![\"Cev1WinningBoard\"](\"https:\/\/www.sirknightj.com\/blog\/wp-content\/uploads\/2022\/06\/Cev1WinningBoard.gif\")
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Brainstorming<\/h3>\r\n
Over the past few months, a couple of friends and I got together to create a game. We weren’t sure what kind game we were going to create yet, so we started off with some brainstorming.<\/p>\r\n
We thought of games we really liked and attempted to mash and merge ideas together to create some brand-new game. We really liked Civilization V and Plague Inc. and wanted to do some sort of resource management game, and write a great story to go along with it.<\/p>\r\n
With all games, the player needs to have some sort of action. In most resource management games, there are two types of actions:<\/p>\r\n
2. An action that gets the player closer to the goal<\/p>\r\n In Machine Learning simulator, the player \u201cbuilds up\u201d a computer which they will use to participate in machine learning competitions. By participating in these competitions, the player will earn more money, which they will use to improve their computer, machine learning algorithm, training data, etc. in order to win in higher and higher competitions (which grant more money). There would be plenty of things the player can do in order to improve their performance, such as hiring developers (various tiers of developers?) or purchasing better computer parts. We can incorporate both idle and gacha aspects to this game, by maybe having some sort of \u201cresearch events\u201d happening on the side, which unlock upgrades or something to further the computer\u2019s progression, but time locked, and also include a computer parts gacha. We can have infinitely-many \u201cmachines\u201d, as such, the player can\u2019t really \u201cmax out\u201d and run out of gacha targets to summon for.<\/span><\/p>\r\n The mechanics of the game are fairly simple (the player doesn\u2019t need to know very much of anything about coding or anything like that), but optimization and figuring out the most efficient way to progress with the least amount of time\/resources spent would be interesting to the expert players.<\/span><\/p>\r\n It’s a pun! “Severity 1” incidents and “Coherent Extrapolated Volition”<\/span><\/p>\r\n You are a newly created artificial general intelligence that has been instructed to maximize human safety. Unfortunately (for humans), your utility function is <\/span>misaligned<\/span><\/a>, and you plan to achieve this goal by benevolently taking over the world and enacting totalitarian policies to ensure maximal long-term human safety.<\/span><\/p>\r\n The AI (player) should use nonviolent methods even if, for example, humans use nuclear weapons against it. The player\u2019s score is the number of surviving humans, which disincentivizes deploying weapons of mass destruction. The ultimate goal is to control the world, but intermediate goals could be decommissioning weapons to discourage war, curing diseases, or outlawing cars.<\/span><\/p>\r\n The main UI is a world map visualization, like in Plague Inc, where the goal is to conquer every country. The key metrics are: dead humans (trying to minimize), trust in AI, and public satisfaction. In the beginning, the player has low resources and low trust. For each country, the player can spend \u201cpublic satisfaction\u201d points to enact safety policies. More totalitarian policies decrease public satisfaction more, like banning cars vs banning unsafe drinking water. Enacted policies decrease the number of dead humans and increase trust in AI over time. If trust in AI is high enough, the player gets more freedom in buying policies that aren\u2019t as clearly related to safety, like peacekeeping robots.<\/span><\/p>\r\n As the game progresses (maybe based on total trust in AI?), the player gets access to more potential policies in their tech tree. In the end game, the player can deploy the robots to less trusting or less satisfied countries to force them to adopt very totalitarian policies regardless of trust in AI values. The final step will be to enclose all humans in cryogenic chambers to maximize safety.<\/span><\/p>\r\n The difficulty can be adjusted easily by changing some variables about how difficult resource acquisition is or how much tech tree items cost. We can also include \u201cadvisor popups\u201d to suggest good actions to the novice player. Expert players are challenged because there are many possible options and it is difficult to optimize for the best final score.<\/span><\/p>\r\n Make each country have different policy costs and trust in AI values depending on their culture. Include \u201cnews alerts\u201d like Plague Inc.<\/span><\/p>\r\n<\/div><\/div>\r\n After the initial brainstorming session, we needed to actually make the game. We decided as a group to go with the CEV 1 idea over the Machine Learning Simulator, as it seemed more interesting and had more varied gameplay\/interesting to play.<\/p>\r\n The gameplay is like a Plague Inc. and Civilization hybrid. The goal is for the player to take over every country in the world while balancing resources and researching policies in a tech tree. There are three resources the player has to manage:<\/p>\r\n The player must always keep $ and sat positive. The lose condition is when either is negative.<\/p>\r\n We split up the world into “regions” (corresponding to subcontinents). Each region produces a different amount of $, sat, and troops per turn and requires some combination of resources to “take it over.” For example, taking over Europe may require 100K sat, 500T $, and 50K troops. To add complexity, regions are interdependent; taking over Europe without first taking Asia would cost more. After acquiring a region, it acts as a resource source (troops++ and $++) and a resource sink (sat–).<\/p>\r\n Researching tech tree upgrades can increase resources, or decrease or “move” the amount of resources required to take over a country. For example, the “Global Web Influence” policy manipulates content on the web to push more trust in AI, and could have the following costs and benefits:<\/p>\r\n Costs:<\/p>\r\n Benefits:<\/p>\r\n Example branches of our tech tree:<\/b><\/p>\r\n\r\n Policies tree:<\/strong><\/p>\r\n\r\n\r\n\r\n Science tree:<\/strong><\/p>\r\n\r\n\r\n\r\n (Not shown: military tree)<\/p>\r\n<\/div>\r\n<\/div>\r\n\r\n Random interactive events affect the player’s resources. The likelihood is determined by the satisfaction level and\/or upgrades unlocked in the tree. These events have 2-3 choices for the player to choose from and there will be tradeoffs between morality and resources. Some examples:<\/p>\r\n We created a spreadsheet on Google Sheets with the costs\/benefits of each region and kept track of the player’s resources as they played the game. Initially, our game balancing was terrible (on our first playtest, a loss was guaranteed by turn 5), but we tried to change the relative costs to keep it interesting. Game balancing was a very significant challenge for us.<\/p>\r\n Our players did not find the game very fun, partly because our game was unbalanced, but also because they felt like they were waiting for the days to pass by and resources to accumulate, without much opportunity for action. We were worried that players would find the tech tree or number of regions overwhelming, but they did not raise this concern.<\/p>\r\n With our first design going poorly, we decided to scrap our game idea and start over from scratch. Since a “world” might be too chaotic and overwhelming for the player, we decided to go with a single city.<\/p>\r\n We also took inspiration from the MegaMan Battle Network 3 Navi Customizer.<\/p>\r\n Essentially how the Navi Customizer worked is that over the course of the game, you unlocked new “pieces” which you can try to fit into your grid. There are certain limitations on where pieces can go, but it let you choose which upgrades you wanted to apply to MegaMan.<\/p>\r\n In our case, buildings would be those “upgrade pieces”, which the player would place down on a grid. We can have upgrades which allow buildings to perform better when placed next to other buildings. Basically creating a “soft restriction” on where the player can place buildings, unlike in MegaMan, which would refuse to let you place certain upgrades next to each other.<\/p>\r\n The player is an AI in charge of a new Mars colony. The AI’s (and thus the player’s) objective function is to “ensure colonists survive”, and they will do\u00a0anything<\/i>\u00a0to keep people from dying. The player loses if a certain number\u00a0N<\/i>\u00a0of colonists die (hard mode=1, medium=100, easy=\u221e). The player wins when they create a post-scarcity economy where no humans can die and resource production is greater than resource consumption.<\/p>\r\n The theme is misaligned AI and space colonization. The upgrade tree contains policies and buildings to improve the survivability of the colonists. As the player continues researching through the tree, the policies become more ominous, allowing the AI to genetically modify colonists, impose child limits, and ultimately cryonically freeze colonists or upload them into the Matrix. The player wins when one of the final win-condition upgrades is researched, ushering in a new post-scarcity dystopia.<\/p>\r\n There are eight resources:<\/p>\r\n Each colonist consumes 2 food\/turn, 1 water\/turn, 1 oxygen\/turn. If resource consumption is more than resource production, non-critical buildings (like schools and mines) “fail” (get deactivated) and if resource consumption is still too high, colonists die until consumption < production. The population increases exponentially as turns pass, pressuring the player to constantly increase resource production.<\/p>\r\n There are several types of buildings that consume and produce resources. The player can rotate and place these strangely-shaped buildings on a 15×15 grid. A challenge is choosing and configuring the buildings to fit the available space.<\/p>\r\n<\/a>1. An investment that increases resources generated<\/p>\r\nInitial Ideas<\/h3>\r\n
Synopsis<\/b><\/h4>\r\n
Similar aspects to games like<\/b><\/h4>\r\n
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Playable by novice and experts because<\/b><\/h4>\r\n
Cool ways to increase complexity<\/b><\/h4>\r\n
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Naming<\/h4>\r\n
Synopsis<\/b><\/h4>\r\n
Game mechanics<\/b><\/h4>\r\n
Similar aspects to games like<\/b><\/h4>\r\n
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Playable by novice and experts because<\/b><\/h4>\r\n
Cool ways to increase complexity<\/b><\/h4>\r\n
Design Phase – Round 1<\/h3>\r\n
Gameplay<\/span><\/h4>\r\n
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Tech tree<\/span><\/h4>\r\n
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Random events<\/span><\/h4>\r\n
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Testing<\/span><\/h4>\r\n
Feedback<\/span><\/h4>\r\n
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Design Phase – Round 2<\/h3>\r\n
<\/p>\r\nPremise<\/b><\/h3>\r\n
Narrative<\/span><\/h3>\r\n
Game mechanics<\/span><\/h3>\r\n
Resources<\/span><\/h4>\r\n
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Buildings<\/span><\/h4>\r\n