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A colleague of mine asked where I found my working definition for one, one-and-a-half and two-sided games that appears in some of my game design lecture material. As far as I know, there is no "official' lexicon for war gaming, so I made it up. In truth, it is not so much a definition of WHAT two-sided gaming is, but rather WHEN you should use two-sided vs. one or one-and-a-half sides in your game design. Perhaps the best way to think about sides in a war game is to take it from the players' perspective, i.e. "Who am I playing against and what is their objective?" and "What is the role of Control?"

If the challenges facing the player team (e.g. the Blue Team) are primarily created by a moderator, facilitator, faculty group or control team whose only purpose in the game is to poke, probe or otherwise stimulate Blue to think about and respond to a problem, often in a pre-scripted manner - in other words, have no gaming winning objective of their own - then it's a one sided game. If the adversary is a separate team from the control group, but under Control's close supervision in order to maintain game pace, direction and overall objective, then you have what we call a one-and-a-half sided game, the half being some aspects of a Red Team. Red in this case is essentially working for Control to assist in achieving the game's larger objective, which is often educational in nature. In this case Red is sometimes referred to as Pink (part White or control cell, part Red cell). In both these cases, Control or a notional Red is performing more of a Devil's Advocate or Anti-Blue role than a Pro-Red role for the purposes of challenging Blue.

If on the other hand, Red gets to play in a dynamic manner to achieve their own victory conditions, then you have a two-sided game (or multi-sided game). From either side's perspective, they are battling against another set of players on equal footing. Neither side has any undue or disproportionate interaction with Control. From an outside observer perspective, the sides are indistinguishable in terms of their purpose - that is, to win the game. Control acts more as an umpire to ensure the game is played according to the rules, and the score is the score.

You know you're probably NOT in a two-sided game:
- If injects are used or the game is MSEL driven.
- If the Red Team is being steered directly by Control.
- Phrases like "keeping Red in their box" are used.
- If Control, in acting as higher authority for both sides, is far more constraining and manipulative of Red than Blue.
- If Red winning runs counter to the game's objective.
- If there is no interest in whether or not Red can or does win.

Two-sided games are more psychologically demanding. Take for instance a computer based game that can be played solitaire (against the computer) or networked with another human opponent, which I have at home. When my son plays against the computer, the game "feels" one or maybe one-and-a-half sided. While he doesn't like to lose to the computer, contrast that against when he plays against his brother on the other computer. The game now is definitely two-sided and the emotional commitment to the outcome is quite a bit higher! As McCarty Little put it, "Now the great secret of its [war game's] power lies in the existence of the enemy, a live, vigorous enemy in the next room waiting feverishly to take advantage of any of our mistakes, ever ready to puncture any visionary scheme, to haul us down to earth." And if that applies to both sides, you have yourself a powerful two-sided game.

 
Posted: 4/27/2010 12:14:18 PM by Professor Peter Pellegrino | with 0 comments


A recent story on NPR (http://www.npr.org/templates/story/story.php?storyId=125588087) casually mixes gaming, simulation and computer programming, as if they were all one in the same. Typical is this quote from a student studying “gaming,” “As soon as I got into computing, I just fell in love with it. I really love the logic behind it. I love the sort of building-something-out-of-nothing sense that you get from it.” Notice he said “computing,” and not “gaming.” Even if that’s what he meant, the two are clearly the same to him.

According to the NPR story, students at Georgia Tech are learning how to design games by studying previous game systems. Game like Go (2,500 years old), Mahjong (2,000 years old) or Chess (1,500 years)? How about those Johnny-come-lately games like Monopoly (100 years)? Nope. The grand-daddy game to be studied…Atari (for those too young to remember, that would be Pong, 1972).

To be fair, Pong was a phenomenon in its day. But why? To understand that, hopefully these degree programs include elements fundamental to game design – any game, not just computer games  – why people play games, the nature of competition vs. cooperation, the concept of flow, the psychology of decision-making under stress, reward and penalty, etc.   That part apparently isn’t nearly as exciting as virtual reality, augmented environments and iPhone apps. But without those fundamentals, what you get is a computer game programmer, not necessarily a game designer.   There’s a reason those previously mentioned games have survived for hundreds or thousands of years, whereas the drawer under the family gaming console is littered with forgotten game cartridges from last year.          

My issue with this story can be summed up by changing the title to this post to “War Gaming and Models & Simulation – It’s All the Same Thing, Right?” In other words, the tendency to see technology as the ends rather than a means to an end. Not that gaming is the ends, either. Gaming, using a board and tokens, playing cards, computer, ball and bat, or just our imaginations can be a powerful learning and discovery tool. At the Naval War College, gaming is used to examine a wide range of pol-mil problems: deterrence, cyber-threats, irregular warfare, conventional conflict, counter-proliferation, future maritime strategy…all with technology no more complex than desktop computers running Microsoft Office.

By focusing on the latest technology, we tend to overlook the most powerful gaming system that’s been around for millions of years – the human mind.      

Posted: 4/6/2010 10:45:43 AM by Professor Peter Pellegrino | with 1 comments


A colleague recently sent me this link to the computer-based variation of the Pandemic board game:
 
 
This is a good example of the kind of game that evolves from examining and mapping a process, in this case, the spread of disease. This entails identifying the critical attributes of the system and understanding their input-process-output relationships. The designer decides which inputs he wants the player to make decisions about, which go into a 'black box' where some process takes place which converts the player inputs (decisions) into an output, in this case, death rates. While those inputs under the player's control are visible (resistance, symptoms, etc), the process is hidden (how and to what extent do all the attributes interact to affect the victory condition). Players via their choices try to influence the output to their favor in order to win the game. They have some metrics (lethality, infectious, visibility) which are like gauges attached to the black box, which give some clue as to how well we are manipulating some aspects of the machine. Through reasoned trial and error, the player tries to get the black box to produce the right output by making choices analogous to pulling on different levers attached to the box. Decisions are not free; the different levers cost differing amounts to pull, and the player has a budget. In this game, the budget is in the form of Evolution Points. 
 
If you play long enough, you should be able deduce what some of the algorithms are in the process and which levers are more important to pull than others to maximize your chances of winning. That's the game's challenge.
 
But if the black box part of the game is so complicated that you can't even begin to understand (or in a reasonable amount of time begin to learn) the linkage between your actions and the outcomes, you quit playing in frustration. In good game design, there is a balance between the players' skill and the game's difficulty. This is Mihaly Csikszentmihalyi's concept of game "flow." Too hard (complexity>skill) you quit in frustration. Too easy (complexity<skill) you quit out of boredom. A flawed game adds features which are really nothing more than eye-candy; they are levers which are not connected to the machine. You may initially believe that the features are good because they make the game look more 'realistic' or give the players more things to manipulate. Players soon view the game as 'dishonest' - you can manipulate the controls of the game, make decisions, but quite frankly it won't help you win the game.     
 
That's all purely from an entertainment perspective - hiding the process within the black box is part of the game. When it comes to professional war games, we are either trying to give players decision making experience (education) or develop decision making information (research and analysis). Therefore we should insist on looking "under the hood" of any black box or simulation that is a part of a game in order to understand how inputs are converted to outputs, lest game participants take away the wrong lesson or analysts draw the wrong conclusions. And not every simulation programmer is willing to lift that hood.
Posted: 4/2/2010 10:05:07 AM by Professor Peter Pellegrino | with 0 comments