DECISION TRAINING USING AGENT-BASED BUSINESS STRATEGY GAMES

2,453 views

Published on

0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,453
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
38
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

DECISION TRAINING USING AGENT-BASED BUSINESS STRATEGY GAMES

  1. 1. DECISION TRAINING USING AGENT-BASED BUSINESS STRATEGY GAMES Mike Dobson, Vadim Kyrylov, & Tetyana Kyrylova. School of Interactive Arts & Technology, Simon Fraser University, Canada [mdobson, vkyrylov, tkyrylov]@sfu.ca ABSTRACT. or several different competitive industries. The simulation is run according to a predefined scenario that Emerging technologies, such as intelligent agents, specifies the initial state of the game and the important avatars, and distributed environments offer new events taking place during the simulation run such as opportunities for the improvement of business games used changes in market conditions. for training decision makers. The advent of these technologies also creates new challenges to game Player activities are supervised by the instructor who developers and training consultants. We investigate these coordinates their work. The play is a series of rounds opportunities and offer suggestions on how to better spanning over the time period of up to several years, with address technical and pedagogical challenges. Keywords: steps normally equal to that of the operations management learning-games, agent-based gaming, simulations, planning horizon in the real context, say one quarter of a business. calendar year. A training session normally requires several days and 6-8 hours per day. Training exercises for students majoring in business administration typically 1. INTRODUCTION takes several weeks with 1-2 short sessions run weekly. The critical role of training managers in decision In each round trainees are expected to make a number making for competitive industries is widely recognized in of functional decisions, typically concerning; company the business and academic community. Business strategy finances, human resources, marketing, production and games have been used for this purpose since the early expansion. In doing so, they acquire from the gaming 1960s and have evolved into sophisticated systems [1]. environment necessary input data, analyze them using Several new gaming technologies now offer greater some decision support tools (built-in or standalone, like opportunities for improved training. Still these spreadsheet programs), evaluate possible options, make opportunities have not been properly identified yet, and the decision, and enter its parameter values into the the potential impact thereof on the pedagogy of game- gaming software. After all the players have entered their based training needs to be investigated The purpose of decisions, the gaming program calculates the new state of this paper is to identify the emerging opportunities in the market and provides an update for the trainees. This gaming technology and evaluate their influence on the procedure is repeated until the end of the simulation time. pedagogy of decision maker training. First we outline Numerous studies have proven that business strategy some of the existing challenges of game-based training games are very efficient learning and training tools. and the limitations of the traditional business strategy However, scattered in the literature, are certain concerns games. Then we discuss how emerging gaming about the existing gaming technology: technologies could respond to these challenges. In doing so, we also elaborate on the pedagogical implications of 1. Lack of timely feedback on the learner’s actions. The the new technologies. Finally, we show an example of an environments do not provide explicit feedback on advanced business strategy game, which implements player’s strategic steps. Rather, their quality becomes many of the new desired properties. apparent only after significant delay. Error can be recognized only with significant delay, often after 2. LIMITATIONS IN CURRENT GAMES corrections have already been made. At the time of writing there were at least a dozen 2. Poor emotional engagement with the gaming commercially available business games. Overviews of activities. Without the proper emotional engagement, many of them can be found in virtually each issue of training sessions become dull and uninteresting. Simulations & Gaming (the flagship journal on this topic). 3. Lengthy durations for learning. Most games lack the Here we provide a summary of our findings based on transparency needed for getting students/trainees these reviews since 1999 [2-7]. A typical business familiar with the game at an efficient pace. strategy game provides a collaborative computer-based environment in which the dynamics of a competitive 4. Unintelligible game output. Information visualization industry is simulated. Players are trainees (individual or features in business games are typically small groups) normally taking the role of market entities. underdeveloped and are often limited to data They can be enterprises or branches, can represent presentation in the spreadsheet format. different places in the supply chain and may belong to one 5. Lack of technology for supporting debriefing. Games 428-120 66
  2. 2. tend to concentrate on the play process, forgetting Optimal agent behavior. Existing business strategy that the after-play activities could be more important games provide little support for assessing learner’s to learning. De-briefing is rarely supported. decision making. If well designed, agents can 6. Training business managers is prohibitively demonstrate optimal behavior by making rational expensive. Training sessions normally require decisions for the player. This offers a range of new leaving the workplace for an extended period of time opportunities for competency development in the trainees. and disrupting the normal work schedule. For this They can receive timely feedback from background reason, sessions have very limited duration (only 2-3 agents monitoring play. This provides a way to compare days). In many cases this is hardly sufficient for learner decisions with the optimal solutions found by the accomplishing training goals. intelligent agent and computing errors without significant delay. As a result, trainees will be able to learn faster In the next section we outline some emerging about how rational decisions should be made. technologies and show how they could help overcome these limitations. Enhanced transparency and increased access. The ability of rule-based systems to provide explanations of 3. EMERGING TECHNOLOGIES the logics leading to decisions made by the agent for the Intelligent agents are gradually finding their way human player, allows the trainee to learn from these into advanced e-Learning environments [8-10]. As we explanations in the process of the game. The environment show below, this technology could make a tangible capable of providing the trainee with such explanations contribution to bettering business strategy gaming. may significantly relax the need for trainee preparation. Intelligent software agents are simulated entities In traditional games, trainees must be well-prepared for enabled with means for perceiving the information about making decisions on their own. In agent-based games, the artificial world in which they live and exhibit active however, trainees may spend more time observing agent behavior by pursuing their own goals (the desired set of play, learning from those actions and explanations. the states of the world). Agents can possess some Significantly relaxed timing constraints. If resources and execute a pre-specified set of actions which necessary, an agent-based game can be run at a much change the state of the world, including the agent’s state faster pace. Running a scenario in a completely automated itself. ‘Rational’ agents can measure the mismatch mode, when the all human player are substituted by between the current and aspired states of the world, agents, takes no more than a few minutes, while in predict possible changes in the state of the world resulting traditional games this is normally takes days or even from actions executed by themselves and other agents, weeks to run just one scenario. This quantitative change and plan their actions in the optimal way under uncertain results in a qualitative difference: the emerging conditions. Optimization can be based on a technology offers an opportunity to run multiple scenarios comprehensive set of logical rules and/or sophisticated in just one class session. This offers new opportunities for procedures using several optimality criteria, or both. In gaming technology such as investigation of the impact of rule-based systems computations can normally be traced various parameters on the businesses and the industry as a back from raw data to final conclusions showing the whole. This also offers new opportunities for competency agent’s line of reasoning. Agents having this ability are development in trainees making better understanding of often referred to as ‘intelligent’ because this rational the various roles involved in a simulation more likely and behavior is typical for intelligent live creatures. better mutually reasonable decision making skills. Agent technology is a promising way to further Increased flexibility. The new technology offers a improve business strategy games. In the gaming wide range of combinations with automated modes of environment an intelligent agent can stand for a market operation of some agents and human role players standing entity, sometimes completely replacing a human player or for other active entities of the gaming environment. The working in the background as an individual assistant to two extremes are, complete automation of the simulation the learner. Monitoring trainee and evaluating his/her and everything performed by human users with only actions online is one more possible role of an intelligent supportive functions like recordkeeping left up to the agent. Consumers, whose behavior in the traditional software. Options lying in between offer new flexibility business game is either pre-specified by the scenario or dimension lacking in traditional business strategy games. sometimes implemented by just an over-simplified Animated pedagogical agents , or avatars, are closely algorithm, can be also modeled by using the intelligent related to agent-based technology and offer agent technology. This offers an opportunity for complementary opportunities in business game-based modeling more sophisticated consumer behavior, which training pedagogy. They are lifelike animated characters could be critical for training managers in some industries, whose purpose is to facilitate the learning process [12- like broadcasting services [11]. Here we analyze some 14]. Several studies have shown that avatars, if properly potential opportunities that will be offered by the designed and used, can significantly improve learning emerging agent technology after it eventually matures [15]. Human-driven avatars are nowadays common in enough. online forums and some role-playing entertaining games. Still little, if nothing, has been specifically proposed on 67
  3. 3. using this emerging technology in business strategy This would remove the stress from the trainees who in gaming. Below we identify some opportunities. In traditional gaming environment normally are compelled particular, it is reasonable to expect that avatars could to work for only 2 or 3 days. Other obvious benefits make business strategy games more emotionally include preserving anonymity of the players and complete engaging, thus adequately addressing some of the removal of the geographical barriers. concerns identified in the foregoing section. Avatars can However, Internet-mediated business games have also significantly add to user friendliness. We believe that important organizational, pedagogical, and technological an advanced business gaming environment would benefit concerns in common: objectives, role-play, synchronicity, especially from the following types of avatar. game facilitation, and participant interaction. Web- 1. Wizard. A friendly, positively-minded pedagogical enabled gaming is more demanding of the human agent whose role is to provide the learner with the facilitator, briefing/debriefing techniques, and creates new explanations and suggestions on how to use the gaming problems, such as finding new sources of motivation and environment in order to better accomplish his/her tasks. accounting of cross-cultural differences of the trainees, if 2. Instructor. An agent whose role is complementary to they are originating from different parts of the world [16]. the Wizard in helping the trainee. Could differ from the These issues require special attention; we speculate that Wizard in that it is less friendly, more demanding, and some of them can be resolved by combining Web-based somewhat authoritarian. gaming with the intelligent agent and avatar technologies. Still the pedagogy of training in the distributed 3. Market Game Players. A set of pedagogical agents environment needs further investigation. standing for the executives of the simulated businesses. Both the particular business run by the trainee and the competing businesses can be personalized by these 4. NEW TECHNOLOGIES FOR GAMES avatars. Different avatars can be representing simulated Some of the limitations of the existing business business entity executive roles, such as CEO, VP strategy games need further deliberation. Marketing, VP Finance, etc. To amplify the emotional impact on the trainees, their personalities should reflect Trimming the Learning Curve The major reasons for both the nature of their jobs and their company goals over-long learning times, are, the lack of transparency of (e.g. aggressive vs. defensive). the game design, and, the assumptions underlying algorithms. These shortcoming have been recently 4. Spy. An agent playing in the background for the trainee recognized and purposefully addressed by some gaming and monitoring and critically assessing his/her actions. researchers [17, 18]. However, we believe that not all This is closely related to the functions discussed in the possibilities for making games fully transparent for the foregoing subsection. trainees have been investigated and even identified. As a 5. Teammates. Human-driven avatars personalizing fellow general recommendation, we would suggest that the trainees working together with the business game user. gaming technology should allow for incorporating meta- Could be especially helpful in Web-based gaming knowledge about the game in several forms. Examples environment (see below). could be ontologies, conceptual diagrams, algorithm Some of the avatars such as the Spy and the Market hierarchical structure diagrams, and graphical Game Players can only be efficiently implemented within representations of the key simulation sub-models (some the intelligent agent technology. Their behavior is driven of these are illustrated below). by the states of the game, whose total number can be Visualization for comprehension. Some researchers overwhelming. Therefore it cannot be reduced just to a have recently recognized that properly designed pre-defined set of presentations like it is in principle visualization of the game data is critical for the efficiency possible to do for other avatars. of training [19]. At this point spreadsheets are the major Web-based Gaming Technologies. Internet-mediated form for providing output data to trainees. A typical business games represent one more new important trend. example is a rather pedagogically advanced business Several business strategy games based on this technology game recently presented in [7], where most outputs are are commercially available [e.g., 4, 6]. Distance training just tables containing numerical data. online offers opportunities for radically reducing the One possible improvement is careful selection of prohibitive costs and relaxing some other constraints of adequate data presentation techniques. So far we can see the traditional game-based training. Eliminating the need the gap between the ways historical data is presented in to commute to and from the training site could be large corporations and in business gaming environments, mentioned as the minimal gain of Web-based training. As from which trainees are expected to learn how to handle a result, there is also no need in day-long training data in their workplace. Corporate data are normally sessions, whose duration could be made reasonably short, stored in data warehouses equipped with report generators say about two hours. Trainees can participate in them and advanced visualization tools, whereas traditional without any rush, from their workplaces or even from games do not provide these options to their users. home, synchronously or asynchronously. The duration of Design for the Debriefing Support. So far business the game play can be made longer, say at least 2 weeks. 68
  4. 4. game developers appear to be preoccupied with the enabled business games. Some reusable technical gaming process itself and neglect debriefing features, that solutions for debriefing can be found in [10]. Agent-based any educational/training games must have. We believe technologies, such as monitoring/evaluating agents, could that planning for debriefing must be made in the early render some effective solutions. Still we believe that this stages of the game design. As it was indicated above, issue needs further investigation, both in the technological debriefing features are especially demanding for Web- and pedagogical aspects. Fig.1. This sub-model shows the consumer base response to the promotional effort by the particular player compared to that of the rivals. The user interface allows the domain expert to adjust the curves, which represent particular sub-models of the simulator, without referring to the detailed model. 5. AN AGENT-BASED STRATEGY GAME automatically or shadow the trainees. This has become possible as a result of developing a set of algorithms We have used the intelligent agent technology and modeling rational behavior of the telecoms. They implemented some solutions discussed above in our implement several innovative concepts, such as firm’s strategy business game for the telecommunications performance indicators and multi-level multi-criteria industry [20]. Our simulation is simplified to a limited set decision making [21]. Focus on the design for model of providers offering telecommunications services such as transparency and data visualization has been set from the high-speed Internet access and cable and ADSL TV to very beginning of the game development. The algorithm residential customers in the metropolitan area. The structure was deliberately designed as a set of telecommunication firms are competing for the hierarchically organized and loosely coupled components. preferences of customers by setting prices, expanding A unified user interface was developed for displaying their network facilities, spending on quality of service, meta-knowledge about low-level algorithms, referred to promotion, and market research. The competing firms are as sub-models. Fig.1 illustrates a sub-model used for also interested in making profits and can attract financing calculating consumer inflow z as function of two by banks. Consumers react to the offerings by deciding variables, spending on promotion by the given player x whose services to subscribe for. They can enter the and promotional spending by the competition y (all market, change provider and or set of services or leave the variables are normalized). The piecewise-linear curves in marketplace. this diagram present the algorithm for calculating z. We consider the telecoms service providers the sole Technically, nothing else shown in Fig.1 except the type of active agent, which can act completely coordinates of the points on these curves is necessary for 69
  5. 5. these computations. All the rest is the meta-knowledge Besides making the game transparent, this technology about this sub-model, which allows the trainee to figure significantly eases model calibration and adjustments of out how this particular feature is implemented. Part of the its parameters. sub-model hierarchy is shown in Fig.2. In the future we In this example, the trainee can view the decision on hope to further enhance the game transparency by allocating the budget suggested by the agent. Users can implementing this diagram so that users can browse it and change the decision parameters by moving the sliders and view the sub-models. There are total 24 sub-models in evaluate the consequences by comparing difference of the this simulator, all of them complete with necessary meta- performance indicators (upper right bar diagram). The pie knowledge. diagram reflects the changes in the budget allocation made by user. While user is changes the Loans parameter the size of the whole pie changes accordingly. In the shown game mode, users have a choice to continue running the model stepwise, or to run several steps automatically, leaving it up to the agent making decisions for the firm automatically. Fig.3 illustrates how decisions proposed by a player agent are presented to the trainee. Graphics convey the most important information about the decision parameters and therefore play a central role Fig.2. Main component of the world model in the user interface. Fig.3. A fragment of the Player Monitor user interface. Two instances of the application are running, each following different players. The split double bars on the diagram (top right) show the anticipated results if the user changes the actions recommended by the automated player agent. CONCLUSION making is the critical factor of success. So far we managed to create such models for some We have investigated emerging technologies, which telecommunications service markets, but more research is may have significant impact on the business-game based needed to extend our results into other areas of interest. training. Of them, most promising is intelligent-agent technology. Still this technology should mature enough We believe that deliberate planning for ensuring for being suitable for business strategy games. model transparency, data and knowledge visualization, Development of adequate models of rational decision 70
  6. 6. and debriefing support are keys for the significant [11] P. Twomey and R. Cadman, "Agent-Based Modeling improvement of business gaming applications. of Customer Behaviour in the Telecoms and Media We also have identified several game-based training Markets," The Journal of Policy, Regulation and pedagogy issues that need to be resolved for ensuring Strategy for Telecommunications Information and efficiency of training. Media, vol. 4, pp. 56-63, 2002. [12] W. L. R. Johnson, J.W.; Lester, J.C., "Animated Pedagogical Agents: Face-to-Face Interaction in ACKNOWLEDGMENTS. This work has been Interactive Learning Environments.," In: The partly supported by a SSHRC collaborative research International Journal of Artificial Intelligence in award to study Simulations and Gaming Environments Education,, vol. 11, pp. 47-78., 2000. (SAGE) led by David Kaufman and Louise Sauve. [13] R. Moreno, "Life-like pedagogical agents in constructivist multi-media environments," EDMEDIA, pp. 741-746, 2000. REFERENCES [14] M. Morozov, A. Tanakov, and D. Bystrov, [1] A. J. Faria, "The changing nature of business "Pedagogical Agents in the Educational Multimedia simulation/gaming research: A brief history," for Children. Building the Knowledge Economy: Simulation and Gaming, vol. 32, pp. 97-110, 2001. Issues, Applications. Case Studies. Part 2.." [2] B. Aslani, "Business Strategy and Computer Amsterdam: IOS press,, 2003, pp. 1611-1616. Simulation Modelling," The CAL Poly Pomona [15] J. Marino, "What can you learn from a Wizard?: Journal of Interdisciplinary Studies, pp. 195-202, How pedagogical agents improve instruction," in 1999. Encyclopedia of Educational Technology, 2004. [3] J. Smith and P. Golden, Airline: A Strategic [16] T. Asakawa and N. Gilbert, "Synthesizing Management Simulation (4th Ed): Prentice Hall;, experiences: Lessons to be learned from Internet- 2001. mediated simulation games," Simulation & Gaming, [4] G. Audia, "Celcom21 - the most widely distributed vol. 34, pp. 10-22, 2003. business simulator in the world," 2003. [17] J. Machuca, "Transparent-box business simulators: [5] D. Burrus, "The Advantage Business Strategy An aid to manage the complexity of organizations.," Game," 2003. simulation & Gaming, vol. 31, pp. 230-239, 2000. [6] D. Honey, "The Business Simulator," 2003. [18] A. Größler, F. Maier, and P. Milling, "Enhancing [7] T. Lainema and P. Makkonen, "Applying learning capabilities by providing transparency in Constructivist Approach to Educational Business business simulators," Simulation & Gaming, vol. 31, Games: Case REALGAME," Simulation & Gaming,, pp. 257-278, 2000. vol. 34, pp. 131-149, 2003. [19] V. Perotti and T. Pray, "Integrating visualization into [8] G. Boy, "Software Agents for Cooperative Learning," the modeling of business simulations," Simulation & in Software Agents, J. M. Bradshaw, Ed. Cambridge, Gaming, vol. 31, pp. 230-239, 2002. MA: MIT Press, 1997, pp. 223-246. [20] V. Kyrylov, A. Kanwal, and T. Kyrylova, "Agent- [9] A. Nijholt, "Agents, Believability and Embodiment Based Simulation of Telecommunications Services in Advanced Learning Environments," presented at Market in a Metropolitan Area," presented at IEEE International Conference on Advanced Business & Industry Symposium (BizSim'04), Hyatt Learning Technologies (ICALT 2001), 2001. Regency Crystal City Arlington, Virginia, USA, [10] M. Dobson, M. Pengelly, J.-A. Sime, S. Albaladejo, 2004. E. Garcia, Gonzales, and J. Maseda, "Situated [21] V. Kyrylov and C. Bonnani, "Modeling Decision Learning with co-operative agent simulations in Making by Telecommunications Services Providers Team Training," in Computers in Human Behavior, in a Strategy Market Game," presented at Accepted M. Dobson, Ed. Amsterdam: Pergamon: Elsevier for publication at the Applied Telecommunication Science, 2001, pp. 457-573. Symposium (ATS'04), Hyatt Regency Crystal City Arlington, Virginia, USA, 2004. 71

×