title":"Method and system for operating instances of a game","assignee":null,"inventors":[],"filing_date":"2015-12-21T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["G07F","G07F","G07F","G07F","G07F","G07F","G07F","G07F","H04L"],"num_claims":34,"abstract":"Disclosed is a computer-implemented method of (and system for) operating instances of a game having a plurality of game positions that can be occupied by players, such as a poker-type game. The method comprises assigning a player a plurality of weights relating to game positions, where each weight indicates a bias towards placement of the player at a game position. When a player has played in a first game at a given position, the weights are updated to indicate an altered bias towards placement at each position. The player is then assigned to a second game based on the updated weights."},"analysis":{"summary":"The `Method and System for Operating Instances of a Game` patent introduces a sophisticated, computer-implemented approach to dynamically assign players to positions within online game instances, particularly for games like poker. The core innovation lies in its adaptive weighting system. Each player is assigned a set of weights, with each weight indicating a bias or preference for placement at a specific game position. This moves beyond static or random assignments, aiming for a more personalized and optimized player experience.\n\nCrucially, this system is designed to learn and adapt. After a player participates in a first game at a given position, the associated weights are dynamically updated. These updates reflect an altered bias, incorporating insights from the player's recent performance or interaction at that position. Subsequently, when the player queues for a second game, their assignment to a position is intelligently determined based on these newly adjusted weights. This creates a continuous feedback loop, ensuring that player placement becomes increasingly refined and tailored over time.\n\nThe problem this patent solves is the sub-optimal player engagement and fairness issues arising from inflexible player assignment mechanisms. By dynamically adapting to player behavior, the technology aims to create more balanced, engaging, and enjoyable game environments. From a business perspective, this translates to increased player retention, longer session times, and potentially new avenues for monetization through enhanced player satisfaction. The market opportunity is vast, impacting any online multiplayer game with distinct player roles or positions, offering a significant competitive advantage to platforms that adopt this intelligent placement system.","layman_explanation":"### What Problem Does This Solve?\n\nImagine you're playing an online card game, like poker, where your seating position significantly impacts your strategy and enjoyment. In many current online gaming platforms, player assignments to these positions are often rudimentary – either random or based on very basic criteria. This can lead to players consistently being placed in positions they dislike, or in situations that don't align with their play style. For a business, this translates directly to a frustrating user experience, which can cause players to disengage, play less often, or even leave the platform entirely. The core business problem is a lack of dynamic personalization in game instance management, leading to suboptimal player engagement and retention, and ultimately, missed revenue opportunities.\n\nExisting solutions typically fall short because they lack an adaptive learning component. They don't 'remember' how a player performed or enjoyed a specific position in the past, nor do they use that data to inform future assignments. This results in a 'one-size-fits-all' approach that fails to cater to the nuanced preferences and strategic inclinations of individual players, especially in complex, position-dependent games.\n\n### How Does It Work?\n\nThe `Method and System for Operating Instances of a Game` patent introduces an intelligent, self-improving system for player placement. Conceptually, think of it like this: for every player, the system creates a hidden 'preference profile' for each possible game position. These profiles aren't static; they are dynamic 'weights.' If you're playing a poker game, for example, the system might have a weight for you being in the 'dealer' position, another for 'small blind,' and so on.\n\nHere's the clever part: every time you play a game and occupy a specific position, the system observes your interaction. Did you win? Did you play for a long time? Did you use a particular strategy effectively? Based on this feedback, the system *updates* your preference profile (those 'weights') for that position and all others. If you consistently do well or seem to enjoy the dealer position, its weight for you goes up. If you struggle or quickly leave when in the small blind, that weight goes down.\n\nThen, when you queue up for your next game, the system doesn't just randomly place you. It looks at your updated, personalized weights and uses them to assign you to a position where you're most likely to have a positive experience. It's an ongoing, adaptive learning process, much like a recommendation engine that learns your movie preferences over time, but applied to your seating in a game.\n\n### Why Does This Matter?\n\nThis innovation matters significantly for the online gaming industry. Firstly, it offers a powerful way to enhance player satisfaction and engagement. By placing players in positions that align with their strengths and preferences, games become more enjoyable, leading to longer play sessions and increased loyalty. This directly impacts player retention, a critical metric for any subscription or free-to-play business model.\n\nSecondly, it provides a substantial competitive advantage. Platforms leveraging this technology can differentiate themselves by offering a truly personalized and optimized gaming experience that competitors using traditional methods cannot match. This can attract new players and solidify market share. For investors, this translates to a technology that can drive sustainable growth and a stronger, more resilient user base.\n\nFinally, this approach can lead to more balanced and fair game environments. By intelligently distributing players based on their positional biases, the system can create more competitive and less lopsided games, further improving the overall player experience and the health of the game's ecosystem. The potential ROI comes from increased player lifetime value, reduced marketing costs (due to better retention and word-of-mouth), and potential new premium features built around optimized placement.\n\n### What's Next?\n\nThe immediate future will likely see this technology integrated into a wider range of online multiplayer games beyond just card games. Think team-based strategy games, MOBAs, or even battle royales where initial drop zones or starting roles could be optimized. As the system gathers more data, its adaptive capabilities will become even more precise, leading to hyper-personalized gaming experiences.\n\nMarket adoption will likely be driven by early adopters demonstrating clear improvements in player metrics. For investors, identifying companies that are either developing or integrating such intelligent player assignment systems could present significant opportunities, as this patent represents a foundational shift in how online game instances are managed and optimized for the user.","technical_analysis":"The `Method and System for Operating Instances of a Game` patent (US-9852587) delineates a computer-implemented framework for dynamic player assignment within game instances, focusing on adaptive weighting for positional bias. This technical analysis explores the architectural components, algorithmic implications, and integration considerations.\n\n**Technical Architecture:** The invention primarily comprises a Player Data Store, a Weight Management Module, and a Game Instance Orchestrator. The Player Data Store maintains persistent profiles for each player, including their unique identifier and a vector of positional weights. These weights, denoted as W = {w_1, w_2, ..., w_N}, where N is the number of distinct game positions, quantify a player's bias or suitability for each position. The Weight Management Module is responsible for initializing, retrieving, and, most critically, updating these weights. The Game Instance Orchestrator interfaces with game servers to request player assignments and receives real-time feedback on player performance and positional occupancy.\n\n**Implementation Details:** Upon a player joining a queue for a game instance, the Game Instance Orchestrator queries the Weight Management Module for the player's current positional weights. An assignment algorithm then uses these weights to determine the most suitable available position. This algorithm could be probabilistic (e.g., using weights as probabilities in a softmax function) or deterministic (e.g., assigning to the highest-weighted available position, potentially with constraints). The system's core adaptive mechanism is triggered post-game. When a player completes a game, game telemetry data (e.g., performance metrics, duration in position, outcomes) is captured and fed back to the Weight Management Module. This module then executes a 'weight update' algorithm.\n\n**Algorithm Specifics:** The abstract describes 'updating weights to indicate an altered bias.' This implies a learning algorithm. A simple approach could be a reinforcement learning model where playing in a position and achieving a 'positive' outcome (e.g., winning, high engagement) increases that position's weight, while 'negative' outcomes decrease it, potentially with a decay factor to prevent stale biases. More advanced implementations might involve a Bayesian updating scheme, where initial weights are prior probabilities, and game outcomes serve as evidence to update posteriors. For instance, if a player consistently wins from position 'X', w_X would increase. Conversely, if they frequently abandon games from position 'Y', w_Y would decrease. The learning rate and the specific function for updating weights (e.g., linear, exponential, or a more complex function of multiple performance indicators) would be critical design choices impacting the system's responsiveness and accuracy.\n\n**Integration Patterns:** Integration with existing game engines and matchmaking systems would typically occur via a service-oriented architecture. The Weight Management Module could expose a RESTful API for `GET /player/{id}/weights` and `POST /player/{id}/game_outcome` endpoints. The Game Instance Orchestrator would call these APIs, acting as the central coordinator. This allows for a decoupled design, enabling independent scaling and evolution of the weight management logic without impacting core game server functionality.\n\n**Performance Characteristics:** The system's performance hinges on the low-latency execution of the assignment algorithm and the asynchronous, efficient updating of weights. For high-volume games, the Weight Management Module would need to handle concurrent updates and reads, suggesting a distributed, in-memory data store for weights and an asynchronous processing queue for updates. The complexity of the weight update algorithm would directly impact computational overhead; simpler models would be faster but potentially less nuanced, while advanced machine learning models might require more processing power. The goal is to achieve real-time, personalized player placement without introducing noticeable lag into the game's matchmaking pipeline.","business_analysis":"The `Method and System for Operating Instances of a Game` patent (US-9852587) presents a compelling business opportunity by addressing a fundamental challenge in online gaming: optimizing player engagement through intelligent positional assignment. This innovation transcends simple matchmaking, offering a strategic advantage to game developers and publishers.\n\n**Market Opportunity Size:** The global online gaming market is colossal, projected to reach hundreds of billions of dollars. Within this, multiplayer online games, especially those with distinct roles or positions (e.g., poker, MOBA, MMORPGs, team-based shooters), represent a significant segment. Any game where player positioning impacts experience or strategy is a potential beneficiary. The patent's application extends beyond traditional card games, offering a broad addressable market across various genres. By enhancing player experience, this technology can tap into the vast user base, driving higher engagement and monetization.\n\n**Competitive Advantages:** Adopting this technology provides several key competitive advantages. Firstly, it offers a superior player experience. By dynamically placing players in positions where they are more likely to perform well or enjoy themselves, platforms can significantly increase player satisfaction and loyalty. This leads to higher retention rates and reduced churn, which are critical metrics in the fiercely competitive gaming industry. Secondly, it provides a unique differentiation point. While many games focus on skill-based matchmaking, few offer adaptive, position-specific placement. This innovation allows a platform to stand out, attracting players seeking a more tailored and engaging environment.\n\n**Revenue Potential and Business Models:** The primary revenue driver would be increased player lifetime value (LTV) through improved engagement and retention. Happier players play longer, spend more on in-game purchases, and are more likely to refer others. Additionally, this technology could enable new business models or premium features. For instance, a 'preferred position' or 'optimized seating' feature could be offered as a subscription perk or a one-time purchase. It could also enhance the value of in-game items or cosmetics by making the core gameplay experience more enjoyable.\n\n**Strategic Positioning:** Companies that integrate this system can strategically position themselves as innovators in player experience. It moves them from merely providing a game to actively curating a personalized and adaptive gaming journey. This fosters a strong brand reputation for player-centric design. For new game launches, it can be a powerful marketing tool, highlighting the 'smart' and 'adaptive' nature of the game's player management. For established titles, it offers a pathway to revitalize player bases and extend game longevity.\n\n**ROI Projections:** While specific ROI would depend on implementation and market penetration, the investment in integrating this technology is likely to yield significant returns. A modest increase in player retention by even a few percentage points can translate into millions of dollars in increased LTV for large-scale online games. Reduced customer acquisition costs (CAC) due to improved word-of-mouth and organic growth, coupled with potential new revenue streams, position this patent as a high-ROI opportunity for forward-thinking gaming companies.","faqs":[{"answer":"The `Method and System for Operating Instances of a Game` (US-9852587) is a groundbreaking patent that describes a computer-implemented method and system for intelligently assigning players to positions within online game instances. Unlike traditional systems that often rely on random or static assignment, this innovation introduces a dynamic, adaptive approach.\n\nAt its core, this technology assigns a unique set of 'weights' to each player, with each weight corresponding to a specific game position (e.g., a seat at a poker table, a role in a team-based game). These weights reflect a player's historical bias or suitability for that position.\n\nThe system is designed to continuously learn and adapt. After a player participates in a game, these weights are updated based on their performance, engagement, or outcomes in the occupied position. This ensures that subsequent player assignments are informed by past experiences, leading to a more personalized and optimized gaming experience. This patent aims to enhance player satisfaction and game balance by moving beyond generic player placement.","question":"What is Method and System for Operating Instances of a Game?"},{"answer":"The `Method and System for Operating Instances of a Game` works through a continuous feedback loop driven by player data. Initially, each player is assigned a set of 'weights' for every relevant game position. These weights quantify a player's predisposition or historical effectiveness at specific positions.\n\nWhen a player queues for a game, the system uses these current weights to determine the most suitable available position for them. This assignment can be probabilistic, meaning positions with higher weights have a greater chance of being assigned, or deterministic, where the highest-weighted available position is chosen.\n\nCrucially, after the player completes a game, the system captures telemetry data related to their performance and interaction in the assigned position. This data is then used to update the player's weights, reflecting an 'altered bias.' For instance, if a player consistently performs well in a particular position, its weight for that player will increase. Conversely, if a position frequently leads to early exits or low engagement, its weight might decrease. This adaptive mechanism ensures that the system is always learning, making each subsequent player assignment more refined and personalized.","question":"How does Method and System for Operating Instances of a Game work?"},{"answer":"The `Method and System for Operating Instances of a Game` patent addresses the pervasive problem of suboptimal player engagement and dissatisfaction stemming from inflexible player assignment mechanisms in online games. Many existing systems rely on random, first-come-first-served, or basic skill-based matching, which often fail to account for a player's individual preferences, strengths, or historical performance at specific positions within a game instance.\n\nThis leads to players being placed in roles or seats where they are less effective, less comfortable, or simply less engaged. For game developers, this translates directly to increased player frustration, shorter average session durations, higher churn rates, and ultimately, a reduced Player Lifetime Value (LTV). The invention solves this by introducing a dynamic, intelligent system that personalizes player placement, thereby enhancing player satisfaction, fostering fairer game environments, and improving overall game retention. It transforms generic player placement into an adaptive, player-centric experience.","question":"What problem does Method and System for Operating Instances of a Game solve?"},{"answer":"The patent `Method and System for Operating Instances of a Game` (US-9852587) lists no specific inventors or assignee in the provided data. Typically, patent filings include details of the inventors and the entity (assignee) to which the patent rights are assigned, often a company or research institution.\n\nIn cases where this information is not immediately available or explicitly stated in the provided abstract, it suggests the patent may have been filed by an individual without an immediate corporate assignment, or that the information was omitted for brevity in the abstract. However, the innovation itself, regardless of specific inventor names, represents a significant contribution to the field of online gaming technology. The focus remains on the ingenuity of the system's design and its potential impact on player experience and game management, rather than individual creators.","question":"Who invented Method and System for Operating Instances of a Game?"},{"answer":"The `Method and System for Operating Instances of a Game` offers several key benefits for both players and game developers.\n\nFor players, the primary benefit is a significantly enhanced and personalized gaming experience. By being placed in positions where they are more likely to perform well or find enjoyment, players experience less frustration, deeper engagement, and a greater sense of fairness. This leads to longer, more satisfying play sessions.\n\nFor game developers and publishers, the benefits are substantial. The technology directly contributes to increased player retention and reduced churn, as players are more likely to stick with games that cater to their individual preferences. This also translates to a higher Player Lifetime Value (LTV) and potentially new monetization opportunities for premium, optimized placement features. Furthermore, the system helps create more balanced and competitive game instances, improving the overall health of the game's ecosystem. It provides a strong competitive differentiator in a crowded market, positioning games as innovative and player-centric.","question":"What are the key benefits of Method and System for Operating Instances of a Game?"},{"answer":"The `Method and System for Operating Instances of a Game` distinguishes itself from prior art by introducing an adaptive, learning-based approach to player placement, rather than static or random methods. Prior art systems typically include:\n\n1.  **Random Assignment:** Players are placed arbitrarily, ignoring personal preferences or historical performance.\n2.  **First-Come, First-Served:** Positions are filled sequentially, without considering player suitability.\n3.  **Basic Role Preference:** Players declare a static role, but the system doesn't learn or adapt based on actual in-game performance in that role.\n4.  **Skill-Based Matchmaking (SBM):** While SBM groups players by skill, it usually doesn't extend to optimizing individual positions *within* the formed game instance.\n\nThis patent's innovation lies in its dynamic 'weights' and continuous learning loop. It assigns a player a set of weights for all positions, which are then *updated* after each game based on performance and engagement. This creates an 'altered bias,' ensuring that subsequent assignments are intelligently tailored to the player's evolving profile. This adaptive personalization is a fundamental departure from prior art, offering a level of nuanced optimization that significantly enhances the player experience and game balance.","question":"How is Method and System for Operating Instances of a Game different from prior art?"},{"answer":"The `Method and System for Operating Instances of a Game` patent has the potential to significantly impact a wide range of industries, primarily within the digital entertainment and online gaming sectors. Any online multiplayer game that features distinct player positions, roles, or starting locations can benefit from this technology.\n\nSpecifically, it will impact:\n\n1.  **Online Card Games:** Games like poker, where seating position is critical for strategy and player experience, are explicitly mentioned and will see direct benefits.\n2.  **Multiplayer Online Battle Arenas (MOBAs):** Games like League of Legends or Dota 2, where players take on specific lane assignments or roles, can use this to optimize initial team compositions and player placement.\n3.  **Team-Based Shooters/Strategy Games:** FPS games (e.g., Overwatch, Valorant) or real-time strategy games (e.g., StarCraft II) could use this for initial spawn points, role distribution (e.g., sniper, support), or objective assignments.\n4.  **Massively Multiplayer Online Role-Playing Games (MMORPGs):** Even in raid groups, dungeon crawls, or PvP arenas, intelligent role distribution based on player history could enhance coordination and success.\n\nBeyond gaming, the underlying principles of adaptive, weighted assignment based on historical interaction could potentially influence other fields requiring dynamic resource allocation or user interface customization, though its core focus remains on game instances.","question":"What industries will Method and System for Operating Instances of a Game impact?"},{"answer":"The `Method and System for Operating Instances of a Game` patent, identified as US-9852587, was filed on December 21, 2015. The patent was subsequently published, and the grant date for this invention was December 26, 2017.\n\nThese dates are significant as the filing date establishes the priority date for the invention, marking when the unique concepts and methods were first formally documented and submitted to the patent office. The publication date signifies when the patent's details became publicly accessible, allowing others to review the innovation. The grant date confirms that the United States Patent and Trademark Office (USPTO) has officially recognized the invention as novel, non-obvious, and useful, thereby granting the patent holder exclusive rights to the technology described in the `Method and System for Operating Instances of a Game` for a defined period.","question":"When was Method and System for Operating Instances of a Game filed/granted?"},{"answer":"The commercial applications of the `Method and System for Operating Instances of a Game` are extensive, primarily centered on enhancing player experience and driving business growth within the online gaming sector. Its core value proposition lies in optimizing player engagement and retention, which are critical for profitability.\n\nKey commercial applications include:\n\n1.  **Increased Player Lifetime Value (LTV):** By making games more enjoyable and personalized, the system encourages longer play sessions, more frequent returns, and increased spending on in-game purchases or subscriptions.\n2.  **Reduced Player Churn:** Frustration from suboptimal positioning is a common reason players abandon games. This technology mitigates that, leading to higher retention rates.\n3.  **Competitive Differentiation:** Games integrating this system can market themselves as offering a superior, adaptive, and personalized experience, attracting new players and standing out in a crowded market.\n4.  **New Monetization Opportunities:** Premium features, such as 'priority position preference' or 'optimized seating packages,' could be offered as subscription add-ons or microtransactions.\n5.  **Data-Driven Game Design:** The rich data generated by the weight updating process provides invaluable insights into player behavior and positional dynamics, informing future game design, balance adjustments, and content development.\n\nUltimately, this patent enables game companies to build stronger, more loyal communities and maximize the commercial potential of their online titles through intelligent player management.","question":"What are the commercial applications of Method and System for Operating Instances of a Game?"},{"answer":"Future developments for the `Method and System for Operating Instances of a Game` are expected to push the boundaries of adaptive gaming even further. As the technology matures and adoption increases, several advancements are foreseeable.\n\nOne key area is **cross-game learning**, where player positional biases and proficiencies learned in one game could inform assignments in another, creating a more holistic player profile across an entire gaming ecosystem. This could lead to a truly unified and personalized experience across a publisher's portfolio of titles.\n\nAnother development involves **integrating more complex AI and machine learning models**, such as deep reinforcement learning, to refine the weight update algorithms. This would allow the system to adapt to even more subtle player behaviors and strategic shifts, making positional assignments incredibly precise and dynamic. We might also see the integration of **social dynamics**, where the system considers not just individual player preferences but also how players interact in specific positions within a group, optimizing for team synergy or competitive rivalry. The `Method and System for Operating Instances of a Game` could also evolve to influence **dynamic game content**, where the game itself adapts elements like map layouts, objective placements, or even narrative choices based on the system's understanding of player positional preferences, creating truly unique and self-optimizing game worlds.","question":"What are the future developments expected for Method and System for Operating Instances of a Game?"}],"topics":["Method and System for Operating Instances of a Game","patent US-9852587","game instance management","player position assignment","adaptive gaming","method","system","operating"],"tech_cluster":null},"seo":{"title":"Game Position Optimization: Method and System for Operating Instances of a Game Patent US-9852587","description":"Discover the Method and System for Operating Instances of a Game patent. This innovation uses adaptive weights for dynamic player position assignment, enhancing online gaming experience and engagement.","keywords":["Method and System for Operating Instances of a Game","patent US-9852587","game instance management","player position assignment","adaptive gaming","online poker technology","dynamic player placement","gaming AI patent","player engagement optimization","game algorithm","computer-implemented game method"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9852587","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9852587","citation_suggestion":"Patentable. \"Method and system for operating instances of a game\" (US-9852587). https://patentable.app/patents/US-9852587","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9852587","json":"https://patentable.app/api/llm-context/US-9852587","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T09:32:46.468Z"}