There seems to be an increasing desire to study game theory with relevance to medicine. Increasing amounts of medical malpractice lawsuits, interactions between doctors and patients, and doctors and health managers, and so forth, can show this. These interactions of course are shaped by the various behaviors and psychology of doctors, patients, and managers.

One example of game theory can be applied to medical ethics. Riggs offers an example of a neurologist dealing with fundamentalist Christian parents who want their brain dead daughter to be on the respirator at all costs. These are a conflict of several different ethical perspectives that are irreconcilable. Game theory can provide a sort of manner in which medicine can deal with this.

Other articles focus on the relationships of doctors to their patients in the realm of medical consultation. A doctor may be more concerned with the overall health while a patient may want a mere quick fix solution. These differences of behavior and needs will be a conflict that w ill have to be dealt with. There are issues also between managers and doctors as well.

While other professions have adopted game theory into their practice, medicine still remains to adopt it and the models remain to be determined still.

Source

http://careers.bmj.com/careers/advice/view-article.html?id=999

http://qshc.bmj.com/cgi/content/full/13/6/415

http://jme.bmj.com/cgi/content/full/30/4/359?ck=nck

In this course we have discussed the importance of a network’s structure, and how a node’s position in that structure helps to determine the balance of power in that network.  This idea is demonstrated very well in the film The Battle of Algiers (1965).  In this film the French army is engaged in a guerilla-warfare type struggle with Muslim activists.  These activists were blowing up dance clubs and cafés, and the French army was unsure of how to respond to these attacks.  The French colonel, Colonel Mathieu describes the terrorists as a network in the following screenshots from the movie:

The Colonel provides a strategy for addressing the problem of the way the activist leaders have set up their network.  From a strategic standpoint setting the network up in this way is a great advantage for the Algerian activists.  Even if they are captured and tortured, no one in the organization knows the names of more than three other members.  This helps to limit the liability if any one member is caught.  Colonel Mathieu recognizes this problem and develops a plan to unravel the rebels’ network.  As the movie progresses he makes arrests and fills in the names of those captured on his chart, starting from the bottom and making his way up the pyramid.  In this way, even though each of the rebels only knows three other rebels, the Colonel is able to infiltrate their network and eventually capture their leader.

This movie from 1965 was relevant and controversial in its time, but in recent years it has drawn parallels to the situation in Iraq.  In 2003 officials from the Pentagon attended a screening of the video and participated in discussions regarding the movie.  Although the contents of these discussions are closed to the general public, one could theorize that these discussions centered on how the events depicted and lessons learned in the movie should impact U.S. policy in Iraq.  This event is discussed in the New York Times review at   http://www.rialtopictures.com/eyes_xtras/battle_times.html.  Identifying the setup of networks, especially within groups that a county is in conflict with is essential, and even more crucial is the ablility to identify the weaknesses within those networks to undermine their efforts against U.S. aims.

If you’d like to watch the clip for yourself, copy and paste the following address into your web-browser:

http://www.liketelevision.com/liketelevision/tuner.php?channel=955&format=movie&theme=guide

Click on the third listing for The Battle of Algiers (it is divided into five sections) and start at 16:26 in the video.

In class, we discussed the existence of Nash equilibria in Traffic Networks, where the individual travelers hope to pick the route from origin to destination with the lowest travel time. Travel time, however, is not a static factor, as increased congestion on a road results in slower driving speeds and therefore longer travel times. If we consider these equilibria in real-world networks, the assumption must be made that all of the travelers have knowledge about congestion, weather, construction, or any other factors that would effect travel time on all of their possible routes.

In reality, this is obviously not the case. Information regarding traffic conditions on major roads can be heard by word of mouth, on radio stations, or even looked up on websites such as Google Maps and SmarTraveler prior to departure, but conditions often change quickly. With the introduction and increasing popularity of in-vehicle GPS navigation systems, the opportunity to deliver current, accurate traffic conditions is increased even further. In the world of Traffic Engineering, these methods are all Advanced Traffic Information Systems (ATIS), a type of Intelligent Transportation System.

As ATIS become more popular and more common, the question is raised: are benefits encountered by all users, or is there some point of saturation when an additional ATIS user does not experience any benefit. Obviously, if you are the only driver who knows that one road is congestion free, you will choose that route. If every driver has access to the same information, however, nobody has a clear advantage. The following article, “Route Choice, Network Traffic, and Intelligent Transportation Systems” by Randall Hall from USC provides an overview of a number of simulation studies that attempt to answer that question. Hall concludes that providing accurate information will never decrease performance of the network (as others have suggested), but he warns that the main function of ATIS should be to provide confidence for the drivers, and to steer traffic away from dis-equilibrium situations such as traffic jams.

Hall, R.W.

Route choice and advanced traveler information systems on a capacitated and dynamic network

Transportation Research Part C (Emerging Technologies)

Vol. 4, 5, 1996, p. 289

Route choice and advanced traveler information systems on a capacitated and dynamic network

[Must log into Engineering Village as Cornell student to view full text]

Information about ITS/ATIS:

ITS Wikipedia Entry

US DOT ATIS Documents

dab97@cornell.edu

Above is a link to one part of a trio of articles recently published by the Cornell Daily Sun researching financial aid inequalities in the Ivy League and its effect on athletic programs. With athletic scholarships outlawed by the principles of the Ivy League conference, the process of recruiting prospective athletes is much different than almost all other Division I programs. The article in the Sun delves into the issue of financial aid policies, in which athletes are processed equally with all other students. Before 1991, athletes who were being recruited by multiple Ivies could have their financial aid offers matched by the competing schools, creating a scenario where the athlete could choose the school they felt was the best fit without money as a factor. This successfully kept interconference athletics at an equal balance. However, the US Justice Dept sued the Ivy Leagues in that year on grounds that this practice was an illegal restraint of trade and a violation of the Sherman Antitrust Act, forcing the Ivy League schools to calculate financial aid packages according to their own independent standards.

For many prospective athletes, financial aid packages take the place of athletic scholarship and create strong ties and arguably the largest incentive toward choosing a school. Princeton, Harvard, and Yale are able to provide financial aid to students that the other Ivies cannot hope to match, and this goes for their student athletes as well. The result is that these three schools now possess an unfair recruiting advantage over the other schools in the conference. With scholarships non-existent, financial aid takes over as the most visible factor that determines which team the prospective student athlete will choose.

With these factors in mind, recruiting in the Ivy League is a very complex, collaboritve process between coaches and high-school athletes that produces a very interesting game from both perspectives. The simpler game comes from the athlete’s point, as the dominant strategy for them, assuming they are in need of aid, will almost always lie in the largest financial aid package. The coaches’ game produces many other factors and strategies. For example, an Ivy League coach has a certain number of “slots” in which he can get definite admittance for prospective athletes. This restrics the number of athletes he can recruit. Let’s say a Cornell coach is recruiting 9 players for 8 slots, knowing that one player will have to be omitted. His top recruit is also being recruited by Princeton, a school which will most definitely offer more financial aid. If the coach continues to recruit this player and omit a less valued one but the player commits to Princeton, then the coach has lost not only that player but also the player that he omitted. This creates a situation where a coach might not offer a slot to his best potential athlete if he or she knows that a better-endowed school is in competition. Financial Aid and money definitely does play a role in recruiting practices in the Ivy League.

1. http://www.economist.com/displaystory.cfm?story_id=5065558

   http://www.nytimes.com/2008/02/05/technology/05regulate.html

   After today’s discussion of information networks and general breakdown of the internet, I was curious to look at the ongoing battle between the Internet giants Google, Yahoo and Microsoft. During this morning’s lecture we spent some time discussing how the internet was a type of directed network, which included some pages that did not reciprocate the sending of information. Instantly I thought of these corporations and their dominant presence in the internet. These sites serve as perfect examples of “gatekeeper nodes” that we touched on in Week 1. Because of their market share, they control the vast majority of internet navigation and communication.

   As noted in the economist article above, the battle between these sites started to heat up in 2005. Google clearly has been in the driver’s seat for the past year, being the most visited site on the internet. In an effort to catch up, Microsoft had planned to merge with Yahoo so they could take on their rival. This plan is briefly outlined in the Times story listed above. The plans for the historic merger went awry when Yahoo refused the offer from Microsoft this past week. But what if it had gone through? As the article points out, if Microsoft had taken on Yahoo’s market share we may well be in the midst of another antitrust scandal. In the corporate world today, mergers are commonplace and industries are being increasingly controlled by large companies. However, when examining the world’s primary means of communication, I am leery of such polarization. Today’s conversation really made me examine how much I rely on the internet for information and day to day communication. It is just interesting to think how people’s access to the internet would be changed by such a dramatic polarization in the market. Imagine a network with only one or two gatekeepers to the worlds greatest information source. While it seems like a smart business move to make, the outcome could be remarkable. Giving these corporations an unprecedented level of power over our primary information network could dramatically alter the way people communicate in today’s world.

http://www.usatoday.com/sports/2008-02-27-drugs-hearing_N.htm

The prisoner’s dilemma is a classic game theory situation, as it can be applied to a plethora of varied cases. One such case involves the delicate art of athletic cheating. Whether the setting is baseball or mountain biking, each athlete’s dominant strategy is to use steroids. If one athlete uses performance-enhancing steroids while another does not, then the cheater gains a huge competitive advantage over the non-cheater. Thus, many athletes are driven to cheat in order to gain advantage, whether it is to break records or win more games.

The end result, which does not maximize social welfare, is that most athletes use drugs and do not gain any competitive advantage over one another. Therefore, it may be better, especially in terms of cost (drugs are expensive) if all athletes did not use steroids, because they would have saved much money this way. This then maximizes social welfare. Plus, there are additional costs of using steroids, including potential future health degradation and a huge risk of damaging the athlete reputation if caught. Of course, athletes cannot trust each other to be honest, and thus, they cannot arrive and the result where there is no drug use whatsoever.

Additionally, the demand for steroids creates an arms race of sorts between the steroid makers and the sports regulation authorities. This is another prisoner’s dilemma situation. Both the makers and the authorities must keep building better drugs/drug detectors to keep up with each other. If the makers improve their product and the authorities do not, then the makers’ product will have a competitive advantage, and vice versa. Thus, both groups are forced to spend large portions of time and large amounts of cash in their quest for constant innovation.

Thus, game theory offers some insight into why athletic cheating is so rampant in today’s world of sports.

http://www.brown.edu/Administration/News_Bureau/2005-06/05-145.html 

As evidenced every day throughout the world, being selfish pays off. When facing off against each other, the cheater will dominate the philanthropist every time. Game theory supports this conclusion. In the typical public goods game, described here: http://en.wikipedia.org/wiki/Public_goods_game . Players each secretly choose to put a certain amount of their private money into a common pool. At the end of the round, the money in the common pool is doubled and evenly distributed back amongst the players. In this scenario, when the philanthropist faces off against a cheater / selfish player, the selfish player will always come out on top. Being selfish is always the winning strategy. Players can’t afford to be altruists due to the risk of selfishness from others.

Because of this, it has been very difficult for scientists to explain how cooperation has evolved both in human and animal societies, when selfishness seems to  pay off. This phenomena has been dubbed “The Tragedy of Commons”. Three researchers have now come up with a new model for the public goods game that has helped to shed some light on why cooperation is an effective and even dominant strategy. The details of their experiement can be seen in the link at the top of this post. In summary, players were broken off into groups to play the game. Each player then reproduced according to the amount of payoff they had received, and passed their strategy on to their offspring. These players then split up into new groups and repeated the process. After running the game many times, the researchers found that cooperators thrived. This new model, created by three researchers Timothy Killingback, Thomas Flatt, and Jonas Bier, helps to show how cooperation can evolve and thrive, using only population dynamics as an explanation. One of their conclusions was that cooperation appeared to thrive in smaller groups, where their investments payed off, allowing them to dominate the small group and then spread their offspring and through them, their altruism to other groups.

The researchers’ full paper can be found in the June 22, 2006, issue of Proceedings of the Royal Society B: BiologicalSciences. A summary of their work can be found in the link at the top of this post.

I recently stumbled upon news article, which is about a new “web based marketplace where investors and entrepreneurs can make serious investment connections.” I thought this was interesting because it shows the real world applications encompassing many of the things we have been learning about in the past few weeks. Mainly, it shows how the power we have recently been talking about can be applied to some types of businesses such as this one. The basis of this site is very similar to many others, such as ebay and online dating sites. Their function is to be gatekeepers, whether local or not, and match up, or connect two people that have a common goal or interest. They use this inherent power in being a gatekeeper to make money and that is how the website/ business functions. People who use these sites are looking to expand past their own social network into that which they normally couldn’t expand in order to get what they want, whether it be to buy or sell a good, or in this case to invest in companies or even a company looking for investors. This site can create a link which in turn will give both parties what they want, for a small price of course. Many are realizing that this power can be easily tapped through the internet and is a great way to start up a new business, or as in this case expand a business.

In the article it says “Fundability bridges the gap between the fast pace of entrepreneurial startups and the slow and inefficient fundraising process.” This highlights the aim of this new web site, which is to become a gatekeeper for these entrepreneurs who would otherwise have a very difficult time trying to advertise, or expand their network to find people willing to invest, which on their own could take a very long time. Lack of funds drive many startup businesses out of business. The aim is to make it easier to expand their network and thus obtain investors. The web is a powerful tool and many are learning about the power that can be utilized through it, which closely ties to what we have been discussing in lecture recently.

http://www.foxbusiness.com/article/startup-tv-network-

launches-fundability-web-site-connect-entrepreneurs-50_492471_1.html

about www.fundability.com

http://www.last.fm

Last.fm is considered to be the first of its kind, and has been the most successful in its area of service. Essentially, it is a networking service based upon music. Last.fm essentially learns the users preferences in music in a variety of ways, and then creates a radio station based off of the music the user listens to. The most common way that it gets this information is through what it calls “scrobbling”—whenever a user listens to music using their preferred media player, it will take that information and add it to the users profile, where this information will later be used to determine what will be played on the users radio station.

Once the information has been gathered, the networking process comes into play. We can consider users and artists to be nodes on a graph of the network, with edges connecting users that enjoy the same artists, and nodes between artists if people who enjoy the one artist’s music also enjoy another artist’s music. This is how the basic user’s radio station is formed—once they begin listening to music, Last.fm finds music by similar artists—those that are considered the most similar (to an artist) are those which have to most amount of common listeners (to the same artist).

For the most part, this system is effective in helping users find new music, since people who usually listen to a certain song/artist will typically listen to other music that is similar. However, with the most popular artists, there is obviously some problem with the system. Consider an artist like U2. With such a huge fanbase, it seems unlikely that users will have similar preferences in music, or if they do, they will merely include other “Top 40” artists, with no true similarity to the artist in question, U2. This can be seen from their similar artists page on Last.fm, where we find that the top 3 most common artists are Coldplay, R.E.M., and The Police. While these artists do have some things in common, they are not truly the most similar artists to U2 when we consider only their music.

Last.fm has a variety of other options that allow users to access their network in different ways. Each user has a unique “Neighborhood,” i.e., the list of users who listen to similar music. This system is also based upon the same similar artists network, so it can use the same network graph. One can listen to tracks similar to an artist, or similar to another users preferences (such as someone in their “Neighborhood”). However, there are other options that are based upon a different networking system. One can use a “tag” based system that will play songs by artists who have similar “tags.” These “tags” are most commonly used to put the artist’s genre. However, they are also used to put the mood of the artists music, the instrumentation used, their popularity, or even something as arbitrary as “water” (users who put this refer to artists whose names are related to water or who have popular songs about some kind of water). This network has nodes for tags and artists, and an artist who has been given a tag has an edge between themselves and the tag.

In the Wired article “A New Type of Game Turns Web Surfing Into All-Out Information Warfare,” Mary Jane Irwin describes an online game that adds new and exciting dimensions to browsing the Web. In “passively multiplayer online games” (PMOGs), Web users add an application that follows their online activity. The object of the game is to win as many “data points” as possible. Players win or lose points based on which sites they visit. Each player has a supply of objects that they can plant onto websites to defend themselves or deduct other players’ points. For example, players can plant mines on certain pages; the mines will then deduct points from other players when they visit the site. Players can also set up missions for others to complete, which usually involve players going through different sites in order to achieve a goal. Carrying out a mission lets a player earn more objects and points.

In addition to being entertaining, PMOGs allow players to explore different areas of the Web network. As we learned in class, the Web can be thought of as an information network, with nodes acting as pieces of information and edges as links. Missions in PMOGs make full use of the Web as an information network by leading players to different websites and links. Because players take advantage of the information available to them on the Web, the idea of the Web as an information network is strengthened.

PMOGs also allow players to be exposed to parts of the Web network that they may not have encountered before. For instance, the Wired article mentions a mission crafted around the TV show Arrested Development. In the mission, players had to surf through fan sites about the show in order to finish the task. Players who might have never heard of Arrested Development before playing PMOGs ended up learning about something new. Thus, missions can bring previously faraway parts of the network closer together.

There are strong implications that arise from the idea of PMOGs. As mentioned before, players are rewarded (gain points) when they go to certain websites and are punished (lose points) when they go to others. If a player loses points whenever he goes to a favorite site, he may eventually steer clear of the site altogether. On the other hand, if a player is rewarded whenever he goes to a webpage, he may visit that page more often. Therefore, rewards and punishment in PMOGs have great potential in changing user behavior. They may even restructure the Web network: if players have their own websites, they may be more inclined to link to sites where they earn rewards and refuse to link to sites where they are punished.

Furthermore, players in PMOGs have the opportunity to promote their own agenda when they create missions for others. When building missions, players can have others go to sites that support certain political and social views. People with extreme and controversial views can exploit missions to reach an audience that they otherwise may not have come into contact with. For example, someone with a pro-terrorist view could create a mission in which he leads players to sites that support the actions of Al Qaeda and other terrorist groups. While people tend to think that being exposed to different parts of a network is beneficial, it can have possible dangerous consequences.