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I n t e r a c t i v e E n t e r t a i n m e n t

Geogames: DesigningLocation-Based Gamesfrom Classic BoardGames

Christoph Schlieder, Peter Kiefer, and Sebastian Matyas, University of Bamberg

The traditional image of interactive entertainment—games that reduce players’

physical involvement to moving a joy stick—is obsolete. Games researchers and

designers are already integrating complex movement into games; Nintendo’s Donkey

Konga, Sony’s EyeToy, and Konami’s Dancing Stage are good examples. This kind of

game might use simple sensor contact, such as hit-ting a drum or stepping on a dancing mat, or moreintricate forms of movement captured by video orinfrared, such as waving gestures. They involve mov-ing parts of the body but only limited displacementof the body as a whole.

Cognitive psychology’s classification of spatialscales helps clarify the issue of player movement.Daniel Montello1 distinguishes

• figural space, which is smaller than the body andaccessible to haptic manipulation or close visualinspection;

• vista space, which is as large as or larger than thebody but can be apprehended visually from a sin-gle place without locomotion; and

• environmental space, which is larger than the bodyand can’t be experienced without considerablelocomotion.

Location-based games involve body movementsbeyond figural space—that is, beyond the space ofcomputer screens and small 3D objects. They focuson locomotion in vista space, typically a single roomor sports field, or in environmental space, such as aneighborhood or city. Several location-based gameshave been designed for environmental space usinglocalization technologies such as GPS. Some areadaptations of popular computer games, and others

are rather straightforward chase games (see the side-bar “Location-Based Games”).

A third type of game—what we call challenginglocation-based games—combines the intellectualand strategic appeal of classic board games with thereal-time locomotion and physical involvement oflocation-based games. Although the idea of directlymapping classic board games onto the real worldisn’t new,2 we know of no general framework fordesigning such games. Furthermore, a straightfor-ward approach to the spatial mapping of classicboard games doesn’t work. Instead, we developedthe Geogames framework, which uses search tech-niques to identify a single temporal parameter forbalancing sportive versus strategic elements.

Spatial versions of board gamesNot all types of spatial mapping are interesting.

Players consider a location-based game challengingif it addresses both their reasoning skills and theirmotor skills. Neither a chess tournament with outdoorchess pieces nor a 100-meter sprint would constitutea challenging location-based game in this sense.

Board games come in many variants, not all ofwhich are intellectually as demanding as chess or Go.Many of them involve two players, are deterministic(no random element such as dice), and provide fullinformation about the game’s state to each player (nohidden elements such as cards in the opponent’s hand).

Location-based games

introduce an element

missing in interactive

console games: the

physical effort of

sports. Using classic

board games as

templates, challenging

location-based games

add strategic

reasoning to sportive

locomotion.

We concentrate on this rich class of games asa source of inspiration for the strategic ele-ments in our game design and use the termboard game in this narrow sense.

Our running example is a structurally sim-ple, well-known board game: tic-tac-toe. Twoplayers move alternately, placing tokens (thefirst player to move uses “X,” the second “O”)on a 3 � 3-square game board. The player whofirst places three tokens in a row, a column, orone of the two diagonals wins the game.

Physically, board games are played in fig-ural space. To obtain a location-based ver-sion of the game, we must map the game ontovista or environmental space such that eachmove requires the player’s locomotion. Thisintroduces time as a new dimension in thegame. We call the result a spatial version ofthe board game and refer to the process ofproducing it spatialization.

The straightforward approach to spatializa-tion consists of assigning coordinates, or geo-graphic footprints, to each board position. Ageographic footprint can be a point, a polyline,or an area. For tic-tac-toe, we assign a coordi-nate to each of the nine board positions (andto simplify matters, we’ll use points). In thespatial version of a board game, players mustphysically move to a board position to place atoken (an “X” or “O” in tic-tac-toe). The time

it takes to complete a move therefore dependson the distance between the board positions invista or environmental space.

The spatial version of a classic board gameis particularly interesting if it satisfies the fol-lowing requirements:

• Balance of sportive and reasoning ele-ments. A marginal difference in speedshouldn’t lead to a winning strategy (as itdoes in a 100-meter sprint). Also, the gamedesign should handle the problem that wedon’t know in advance who is faster andwho is slower (although in practice there’salways a difference in speed between twoplayers). In setting up tournaments withmultiple unknown players, it’s impossibleto counterbalance speed differences bygiving the slower player a head start.

• Unconstrained choice of geographic foot-prints. The game design should constrainspatialization as little as possible. Ideally, thegame designer should be able to map boardpositions onto any set of geographic loca-tions—for example, to cultural heritage sitesor places of outstanding natural beauty—toincrease players’ interest in the game.

Because of the designer’s freedom to assigngeographic footprints, the spatial version of a

board game generally won’t preserve the dis-tance relationships that hold on the game boardin figural space. For instance, tic-tac-toe’sboard positions don’t need to be arranged in aregular 3 � 3 square, as in figure 1a; thearrangement in figure 1b is just as possible.The latter set of footprints isn’t just a rotatedversion of the previous set: the three top-mostpositions form a row, as do the three bottom-most positions and the three middle positions.

The synchronization problemUnfortunately, a straightforward approach

to spatialization (one that ignores the syn-chronization problem) results in unchal-lenging location-based games. The problemis that board games’ logical appeal is linkedto the complexity of a game’s state space,which changes drastically if the two playersdon’t move in alternation.

Consider the game illustrated in figure 1a.The players’spatial trajectories reveal that theX-player moves faster than the O-player.Obviously, in this case the X-player has a sim-ple winning strategy: take the shortest pathfrom top to bottom through the closest col-umn and win the game after placing the thirdX-token. This spatial version of tic-tac-toeamounts to a race between the two players,which lacks any elements of strategic rea-

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A mobile game is simply a game that runs on a mobiledevice—for instance, Tetris on a smart phone.

Some mobile games use environmental space as playingground. In these location-based games, the players’ positions—and sometimes locomotion—constitute key game elements.Some sort of position-tracking technology, typically GPS, wire-less local area network, or Cell-ID in general packet radio ser-vice or universal mobile telecommunication system networks,is required to play the game. An early and rather simple exam-ple of a location-based game is geocaching, in which playersuse geographic coordinates to find hidden objects using ahandheld GPS receiver as the mobile device (www.geocaching.com). Games with more advanced computational supportinclude Can You See Me Now!1 where players on the streetschase online players, and Pirates!2 where players interact withother players through their avatars in the virtual world.

Augmented-reality games integrate the virtual world of thegame with environmental space at a perceptual level. A well-known example is Human Pacman,3 where human playersrole-play the main game characters.

Pervasive or ubiquitous games such as the Songs of North4

introduce the concept of an omnipresent gaming world thatlets players connect with the game anywhere and anytime.

Through all genres, from location-based to ubiquitousgames, traditional chase games or adaptations from well-

known desktop computer games dominate. Although novelgame concepts exist, for instance Uncle Roy All Around You,5

none of these concepts seems to focus on finding a challeng-ing balance of sportive and reasoning elements. This is exactlywhat geogames are about.

References

1. M. Flintham et al., “Where On-Line Meets On-the-Streets: Experi-ences with Mobile Mixed Reality Games,” Proc. Conf. Human Fac-tors in Computing Systems (CHI 03), ACM Press, 2003, pp. 569–576.

2. S. Björk et al., “Pirates!–Using the Physical World as a Game Board,”Proc. IFIP TC.13 Conf. Human-Computer Interaction (Interact 01),IFIP Technical Committee on Human-Computer Interaction, 2001;www.viktoria.se/fal/publications/play/2001/pirates.interact.pdf.

3. D. Choek et al., “Human Pacman: A Mobile, Wide-Area Entertain-ment System Based on Physical, Social, and Ubiquitous Computing,”Personal and Ubiquitous Computing, vol. 8, no. 2, 2004, pp. 71–81.

4. P. Lankoski et al., “A Case Study in Pervasive Game Design: TheSongs of North,” Proc. 3rd Nordic Conf. Computer-Human Interac-tion (NordiCHI 04), ACM Press, 2004, pp. 413–416.

5. M. Flintham et al., “Uncle Roy All Around You: Mixing Games andTheatre on the City Streets,” Proc. Level Up: 1st Int’l Conf. DigitalGames Research Assoc. (DIGRA 03), 2003.

Location-Based Games

soning. So, we can’t consider this a chal-lenging location-based game. This kind ofrace will occur even for a marginal differencein speed. On the other hand, in a game withstrictly alternating moves (for example, out-door chess), a player’s speed has no impactat all—also an unchallenging board game.

Figure 1b illustrates a challenging location-based game. Here, moves don’t always alter-nate. To put it differently, the task of design-ing a challenging location-based game froma board game involves limiting the occurrenceof multiple moves by the faster player. We callthis the synchronization problem because itsomewhat levels differences between the twoplayers’speed, resulting in a deliberately non-perfect synchrony of moves.

The synchronization problem isn’t a prob-lem of the specific choice of geographic foot-prints and the starting position, as in figure1a. It appears in figure 1b as an effect ofspeed difference between players in muchthe same way as in figure 1a. Nevertheless,we might be tempted to look for a spatialsolution to the synchronization problem, onethat somehow handicaps the faster player.We could try to distort the tic-tac-toe gameboard so that the faster player has to coverlarger distances, as in figure 2. Such anapproach, however, violates both designrequirements listed earlier, with the accom-panying consequences. On the one hand, itforces game designers to determine whichplayer moves fastest; on the other hand, itprevents them from using geographic pointsof interest in the spatialization.

Fortunately, the synchronization problemhas a surprisingly simple temporal solution:after reaching a board position and placing atoken, players must spend a certain synchro-nization time at that position before moving on.

Typically, the game designer will integratesynchronization time into the game by hav-ing the player perform some time-consum-ing tasks, such as solving a puzzle or search-ing for an item. We’ll see later that the lengthof the synchronization time interval consti-tutes the parameter that determines whetherthe spatial version of a board game becomesa challenging location-based game or dete-riorates into either a race-style game (inwhich the sportive element dominates) or aclassic board game (in which the reasoningelement dominates).

The Geogames framework Although a spatial version of tic-tac-toe is

somewhat interesting on its own, designersneed a general method for reusing boardgames as templates for location-basedgames. Our descriptive framework for loca-tion-based games should handle other spa-tial versions of board games or other possi-ble games, such as CityPoker.3 Typically insuch games, a fixed number of players (oftenbut not always two) move between a fixednumber of board positions, called locations,taking up and putting down resources whenthey reach a new position. A resource is any-thing that players can transport and deposit inlocations, such as an X-token in tic-tac-toeor a playing card in CityPoker. The frame-work we created, Geogames, defines the stateof a game by the players’ locations and by thedistribution of resources among players andlocations. The framework describes actionsas transitions between states, including thecombined effect of moving from one loca-tion to another and of taking up or puttingdown resources there.

The following definitions describe theGeogames framework, in which the designercan express a temporal solution to the syn-chronization problem.

Definition: Let P denote a set of players, L aset of locations, and R a set of resources. Astate s = (location, resources) is a tuple of twomappings, location: P � L and resources:R � L � P. S denotes a set of states, usuallya game’s states. An action a on S is a mappinga: S � S. A set of actions is denoted by A.

The first basic constraint for actions is spa-tial coherence: a player can pick up or disposeof a resource only at the player’s current loca-tion, and no resource can appear or disappearat a location without a player’s involvement.To describe the temporal aspect that differen-tiates location-based games from boardgames, the designer assigns a duration to allactions.

The designer also assigns each game statea value that expresses a player’s interest inthat state. In tic-tac-toe, the values of interestare open, X-wins, O-wins, and draw, with theintuitive semantics that open is assigned tonon-end-game states. The designer specifiesthe synchronization interval’s length (sync-Time) as a positive real number.

The second basic constraint for actions istemporal coherence: every action consumestime equivalent to the sum of its duration andthe synchronization interval.

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Start X/OStart X Start O

(a) (b)

Figure 1. Two spatial versions of tic-tac-toe: (a) with an equidistant mapping, and (b) with a distorted mapping.

Start X

Start O

Figure 2. Looking for a spatial solution tothe synchronization problem.

Definition:A geogame G = (S, A, time, value,syncTime) consists of two mappings, time: A �R� (the set of positive real numbers) and value:S � V, where V denotes the value space forstate evaluation, and a constant syncTime � R�.

The time mapping doesn’t necessarily needto be proportional to the geodetic distances inthe geographic environment, because playerswill rarely be able to move as the crow flies.Furthermore, the possibility of using physicalobjects to obstruct players’movements offersan additional degree of freedom that’s sup-ported by the Geogame definition.

Although the definitions together describe alarge class of games, not all location-basedgames are geogames. Most important, gamesthat don’t satisfy the spatiotemporal coherenceconstraints—in which resources magicallyjump around the board—aren’t geogames.

GeoTicTacToeWe can easily describe a spatial version of

tic-tac-toe, which we call GeoTicTacToe, ina way that fits with the two Geogames defin-itions given earlier. Two players, P = {PX,PO}, play the game on a board with locationsL = {L11, …, L33, StartX, StartO}, where Xand O are the tokens; that is, R = {X1, …, X6,O1, …, O6}. The game’s states are describedby their distribution of resources. For in-stance, start = (locationStart, resourcesStart)with locationStart(PX) = StartX, location-Start(PO) = StartO, and resourcesStart(X1) =… = resourcesStart(X5) = PX, and similarlyfor the resources denoting the O-tokens. In

practice, the framework explicitly describesonly the starting state and constructs the otherstates by applying actions to the starting state.

AnalysisThe synchronization time interval specified

by a geogame’s syncTime constant is crucial tothe game. In principle, we could find suitablevalues for the parameter by playing and eval-uating numerous games with different para-meter settings. Although we improved earlyversions of the CityPoker game that way, thetrial-and-error approach is hardly satisfactoryas a method for game design.

However, we can find adequate values forthe syncTime parameter by systematically explor-ing the game’s state space. To do this, we usea Geogames analysis tool that relies on a sim-ple player behavior model. A player firstdecides which location to move to next (severalpossibilities), then moves toward that location,arriving some time later (no lost players). Then,the player decides which actions to take uponwhich resources, and takes those actions. Theplayer waits syncTime and then moves to thenext location. The Geogames analysis toolmakes several additional assumptions—forinstance, that players move as fast as they canand that they don’t waste time by waitinglonger than the synchronization interval.Finally, the tool assumes that each player willtry to win.

With these assumptions, the Geogamesanalysis tool explores the state space using ageneralization of the minmax algorithm. Thegeneralized algorithm handles multiple play-

ers and determines the next player to moveaccording to the time units players need fortheir actions. This requires several modifica-tions of minmax (see the sidebar “TakingTurns in Games”). Consider, for example, twoor more players arriving at a location in thesame instant of time (concurrent action uponresources), necessitating the incorporation ofrandomized elements. Furthermore, appro-priate pruning strategies become essential forstate spaces larger than that of GeoTicTacToe.

We can evaluate game-end states using anevaluation function that is derived from thegeogame’s value mapping. The result prop-agates from the game tree’s leaf nodes to itsroot as the standard minmax would. Finally,the values at the starting state induce a playerranking and thus represent the game’s out-come. This ranking gives the game designera preliminary idea about the fairness of thegame he or she has created: a completely fairgame ends with all players having the samerank. Note that fair games aren’t necessarilychallenging location-based games.

The architecture of the Geogame analysistool features four functional layers: a searchmechanism, the Geogames engine, a concretegeogame, and a parameterized geogame. Thisarchitecture lets us easily model and analyzeany geogame and to experiment with differ-ent search mechanisms and parameterizations(such as different starting points and spatial-izations). This includes the implementationof advanced search algorithms such as maxnor paranoia4 for multiplayer games or pruningstrategies such as null move pruning5 for

SEPTEMBER/OCTOBER 2006 www.computer.org/intelligent 43

In most classic board games, players alternate moving. Never-theless, a typical board game involves more strategic reasoningthan most location-based games that have been proposed sofar. Not surprisingly, board games have made a digital reappear-ance in the form of computer-augmented tabletop games.1

Some noncomputerized variants of chess, such as ProgressiveChess or Double Move Chess (www.chessvariants.org), try toenrich the game experience by lifting restrictions on turn-takingto some degree.

The geogames described in this article go one step further byreplacing turn-taking restrictions with real-time locomotion ina real-world environment. Traditional AI techniques for turn-based games such as the minmax algorithm can be used in thiscontext but must be adapted to handle players’ concurrentmoves or simultaneous actions. For real-time strategy games,Alexander Kovarsky and Michael Buro developed a randomizedminmax algorithm combined with a sampling-based evaluationstrategy to search the corresponding state space under real-time restrictions.2

Two of us (Peter Kiefer and Sebastian Matyas) presentedanother variant of the minmax algorithm for balancing ageogame at design time.3 This algorithm considers concurrencyin location-based games by taking into account the game’s spa-tiotemporal configuration.

References

1. C. Magerkurth, T. Engelke, and M. Memisoglu, “Augmenting theVirtual Domain with Physical and Social Elements,” Proc. Int’l Conf.Advancements in Computer Entertainment Technology, ACM Press,2004, pp. 163–172.

2. A. Kovarsky and M. Buro, Heuristic Search Applied to AbstractCombat Games, LNCS 3501, Springer, 2005, pp. 66–78.

3. P. Kiefer and S. Matyas, “The Geogames Tool: Balancing Spatio-Temporal Design Parameters in Location-Based Games,” Proc. 7thInt’l Conf. Computer Games (CGAMES 05), Q. Mehdi and N. Gough,eds., Univ. of Wolverhampton, 2005, pp. 216–222.

Taking Turns in Games

more complex games. Only the Geogamesengine layer is fixed, as it reflects our generalframework.

EvaluationWe can evaluate the game’s state space for

different syncTime values as well as for differentvalues of the speed factor—that is, the ratio ofthe average speed of the X-player divided bythe average speed of the O-player. To illustratedifferences between various spatializations, weevaluated the two spatial versions of tic-tac-toe depicted in figure 1. Values for syncTimeranged from 0 to 12 in steps of 0.5, and valuesfor the speed factor ranged from 1.01 to 1.20in steps of 0.01. The result of the evaluation isdescribed by three parameters:

• Player ranking. Because the slower O-player can’t win, only two outcomes arepossible: the X-player wins or the gameends in a draw.

• Game depth (the number of X- and O-tokens placed at game end). Each end statehas a depth value between 3 (one playercould place three tokens) and 9 (all tokenshave been placed), which is propagatedthrough the tree along with the corre-sponding evaluations. Winners prefer theend state with smaller depth. Obviously,depth correlates with ranking: a depthsmaller than 9 always means a win for theX-player, and a depth of 9 could result ineither a win or a draw. Our study didn’thave any wins at depth 9.

• Optimal path through the game tree cor-responding to the game in which both

players act optimally. Usually, more thanone optimal path exists.

Figure 3a shows the results for GeoTic-TacToe played with the geographic footprintconfiguration shown in figure 1a. The resultclearly shows the effect of the length of thesynchronization interval. For small values ofsyncTime, the game’s depth doesn’t exceed 5.The faster X-player wins these games by rac-ing. The O-player can’t prevent the X-playerfrom setting three X-tokens in a straight line.

On the other hand, high values for syncTimelead to the two players alternating moves, asin the board version of tic-tac-toe. The inter-esting range for the syncTime parameter lies, forexample, between 3 and 9 if the players’speeds differ no more than two percent (thespeed factor is less than 1.02), leading togames that end at depth 7. Games with depth6 through 8 are a winning situation for the X-player, as are race games at depths 4 and 5.

We consider a location-based game withgreater depth more interesting, mainly fortwo reasons. First, discovering the winningstrategy is cognitively more difficult, and sec-ond, implementing the winning strategy isharder because of real-world obstacles. Forinstance, the time needed to move in an urbanenvironment between two board positionsmight vary because of traffic lights. Thisunpredictability increases with greater depth,so there’s good reason to call these gameschallenging geogames.

Figure 4 illustrates an optimal path (the gamecourse) for a syncTime of 5, a speed factor of 1.02,and depth 8. At the beginning of this game, it

looks race-style. Player X starts running throughthe upper horizontal line, while player O occu-pies the middle spot 5. But because of the sync-Time interval, player X is forced to wait; mean-while, player O can prevent a fast win by takinglocation 1. Player X in return blocks player Ofrom winning by moving to location 9. This inturn forces player O to move to location 6 sothat player X can’t get three in a column. Finally,player X now can take advantage of his speedand takes locations 8 and 7 before player O canreach either of them. This type of movesequence, blending logical reasoning with phys-ical locomotion, is generally found at depths 6through 8 and creates what we consider a chal-lenging geogame.

Using the Geogames analysis tool, we canalso study the effect of different choices ofgeographic footprints, including the startinglocations. Figure 3b shows a depth-versus-syncTime plot comparable to that of figure 3a butfor the geographic footprint configurationshown in figure 1b. We found different bound-ary values delimiting race-style games, chal-lenging geogames, and classic board games.The footprint configuration generating figure3b promises more interesting games than thatgenerating figure 3a, because all depth valuesfrom 3 through 9 actually occur.

Designing a geogameSo, to design a geogame, choose a syn-

chronization interval within the value rangecorresponding to challenging geogames—forGeoTicTacToe, we find this at a game depthbetween 6 and 8. Within this range, you canemphasize speed or reasoning. You can ana-

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(b)(a)

1.20

1.15

1.10

1.05

Spee

d fa

ctor

0 121110981 2 3 4 5 6syncTime

Game depth Game depth

Race game

7

5

Challenging geogame

7

Board game

9

1.20

1.15

1.10

1.05

Spee

d fa

ctor

0 121110981 2 3 4 5 6syncTime

Race game

7

4

5 6 8 97

Board game

Challenging geogame

Figure 3. GeoTicTacToe results (a) for the game board shown in figure 1a, and (b) for the game board shown in figure 1b.

lyze any other geographic footprint or otherassumptions (for instance, about speed ratios),the same way. In general, then, you can

1. select a classic board game with inter-esting strategic elements,

2. choose alternative sets of geographicfootprints in vista or environmentalspace for the board positions,

3. model the resulting location-based gamewithin the conceptual framework, and

4. use the analysis tool to derive interest-ing values for the syncTime parameter.

Our main goal in describing our concep-tual framework and analysis tool was toshow how to determine a synchronizationinterval numerically so that you can imple-ment challenging geogames in geographicspace. Knowing the game area’s real dimen-sions, you can easily translate the syncTimeparameter from abstract time units to sec-onds. For instance, when choosing the spa-tialization illustrated in figure 1a for a city-size game board of 2 � 3 km and pedestrianswith a speed of 3 meters per second, onetime unit would correspond to approxi-mately 83 seconds. In other words, a syncTimeof 5 time units corresponds to approximately7 minutes of waiting.

We are currently exploring how to bestfill the syncTime interval by present-

ing interactive content (mini games, quizzes,or puzzles). These elements can add extravalue to a geogame in tourist or educationalscenarios. Edutainment, most recently that oflearning with mobile games, is a growingresearch topic.6,7 Geogames with their intrin-sic syncTime interval constitute an ideal mediumfor transporting edutainment content.

syncTime analysis, as we’ve implemented itthus far, uses some simplifying assumptions.For instance, we assumed that players don’twait longer than the synchronization inter-val. In test-playing our games such as Geo-TicTacToe, we never encountered playerbehavior that contradicted that assumption.However, it’s well known from games withmore complex state spaces that sometimesthe best move is not to move but to let theopponent move twice. Obviously, this couldlead to deadlocks in which the players waitfor each other to move. Therefore, complexgames such as chess possess zugzwang rules,which enforce making a move.

Because of the simplifying assumptions,the Geogames synchronization logic isalmost trivial: move to the next position, waitsyncTime, move to the next position, and so on.With this logic, players can’t wait indefi-nitely. It could be interesting to permit play-ers of geogames with a complex state spaceto wait longer than the synchronization inter-val. We’ll then need some sort of zugzwangrules to avoid deadlocks. A natural frameworkfor describing more complex synchronizationmechanisms is temporal logic. But from anempirical point of view, we must first explorethe practical usefulness of different synchro-nization mechanisms. Which mechanisms canhuman players manage cognitively? Whichare adequate for edutainment applications?Once we’ve done that work, we can thendescribe candidate synchronization mecha-nisms, including zugzwang rules, in a suffi-ciently expressive temporal logic (such aspropositional linear temporal logic or first-order linear temporal logic) that we could, forinstance, prove safety and progress properties.

Another area for future research is com-paring different geogame spatializations.This includes studying the scalability of theGeogames design approach by creating andcomparing spatializations at different scalesin vista and environmental space—for exam-ple, scaling a game from a sports field to awhole country. Furthermore, we plan to spa-tialize board games with more complex statespaces as well as multiplayer games.

Another line of research that originally ledus to designing geogames is the recognitionof user intentions from motion behavior. Theproblem of intention recognition consists ofassigning meaning and goals to a person byanalyzing his or her motion in a spatial envi-ronment. The location-based game City-Poker, for example, was originally devised asa scenario to study intention recognition.3

Being able to interpret and predict a user’sintentions will help game designers presentinformation automatically on mobile devicesin situations with limited interaction possi-bilities—for instance, playing GeoTicTacToe

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X/O

4

X/O

3

X/O

6

X/O X/O

897

31

654

2

1

X/O

7

X/O

5

X/O

2

X/O

8

Figure 4. Game flow of a challenging geogame.

on bikes and with smart phones, as in our cur-rent implementation (see the “The GameInterface” sidebar).

Although social interaction plays animportant role in geogames, single-playerversions are also desirable. The design of avirtual smart opponent with appropriate AImethods running on the limited capabilitiesof a mobile device is yet another object offuture research.

AcknowledgmentsThis is an extended version of our article,

“Geogames:A Conceptual Framework and Tool forthe Design of Location-Based Games from ClassicBoard Games,” Proc. 1st Int’l Conf. Intelligent Tech-nologies for Interactive Entertainment (INTETAIN

05), M. Maybury, O. Stock, and W. Wahlster, eds.,LNAI 3814, Springer, 2005, pp. 164–173.

References1. D. Montello, “Scale and Multiple Psycholo-

gies of Space,” Proc. Conf. Spatial Informa-tion Theory (COSIT 93), LNCS 716, Springer,1993, pp. 312–321.

2. D. Nicklas, C. Pfisterer, and B. Mitschang,“Towards Location-Based Games,” Proc. Int’lConf. Applications and Development of Com-puter Games in the 21st Century (ADCOG 21),L.W. Sing et al., eds., 2001.

3. C. Schlieder, “Representing the Meaning ofSpatial Behavior by Spatially GroundedIntentional Systems,” GeoSpatial Semantics,LNCS 3799, A. Rodríguez et al., eds.,Springer, 2005, pp. 30–44.

4. N. Sturtevant, “Current Challenges in Multi-Player Game Search,” Computers and Games: 4th Int’l Conf., CG 2004, LNCS3846, Springer, 2006, pp. 285–300.

5. O.D. Tabibi and N.S. Netanyahu, “Verified Null-Move Pruning,” ICGA (Int’l Computer GamesAssoc.) J., vol. 25, no. 3, 2002, pp. 153–161.

6. K. Facer et al., “Savannah: Mobile Gamingand Learning?” J. Computer Assisted Learn-ing, vol. 20, no. 6, 2004, pp. 399–409.

7. G. Schwabe and C. Göth, “Mobile Learningwith a Mobile Game: Design and Motiva-tional Effects,” J. Computer Assisted Learn-ing, vol. 21, no. 3, 2005, pp. 204–216.

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46 www.computer.org/intelligent IEEE INTELLIGENT SYSTEMS

Geogames are intended to bring game playing back to the physical world.Although game areas for geogames can scale from vista to environmental space,our current implementation of GeoTicTacToe is designed for a citywide gameboard with bicycles as the means of transportation (see figure A1). Players arelocalized using a GPS receiver (not necessarily installed on the handlebar) that com-municates with the smart phone via Bluetooth. A map of the game area appears onthe phone’s screen. Figure A2 shows the map, enlarged. Each player can see his or hercurrent location marked with a small pink cross (1) on the map. As soon as one of theplayers reaches an unoccupied location (one of the yellow squares), a small X or Oappears, indicating that the location is reserved. After the syncTime interval has passed,the mark enlarges, and the player is free to move on. If a player leaves a reserved loca-tion, he or she loses that location and the small mark disappears.

Because of the high speed of locomotion, possibilities for interaction with themobile device are severely limited. A main design objective for the GeoTicTacToeassistant system consists in minimizing the need for user interaction. Our currentresearch focuses on the context-aware presentation of game information (forexample, automatic zooming).

Figure A. Playing GeoTicTacToe: (1) A player’s bicycle handlebar. (2) The game areamap. (figure courtesy of the State Office for Survey and Geographic Information,Bavaria, Germany, 2005)

The Game Interface T h e A u t h o r sChristoph Schliederis a professor of com-puting in the culturalsciences at the Univer-sity of Bamberg. Hisresearch focuses ondeveloping and apply-ing methods from semantic information

processing to problems from the cultural sci-ences, including qualitative spatial reasoning,preferred mental models, and geospatial seman-tics. He received his PhD in computer sciencefrom the University of Hamburg. Contact him atOtto-Friedrich-Universität Bamberg, Feldkir-chenstr. 21, D-96045 Bamberg, Germany;christoph.schlieder@wiai.uni-bamberg.de.

Peter Kiefer is aresearch assistant andPhD candidate in ap-plied computer sciencesat the University ofBamberg. His researchinterests are in knowl-edge representation,especially intention re-

cognition from motion patterns. He received agraduate degree in information systems from theUniversity of Bamberg. Contact him at Otto-Friedrich-Universität Bamberg, Feldkirchenstr.21, D-96045 Bamberg, Germany; peter.kiefer@wiai.uni-bamberg.de.

Sebastian Matyas isa research assistantand PhD candidate inapplied computer sci-ences at the Universityof Bamberg. His re-search focuses on se-mantic data integrationin geographic informa-

tion processing. He received a graduate degreein information systems from the University ofBamberg. Contact him at Otto-Friedrich-Universität Bamberg, Feldkirchenstr. 21, D-96045 Bamberg, Germany; sebastian.matyas@wiai.uni-bamberg.de.

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