Leveraging Artificial Intelligence(AI)/Machine Learning(MI) In Gambling Games

Artificial Intelligence(AI)/ and Machine Learning(ML) have been in existence for decades with AI applications being used in a number of different domains. Video games, in particular, have leveraged AI to assist and direct gaming characters/avatars to act in a human way and to assist the characters in their interaction with the game or other  players. Gambling style games have not leveraged AI and Machine learning techniques(to my knowledge). However, this may be changing as "traditional" gambling games have to sort out a way to reinvigorate the space and grow the market and attract a younger audience.  Online gambling potentially provides the ideal  environment for AI/ML because game play   generates a significant  amount of data that can be used to profile players, spot trends, increase revenue per player and increase engagement.

The real question is what form of AI is more appropriate for the  gambling space versus the video game space where some AI is already in use? It is common knowledge that video  games use a "form" of AI. However, the AI  approach used in video games  may or may not be appropriate  for traditional gambling games that are simpler, less "role" playing oriented and lack the  massively multi-player characteristics of some video games. Online poker may be the exception to this characterization.

What are the options in terms of AI approaches?

Machine Learning(ML) - Until recently computer programs have been  hard coded anticipating what a problem will be and  reacting  to  a fixed set of scenarios  providing recommendations or executing code that drives a process to conclusion. Traditionally, computer programs have  not been able to react to events, learn from these events and automatically change a program's behavior  based on that interaction. Machine learning changes all of this as it includes  ways to  react to  unexpected events by analyzing data patterns and making recommendations based on that analysis. This approach could be used in gambling games to   solve the problem of a player continually winning or losing a game, skewed payouts, consistent losses with not enough wins, etc.  In an ML driven environment the games math model, bonus structure and payout structure could be modified during play to improve the overall experience and to increase revenue per player.

Case Based Reasoning(CBR) -  CBR is an AI approach that matches the goal of the outcome with specific "cases" that are appropriate for a scenario. This concept could be extended into the gambling environment  for specific game types,  game "states" and player profiles.  Case based reasoning has been used for diagnostic purposes to determine a specific method to address a symptom or issue. In gaming the case could be the "characteristics" of  game play and or the history of game play of a particular player. It could also be applied to the amount of the "wager" and loses to date or in a game. In a multiplayer or head to head game the game play of the players and opponents could be adjusted over time as the game progresses. Players may also chose a "case/category" to be placed in before the start of a game.

Decision Tree   - Decision trees were some of the first AI systems constructed. A decision tree starts at a point where a problem or goal is stated and then guides an individual or program  through a process of questions and answers to help that person or machine to achieve a goal. These systems are relatively static. Consequently if a scenario has not been experienced or anticipated there is no other option. In a gaming environment  it may be difficult to anticipate all possible scenarios . However, once the decision tree becomes robust it can be an effect coaching tool to help a player execute a reasonable gaming strategy or drive a slot experience based on player profiles.

Neural Networks - Neural networks are essentially 'learning" systems that evaluate behavior  and  or activity and develop "advisory" approaches to solve problems. To be effective neural networks need a constant flow of data. Neural networks would appear to be a good approach for massively multiplayer gambling games  such as poker or perhaps blackjack where a a number of players  continually engage and react in a gaming environment create large and ever changing data sets. Slot games are fertile ground for Neural Networks because they accumulate large data sets that can be associated with a single player and groups of players.

Post Play Analysis Learning  -   Although  reacting to game play activity during a game using AI/ML is the ideal scenario, post analysis of game play data is also important. Mining data from a game data depository that contains game play data that has been accumulated over time is an excellent way to determine trends,  player habits, causes of drop off and engagement. MI in particular is a great way to to do this as MI is geared to evaluating large data sets. The analysis of this data could be used to determine better ways to monetize games, improve the "stickiness" of games.    

It may seem odd to think of   gambling games  as a domain that can take advantage of advanced computing approaches.  However, given the amount of data that is generated from gambling games it actually is a perfect forum for AI/ML.  Slot machines are actually  a form of computing device that accumulate large amounts of data making for an excellent source of data for MI/AI.  From an economic perspective  gambling, relative to other gaming domains, has a high revenue per game coefficient.  This coefficient could be improved through the use of ML/AI. The real challenge is to determine what AI approach or approach is or  appropriate for a given "game".



Kevin Flood is the CEO of Gameinlane and FitCentrix, Inc. Kevin spent time at the Machine/Learning Lab at MIT as a technology transfer fellow engaged in model based reasoning, case based reasoning and rule based systems to enhance diagnostics systems.  He created a company called AI Squared as a result of that research.   Kevin has worked for and with US land based casino operators helping them evaluate social casino and iGaming platforms for the purpose of joint ventures and acquisitions in addition to launching online gambling operations in Europe. Gameinlane is also startup "friendly" understanding the unique value new gaming companies bring to the marketplace.  Kevin frequently speaks at gaming conferences around the world providing him with a unique perspective on this very interesting business sector. Kevin can be reached at kflood@gameinlane.com  and or twitter  at @kflow1776.

What Is NeuroGaming And How Will It Impact The Future Of Gaming and Fitness?

I attended a Neuro Gaming Conference in San Francisco recently to get an understanding of what this sector of gaming was all about and if it was relevant to my two business ventures Gameinlane and FitCentrix . The first question I had  when I entered the conference  was what exactly is NeuroGaming? On the surface it appeared to be a sensationalist futuristic label designed to entice people into and engaging in the conference.  After cruising the product and service booths of the companies commercially involved in the space and listening to the lectures and speakers it became clear that  the term "Neuro"  gaming is very broadly defined encompassing a number of disciplines, products, services and aspirations.

Biologic Sensors - There were a host of vendors that manufactured sensors that could acquire a persons body vitals and state. These sensors acquired EEG, EKG, body temperature, heart rate, blood pressure,etc. to be used as indicators of how someone was reacting to an external stimuli  such as a game. These indicators could also be used to direct a game and personalize it for the state that a person was in. For example, if someone was engaged in a multiplayer game with   other opponents  they could  see and react to another gamers biological reaction to a game and potentially modify their strategy based on that state.  An example of this  would be a poker game where a person's vitals and other bio indicators would be made  aware to other players. This bio signature could be used to change one's strategy or perhaps verify a strategy being taken by a player. In a virtual world game each character in that world could have bio attributes that would establish how they are reacting to the world and the software itself could change or morph based on that bio-feedback.

Kinesiology - Sensing body movement such as hand and feet and leg motion is  also a part of NeuroGaming. Although this is somewhat outside of the pure realm of brain patterns and body chemistry it was a big part of the conference with demonstrations of  sensors on one's arms an legs to see how and where they were acting in space. This type of action could be used in Virtual Reality and  Augmented Reality games  to draw a player's motion and actions into the game.

Bio-Feedback To Determine Emotion, Joy, Fear, etc. - Knowing the state of mind and emotional state of someone playing a game to allow the game to react to a player's "state" was also discussed. The relationship of body markers and these historically fuzzy human attributes appear to be getting closer to being  mapped  and understood from a biological perspective edging closer to the day  when machines/games will react to a stimulate these emotions to enhance the game experience.

Cognition and Learning - There was much discussion about learning, memory and classic cognitive science with many panelists having emerged from the academic world having worked on  a thesis project addressing these topics. Games were discussed that could improve or detect the state of a person's cognitive ability and their memory. The primary focus for most of these games was the aging baby boomer generation and the onset of dementia and  Alzheimer's. Games, with the aid of sensors,  could potentially slow the process or  alleviate these ailments. Governments around the world are funding these projects and treatments emerging from game design that could impact the onset and management of these diseases.

Fitness,  Health, VC's  And The FDA - Although the conference was designated as a "gaming" centric conference there was much discussion of the use of bio feedback devices and sensors for the purpose of getting and keeping people fit. Several references were made by venture capitalists  about this sector and the state a  biofeedback venture(or any venture for that matter) needed to be in to receive VC funding.

They specifically  addressed the FDA certification hurtle as a major concern  in the use of biological sensors for  medical  and health "recommendations.". They saw FDA certification as a danger (really long and expensive process) and as an advantage (barrier to entry). They were very keen on the fitness business model in respect to the  integration of game mechanics and bio sensors to improve engagement and monetization.  They  unanimously  encouraged  the "subscription " business model as a favorite for both the  fitness and health sectors  for its recurring revenue attribute.

The Hardware - Many vendors were promoting their hardware either for bio sensors, feedback or just plan game play. Of  course Oculus Rift (VR) was a headliner given its recent affiliation with Facebook. Augmented (AG) as apposed to VR was also on stage acknowledging the potential impact of Nuero Gaming on the future of digitized reality.

There were a number of EEG, EKG, body movement, body temperature, etc. units on display as well. Overall, the format of these devices was somewhat daunting given there placement on your head, in front of your eyes and attached to the body. Given the rather obvious and somewhat cumbersome nature of these sensors/devices it is unclear what the acceptance and integration potential they have. This is especially true if serious movement is expected to engage in a game or a fitness routine.

Overall, it was great to see the merger of academia, medical device manufactures, and gamers  coming  together to discuss the future of   the merger of these disciplines. It reminded me of the great promise of AI(Artificial Intelligence) back in the day. As with AI we have to see what is actually applicable to the consumer world as opposed to the government/military/academic universe.  However, everything must start somewhere and the merger of machine, game mechanics and biological systems is clearly a focus that is on the of edge  commercial adoption.

Kevin Flood is the CEO of Gameinlane, Inc. Kevin writes  about online games and their impact and integration into iGaming and E-commerce environments. Kevin is a frequent speaker at online game events and conferences in Asia, Europe and the US. Kevin and his Gameinlane team are currently working with online gambling, social gaming and e-commerce companies integrating social gaming with online gaming operations and integrate game mechanics into e-commerce applications.