Computer Simulations of Space Societies

© Springer International Publishing AG, part of Springer Nature 2018

William Sims BainbridgeComputer Simulations of Space SocietiesSpace and Societyhttps://doi.org/10.1007/978-3-319-90560-0_1

1. A Virtual Launch into a Computational Cosmos

William Sims Bainbridge¹  

(1)

Arlington, VA, USA

William Sims Bainbridge

Email: [email protected]

This book concerns computer simulation of social behavior related to spaceflight, which is a diverse cluster of topics having no simple definition, but potentially very significant implications for the human future. In a 1973 report, NASA said that astronauts had been trained in simulators for a total of 38,261 h for the Mercury, Gemini and Apollo Programs (Woodling et al. 1973). But these involved physical simulators, having electronic instrumentation, but not the totally virtual simulations that will be the main focus of this book, and they did not emphasize the social factors. To be sure, some simulations were the equivalent of dry runs, or rehearsal sessions, in which flight crews performed roles in a scripted division of labor, but much of that activity over the history of space exploration is usually classified as training, not as computer simulation.

1.1 The Evolving Meaning of Simulation

Consider this apparently clear question: What is a computer simulation? Many plausible definitions could be offered, differing in terms of the complexity of the computational phenomenon, and the particular form of programming that produced it. A picture of a planet displayed on the screen of a computer might fit a permissive interpretation of the simulation idea. Indeed, any picture represents something, rather than being the thing itself, and thus is a simulation.

However, the term computer simulation is usually applied to a dynamic representation of reality, rather than a static image. Consider a standard equation for physics: f = ma. This can be expanded to: force = mass times acceleration. If the force is the thrust from a rocket engine, and we know the momentary mass of the rocket including the fuel it contains, then the formula will predict the momentary acceleration of the rocket, whether in meters per second or feet per second, depending upon the system of units we are using.

But f = ma is not yet a simulation, because it is not inherently dynamic. It becomes dynamic as we enter different numbers into the equation. Suppose we also have a formula for the rate at which the particular rocket uses up its fuel. Then we can put both equations into a computer program inside a loop. Every second, the computer will recalculate the mass of the rocket plus its remaining fuel, as the fuel is expended to produce a constant thrust. The equation f = ma now becomes dynamic, and reveals an increasing rate of acceleration, as the same thrust acts upon a declining mass.

In computer science, the word algorithm is often used, rather than equation or function, and other related terms include procedure, routine, and program. Without great precision, these words refer to segments of computer code that accomplish particular goals, which often require assembling together many smaller components. Some of them are identical to algebraic expressions like f = ma, but others take rather different forms, such as this hypothetical example:

If rocket velocity is high and

rocket direction is down and

rocket and ground are at same location then

display a graphic of explosion;

So far, these examples are not social, and some of the most prominent similar examples from the history of digital computing were not very social either. For example, the ENIAC computer dating from 1943–1946 was designed to calculate the trajectories of artillery, doing so in a series of steps that could reasonably be described as simulation (Stern 1981). While not identical to spaceflight, the simulation was quite comparable to modeling the flight of a spacecraft moving through a complex environment. In an earlier publication, I described this process:

The problem that motivated the U.S. Army to invest in ENIAC was the need for accurate firing tables for aiming artillery during World War II. Many new models of guns were being produced, and working out detailed instructions for hitting targets at various distances empirically by actually shooting the guns repeatedly on test firing ranges was costly in time and money. With data from a few test firings, one can predict a vast number of specific trajectories mathematically, varying such parameters as gun angle and initial shell velocity. The friction of air resistance slows the projectile second by second as it flies, but air resistance depends on such factors are the momentary speed of the projectile and its altitude. Thus, the accuracy of calculations is improved by dividing the trajectory into many short intervals of time and figuring the movement of the projectile in each interval on the basis of the output of the previous intervals and changing parameters (Bainbridge 2004: 221–222).

In the case of ENIAC, the people operating the computer were experts, including its creators, rather than the general public. Several examples from the early chapters of this book will also concern the development of computer simulations as professional research tools. However, given the severe limitations of the current stage the real space program has reached, academic simulation of related social behavior has been rather rare. Two other areas have been rather more productive, educational computer simulations and space-related computer games.

Among the earliest examples of computer simulations open to the general public was an educational computer named the Geniac, dating from 1955, that included two space-related programs in its diverse curriculum. I actually owned one of these challenging but primitive systems in 1956, and explored its capabilities for many weeks. Designed by Edmund C. Berkeley, who co-founded the currently influential Association for Computing Machinery back in 1947, it was a modifiable set of rotary switches assembled and wired by the user to work through various problems that could be expressed in formal logic. As the Wikipedia article for Geniac explains, "The name stood for ‘Genius Almost-automatic Computer’ but suggests a combination of the words genius and ENIAC (the first fully electronic general-purpose computer)."¹

The basic structure was a masonite board and six discs, containing holes to which wires and other components could be bolted, notably a battery and several flashlight bulbs. The instruction manual showed how to set up and use 33 simple electric brain machines, which were circuits that simulated a variety of decision problems. Various numbers of the disks would be bolted to the board, in such a way they could be rotated, representing data input, with one or more lights representing output. Each problem required a particular wiring diagram, such that physically adding bolts and wires was the mode of programming a simulation, always starting from scratch, with no ability to load and unload software as in modern computers. Problem number 8 was Machine for a Space Ship’s Airlock, described thus in the instruction manual:

The airlock of a space ship has: an inner door that goes from the airlock to the inside of the space ship; an outer door which goes from the airlock to the surface of the strange planet which is assumed to have no atmosphere; a pump which pumps the air from the airlock into the space ship; a valve which allows air from the spaceship to flow into the airlock; and a pressure gage which reports the air pressure in the airlock and may be either high or low. There are four lights in the airlock: safe to open the inner door; safe to open the outer door; dangerous to open either door, conditions OK; dangerous to open either door, conditions bad. We want a warning circuit and automatic locks corresponding (Garfield 1955).

The circuit used three disks, with wiring giving each just two positions: (1) Valve from spaceship to airlock: shut or open, (2) Pump from airlock to spaceship: on or off, and (3) Gage showing pressure in airlock: full pressure or zero. A fundamental assumption was that if it was safe to open one of the airlock doors, the other one would be locked, but both would be locked if it was unsafe to open either. For example, if pressure in the airlock is zero, the value is shut, and the pump is off, then it is safe to open the outer door but not the inner door.

This simulated spaceship apparatus tells one astronaut whether it is safe to open one door or the other, but it is never safe to open both. We could imagine a social dimension, if that astronaut is wearing a spacesuit and is currently in the airlock, while a fellow crew member is inside the ship and not wearing a spacesuit, a complexity the simulation apparently assumes but does not explicitly describe.

The second Geniac space simulation is more social but perhaps less realistic, The Uranium Shipment and the Space Pirates. Number 23 in the increasingly difficult set of 33, it requires five of the six disks, each with just two positions but requiring a rather complex circuit to handle all the combinations:

A uranium shipment from one of Jupiter’s Moons, Callisto, to Earth consists of a freighter rocket ship loaded with uranium and a fighter escort rocket ship disguised as a freighter. Space pirates are known to be lurking on one of the two asteroids, Pallas or Hermes. The pirates suspect that one of the rocket ships is a disguised fighter; therefore they may either attack the first ship or wait in hiding for a second ship. The commander of the uranium shipment can send either ship by the Pallas or the Hermes route and can send the fighter either first or second. If the pirate attacks the fighter, the pirate will be destroyed. If the pirate attacks the uranium ship and the fighter has already passed or taken the other route, then the pirate captures the uranium. If the pirate attacks the uranium ship, and the fighter is taking the same route, and is behind the uranium ship, the pirate is destroyed but during the battle, the pirate destroys the uranium ship. Of course, if the pirates do not attack, there is no combat (Garfield 1955).

There are four outcomes: (1) pirates destroyed, shipment safe, (2) no combat, (3) pirates and shipment both destroyed, and (4) pirates capture the uranium. There are two ways in which this 1955 Geniac simulation foreshadows common episodes in the space-related computer games of five and six decades later. First, the outcome of a social interaction is determined by a complex algorithm. The main difference today is that players cannot themselves predict the outcome with any real confidence, because the algorithm includes a random number, and the rules built into the algorithm are concealed from the player.

Second, the excitement associated with the episode requires a degree of simulated violence, in this case life or death outcomes for the pirates and the crew of the uranium ship. Academic social and computer scientists might prefer to avoid violence, and many would argue that any real combat in outer space would not involve human beings, but be millisecond-brief encounters between robot missiles and information-collecting satellites. As intellectually frustrating as it may be at times, humans require a good deal of emotional arousal to motivate their involvement in computer simulations, and violent combat has become a main feature of the examples considered in the later chapters of this book.

1.2 Computational Social Science

In his recent textbook, Introduction to Computational Social Science, Claudio Cioffi-Revilla defines this emerging field as "the interdisciplinary investigation of the social universe on many scales, ranging from individual actors to the largest groupings, through the medium of computation (Cioffi-Revilla 2014)." He maps the field into three subdomains: (1) Big data, which refers to the analysis of very large datasets concerning human behavior, requiring advanced computational facilities to manage potentially terabytes of data and very demanding analytical algorithms. (2) Social networks, which become both theoretically revealing and methodologically demanding as the number of individuals rises into the thousands and the relationships between them expand into multiple dimensions. (3) Computer simulation, which he covers in three distinct chapters, describing methodology, variable-oriented models, and object-oriented models.

Cioffi–Revilla explains that as a methodology, computer simulation of social behavior permits analysis of much greater and thus more realistic complexity than do fixed-form mathematical expressions like f = ma. "This is accomplished by building a computer model of the social system or process under investigation—a virtual world representing relevant aspects of reality—and using that model to perform many kinds of analyses (Cioffi-Revilla 2014)."

One of the first historical examples he cites, Jay Forrester’s World Dynamics, was my own introduction to this field, in a sociology seminar at Boston University that used pre-publication page proofs of this 1971 book as its text (Forrester 1973). Forrester’s Wikipedia page describes him as "the founder of system dynamics, which deals with the simulation of interactions between objects in dynamic systems."² To give but one example of how Forrester’s approach can be applied to spaceflight-related social dynamics, he directly stimulated the highly influential and controversial 1972 study, The Limits to Growth (Meadows 1972). It used complex-system computer simulation, anchored in some empirical variables about the resources and economic dynamics of our planet, to develop scenarios of the possible futures for humanity, efficiently summarized on the study’s Wikipedia page:

The original version presented a model based on five variables: world population, industrialisation, pollution, food production and resources depletion. These variables are considered to grow exponentially, while the ability of technology to increase resources availability is only linear. The authors intended to explore the possibility of a sustainable feedback pattern that would be achieved by altering growth trends among the five variables under three scenarios. They noted that their projections for the values of the variables in each scenario were predictions only in the most limited sense of the word, and were only indications of the system’s behavioral tendencies. Two of the scenarios saw overshoot and collapse of the global system by the mid to latter part of the 21st century, while a third scenario resulted in a stabilized world.³

The controversies surrounding The Limits to Growth are many, most relevant here the possibility that aggressive scientific and technological innovation might expand the scope of the complex human system far beyond the planet Earth, thus becoming limitless. We shall explore simulations of this possibility in later chapters, but we could also consider how Forrester’s method can be applied to analysis of the limits to growth not merely on Earth, but on Mars and indeed on any colonized planet. One step further in the development of that particular orientation toward social science computer simulation would consider the possibility that future civilizations might not consist of networks of colonized planets, each limited primarily to its own resources, but exist on moons and in asteroid belts, such that commerce between settlements would be physically easier and thus cheaper than between high-gravity planets.

The distinction made by Cioffi-Revilla between variable-oriented models, and object-oriented models is logical but not the only way to categorize the alternatives. He refers again to Forrester’s work as an influential example of variable-oriented models, but I naturally think of them as an application of multi-variable statistical analysis, such as these traditional techniques of statistical social science: multiple regression, partial correlations, log-linear analysis, and path diagrams. In their more complex forms, these often distinguish independent variables from dependent variables, with relatively independent or dependent variables intervening between them in a complex diagram, somewhat reminiscent of a family tree in genealogy, but one exhibiting considerable incest. These methods become dynamic models if feedback loops are added, or some independent variables are constantly updated by a stream of new information inputs.

The object-oriented model approach is one I have often used, through what are called multi-agent systems, in which each agent represents a human being, perhaps possessing artificial intelligence to some degree, interacting with many other semi-autonomous agents. As a practical matter, each agent is typically represented by a structured set of memory registers in the computer, acted upon dynamically by the same set of theory-based algorithms, while the agents interact with each other. One of the most influential examples Cioffi-Revilla described is the cellular automata method of Thomas Schelling, and the widely disseminated Game of Life invented by John Conway (Schelling 1960).

Place checkers at random, or in some aesthetically interesting pattern, on a checkerboard. This will be a very simple example of a general principle, and when I programmed an especially ambitious simulation based on this classic idea, it modeled a board with 163,216 squares rather than the traditional 64. The squares on the board are the cells in the cellular part of the name cellular automata, and the automatic part is the mechanistic application of a set of behavioral rules to any kind of change in the pattern of checkers. In a demographic simulation, the checkers might represent people, and when two of different kinds are in neighboring squares, the algorithm could add new checkers near them representing their children. Or, each square could be a person, and the presence of a checker on a square could represent an idea in that person’s mind, such as a political orientation or religious belief that might be influenced by the adjacent squares representing other people. The original Game of Life called the checkers counters and abstractly modeled a hypothetical biological system with these three rules:

1.

Survivals. Every counter with two or three neighboring counters survives for the next generation.

2.

Deaths. Each counter with four or more neighbors dies (is removed) from overpopulation. Every counter with one neighbor or none dies from isolation.

3.

Births. Each empty cell adjacent to exactly three neighbors—no more, no fewer—is a birth cell. A counter is placed on it at the next move.

This game does not seem to model life as we know it on Earth, apparently requiring three parents rather than two, so one might claim that it is a simulation of an extraterrestrial life form. Of course, it is very simplistic. Indeed, that is the real value of this example, because depending upon the starting conditions, the configuration may evolve through many steps, leading to what appear to be more complex patterns. This demonstrates how complexity may evolve from simplicity in a rule-based dynamic system. For example, Fig. 1.1 shows a Game of Life that starts with 10 colored squares in a simple pattern on a large checkerboard.

Fig. 1.1

A game of life at step 1 (left) and step 22 (right)

How the pattern of occupied squares evolves depends entirely of course upon the starting situation, yet often with results a human finds surprising. In the case illustrated in Fig. 1.1, starting with the particular 10 squares never leads back to that pattern, nor to total occupancy of all the 225 cells. Rather, the pattern expands to the 56 cells colored in the right-hand configuration, then constantly recycling: 72, 48, 56 that repeats forever. A different arrangement of 10 colored cells leads to a complex scattering of 102 cells after 100 turns, that drops down to a different configuration of 56 cells at 200 turns, then reaches 166 cells at 500 turns (Bainbridge 2006). Obviously, this game has little resemblance to human social interaction, but in general this kind of simulation illustrates how complex systems may behave in ways that defy human prediction, even if they are totally deterministic (Eve et al. 1997).

As Cioffi-Revilla documents, many social science simulations follow either the variable-oriented or object-oriented approach, yet many of those described in this book are more complex, not only combining both of the approaches he emphasizes with each other and with other methods including injection of random events, but significantly incorporating human beings into the system. Very different from the Game of Life, but as its name implies rivalling it, is Second Life, a non-game virtual world that includes many socially relevant space-related simulations.

1.3 A Creative Virtual World

Since its launch in 2003, Second Life has been the most significant virtual world primarily serving as the computational environment for sharing user-created objects, locales, and computer simulation programs. It was by no means the first example of its species, and much honor belongs to Active Worlds, which launched in 1995. The relative success of Second Life was a result of synergy between the state of the marketplace and the technology in the first years of the twenty-first century, but much credit also belongs to the team that developed it, Linden Lab in San Francisco.

At no cost, a potential user may register with Linden, download some relatively small software, and create an initial avatar. The first time the user logs in, the avatar is in a starter zone of the equivalent of an entire planet, most of which mimics Earth. After wandering around a while to get accustomed to the system, the user may open the search tool of the interface, set it to seek only places rather than people and groups, and enter a search term like spaceflight. Among the first hits will be the International Spaceflight Museum, and clicking a teleport button will send the avatar there.

Figure 1.2 shows an avatar at a literal high point in the museum, the top of a tall pillar, with many full-sized models of real launch vehicles in the background, spread out over a really wide area. Immediately around the avatar is a simulation of the solar system, like an old-fashioned mechanical orrery that depicts the planets quite large in comparison to their orbits, and the sun rather small. The planets move realistically in their orbits, however, and the avatar has gone into levitate mode to hover in mid air as if he were himself a world. This picture is a screenshot taken March 25, 2017, but the exhibits are several years older.

Fig. 1.2

The international spaceflight museum in Second Life

Below and to the right of the avatar is a sign identifying the orrery as the Solar System Simulator. Clicking the mouse of the user’s computer on it links to a page in an online wiki, that reports it was built by Troy McLuhan on some unknown date prior to 2007 December 31. Using the Second Life interface’s search tool for Troy McLuhan fails to turn up an avatar by that name, evidence that combined with the uncertain date of the orrery suggests that he is no longer active in Second Life, although most users currently employ pseudonyms. The wiki reports these technical features of the simulation: The orbital elements (such as eccentricity) are assumed to be constant at the values they had on January 1, 2000. Interplanetary distances use a conversion factor of 0.7 m per Astronomical Unit (AU). Planetary radii use a conversion factor of 0.0246 mm per km. The Sun is not to scale. If it were to scale, you could place 109 Earths side-by-side inside it.⁴

Some distance behind the planet Jupiter, in this image, stands a replica of the Proton booster, which Wikipedia reports was a family of rockets that launched 412 times over the years 1965–2012. The sign identifying the model links to a similar wiki page to the orrery one, saying it was built by Jamey Sismondi on an unknown date prior to 2007 December 31. Searching that name in the Second Life database also fails to turn up a current avatar. Thus, the Solar System Simulator is not only a museum of the history of spaceflight technology, but also an historical archive of the history of virtual worlds, probably catalogued early in 2008. The description of this particular exhibit concentrates much about the social history of spaceflight in a very few words:

The Proton rocket was originally developed in 1965 by the USSR (the former Soviet Union) as one of that country’s first non-ballistic missile designs. The Proton was designed by Vladimir Nikolayevich Chelomei to compete with the larger N-1, designed by Sergey Korolev. Intended for use in the Soviet lunar program, the basic Proton rocket, the Proton-K, was the largest Russian launch vehicle to attain operational status. The Proton is a liquid-fueled design that relies upon toxic, hypergolic fuels. It is a controversial and dangerous combination as several vehicles were lost to failure before the booster became the stable workhorse it now is. Over the years, a variety of booster engine combinations were used, resulting in a number of rocket configurations. Three-stage versions of the Proton-K have been used to launch the Russian elements of the International Space Station (ISS), Zarya and Zvezda, in excess of 20 tons each. The latest version of the Proton lifted a DirecTV broadcast satellite in 2005 but a Proton-M launch in March of 2006 resulted in the failure of the payload to achieve geo-stationary orbit.⁵

Apparently, this text is a decade old, because it does not mention the history of Proton rockets after 2006, and we certainly would have expected a current overview to mention the last flight in 2012. Shifting world history is reflected in the reference to the former Soviet Union, and the Russian elements of the International Space Station. Interaction of individuals and teams is exemplified by the competition between Chelomei and Korolev. The evolution of mass communication technologies is suggested by the reference to a DirecTV broadcast satellite. Thus the documentation associated with a static virtual model of a rocket launch vehicle gives it multiple kinds of social significance.

Social life within Second Life has many dimensions, but the dynamic interplay between enduring groups of avatars and special events is especially interesting and easy to illustrate in connection with social simulations concerning spaceflight. Figure 1.3 records the April 2009 celebration of First Contact Day in Second Life. As a surprisingly significant wiki named Memory Alpha reports, First Contact Day was a holiday celebrated to honor both the warp 1 flight of the Phoenix and first open contact between Humans and Vulcans on April 5, 2063 in Bozeman, Montana. On Earth, children were given a day off from school, a fact that Captain Kathryn Janeway remembered was really the only way it was celebrated.⁶ So, the anniversary of an historical event was celebrated 54 years before it occurred.

Fig. 1.3

Celebration of first contact day in Second Life, 2009

I attended this event myself, in the guise of my original Second Life avatar, Interviewer Wilber, who was created November 25, 2006, and described it at some length in my recent book Star Worlds: Freedom Versus Control in Online Gameworlds (Bainbridge 2016). It was organized by Mike Calhoun, leader of a Star Trek group called United Federation Starfleet. It is not merely a fan club, but a futurist organization with a serious vision based on the philosophy of Star Trek’s creator, Gene Roddenberry, as Calhoun explains on its website: United Federation Starfleet, or UFS for short, started as a dream…..a dream to realize and bring Gene Roddenberry’s vision to life within the realms of a metaverse community. As Mr. Roddenberry said, ‘If man is to survive, he will have learned to take a delight in the essential differences between men and between cultures. He will learn that differences in ideas and attitudes are a delight, part of life’s exciting variety, not something to fear.⁷

In Fig. 1.3, two dozen members of United Federation Starfleet can be seen, named in the text placed by the interface over their heads. They listen to a rousing speech by Calhoun, who stands before the full-scale model of the Phoenix, the first human spacecraft capable of exceeding the speed of light, using warp drive. The first flight in 2063 triggered first contact with the extraterrestrial Vulcan civilization, because the Vulcans had scrupulously obeyed the Prime Directive, a general rule against influencing and thus openly interacting with any civilization that has not yet itself developed interstellar travel. Thus, the values of the Star Trek community imagine a complex interplay of cultures that must be allowed to develop naturally, following whatever principles they themselves decide, so long as they do not harm other civilizations. Human civilization must advance over the coming decades, for example in its conception of gender roles, as illustrated by the Janeway mentioned in a quotation. She does not exist, and yet she has a Wikipedia page:

Vice Admiral Kathryn Janeway is a fictional character in the Star Trek franchise. As the captain of the Starfleet starship USS Voyager, she was the lead character on the television series Star Trek: Voyager, and later a Starfleet admiral, as seen in the 2002 feature film Star Trek: Nemesis. Although other female captains had appeared in previous Star Trek episodes and other media, she is, to date, the only one to serve as the central character of a Star Trek TV series. She has also appeared in other media including books, movies (notably Nemesis), and video games. In all of her screen appearances, she was played by actress Kate Mulgrew.⁸

Thus, Janeway is a legendary hero—heroine having become an obsolete concept—who exists both as an abstract principle of women’s progress and as a role played by an actor—actress having also become obsolete. Figure 1.4 shows one of my other Second Life avatars, Barbara Sims—given that sims are simulated locations in Second Life lingo—standing on a stairway high up the side of a tall exhibit built for the 2012 science fiction convention held annually in Second Life. The building below her, in the center, is her Vulcan Anthropological Museum, containing about a hundred exhibits. Most of then she made herself, but many others were donated by fellow Trekkers. At the time, she was a leader of the Vulcan Council in Second Life, a responsibility she relinquished after the convention.

Fig. 1.4

Some exhibit halls in the 2012 science fiction convention

Each of these annual social gatherings required many people to invest time and money, given that there often have been nearly a hundred exhibits comparable to the Vulcan Anthropological Museum. While visiting Second Life is free, there is an extensive internal economy, in which people pay real-world money to Linden Lab to get Linden dollars, to rent virtual land, and to upload from their computers each texture or image they use to decorate the surface of a virtual object. The 2017 convention celebrated the 10th anniversary of this huge virtual simulation of possible futures.⁹

Most virtual worlds related to spaceflight are not workspaces where users can create their own objects, locations, and social events, but pre-designed games, although few resemble traditional definitions of structured forms of play. Many multi-player games have been compared to themeparks, like virtual Disneylands, and until we have considered several examples, formal definitions will remain elusive. The next logical step, after our brief glimpse of the Star Trek community in Second Life, is to consider a virtual version of its entire popular universe.

1.4 The Final Frontier

To provide contrast with the other examples in this chapter, we can compare a popular virtual galaxy based on very different principles, Star Trek Online. I have studied STO extensively over the years through participant observation, publishing three book chapters about it, but here a brief survey will use a wiki as its data source. Very many Star Trek related amateur wikis exist at Wikia.com, including one about STO, but it has only 694 pages and seems not to have been updated recently, so we shall use the official STO wiki, which claims 50,506 pages (13,499 articles) and fully 305,221 registered users.¹⁰ As the more conventional wiki, Wikipedia, reports, each episode of the original television series began with a proclamation: "Space: the final frontier. These are the voyages of the starship Enterprise. Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before."¹¹

Yet ironically, the original Star Trek series broadcast its last episode June 3, 1969, over a month before the July 16, 1969, launch of Apollo 11 that first took humans to the surface of the Moon, and the return from the Moon of the last flight, Apollo 17, was on December 14, 1972. I edited a 2009 issue of the journal Futures, titled Space: The Final Frontier, commenting in my introduction, "The saga of space exploration has long wandered in a strange twilight period, arguably either dawn or dusk, in which the goal of human expansion into the galaxy is being neither achieved nor abandoned (Bainbridge 2009)." Since then, the twilight has extended another decade, yet Star Trek continues to light the way to the stars.

STO is very much oriented toward stories in the style of the Star Trek television series, and does not emphasize free galactic exploration. During interstellar travel, users view the equivalent of a dynamic map, selecting where to send their spaceship, and where they might enter one or another of many limited simulations to undertake one or another kind of mission. The areas of planetary surfaces depicted are quite small, and many missions take place in orbiting space stations. Some story-based missions and also free-form activities involve combat against other spaceships, within limited spheres of space. For our purposes here, that kind of mission offers a good introduction to the way STO conceptualizes space travel in a social context. Therefore, we can start with the wiki page for