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• Basic AI FSM - Handling state transition

  - by Galvanize

  I'm starting to study on how to implement game AI, and it seems to me that a very simple FSM for my Pong demo would be a nice way to start. My vision on implementing this would be to have a basic state interface and a class for each state, then the NPC would have an instance of the current state. The class should have an update method and directions on wich state to go next, depending on the event received. The question is: How do I handle this event? Should I have a regular addEventListener and a costum event system? Or should I check on update for the things that could change the current state? I'm feeling a bit lost, I feel I have a good grasp on the FSM concept but a good implementation seems tricky, thanks in advance.

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• tic tac toe game ai as3

  - by David Jones

  I'm looking into creating a simple tic tac toe/noughts and crosses game in actionscript3 and am trying to understand the ideas behind the ai used in a game like this. I've seen some simplistic examples online but from what I've read a game tree or something like minimax is the best way to go about this. Can anyone help explain or reference any good examples of this? I've seen that there is a library called as3ds - data structures for game developers which has a number of classes that might help tie this together? Any info/examples or help is much appreciated

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• Designing a simple snake A.I

  - by DillPixel

  I've looked at some stuff online regarding this specific topic, and a lot of the info that I read involved graphs and path finding. I really don't want to get involved in something too complex & out of my level, and also I don't need my snake to be that intelligent (it will be a large board with the snake not growing in size on every munch). How could you structure a simpler AI for the snake that gets the job done relatively well? I would be able to get the snake to move towards the food item correctly, but my issue is that I'm not sure how to deal with the snake colliding with itself. Say the snake has a look ahead, and it finds that its tail is in the way, it could change direction, but what happens next? Any ideas on how to tackle this? Should the snake build an instruction set from every square, or should it think on the go?

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• Tic-Tac-Toe game AI

  - by David Jones

  I'm looking into creating a simple tic tac toe/noughts and crosses game in Actionscript3 and am trying to understand the ideas behind the AI used in a game like this. I've seen some simplistic examples online but from what I've read a game tree or something like minimax is the best way to go about this. Can anyone help explain or reference any good examples of this? I've seen that there is a library called as3ds - data structures for game developers which has a number of classes that might help tie this together? Any info/examples or help is much appreciated.

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• Developing an AI opponent for Monopoly

  - by Bernhard Zürn

  i want to develop an AI opponent for the Board Game Monopoly. I want to implement the whole Game with Prolog (XPCE). The probability for a field on the Board being hit, can be computed with Markov Chains. I already know some "best practices" like "after 50% of the playing time it does not make sense to buy out of jail because in jail you get renting fees for your fields but you don't have to pay for other fields as long as you stay in prison". The interesting question always is: buy a streetfield ? buy houses / hotels ? how much ? so i think i would have to compute some kind of future liquidity .. does anyone know how to pack that into an algorithm or how to translate it to prolog ?

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• Free Models and Related Animations for AI project in Unity [on hold]

  - by zhed

  Does anybody know a good website where to find free models and animations for AI projects? I'm not talking about anything good looking, like stuff you would look for when building a proper game, but, for example, a bunch of male/female models that are able to walk around and that would substitute my ugly "capsules", just to give a better -yet, still rough - idea of what's going on in the scene. On the Unity Asset Store there are a bunch of nice male/female models, but i haven't found any free general-purpose(i.e. normal walking) animation attachable to them. Any tip would we appreciated, thanks :)

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• Checkers AI Algorithm

  - by John

  I am making an AI for my checkers game and I'm trying to make it as hard as possible. Here is the current criteria for a move on the hardest difficulty: 1: Look For A Block: This is when a piece is being threatened and another piece can be moved in behind it to protect it. Here is an example: Black Moves |W| |W| |W| |W| | | |W| |W| |W| |W| |W| | | |W| |W| | | | | |W| | | | | | | | | |B| | | | | |B| | | |B| |B| |B| |B| |B| |B| | | |B| |B| |B| |B| White Blocks |W| |W| |W| |W| | | |W| | | |W| |W| |W| |W| |W| |W| | | | | |W| | | | | | | | | |B| | | | | |B| | | |B| |B| |B| |B| |B| |B| | | |B| |B| |B| |B| 2: Move pieces out of danger: if any piece is being threatened, and a piece cannot block for that piece, then it will attempt to move out of the way. If the piece cannot move out of the way without still being in danger, the computer ignores the piece. 3: If the computer player owns any kings, it will attempt to 'hunt down' enemy pieces on the board, if no moves can be made that won't in danger the king or any other pieces, the computer ignores this rule. 4: Any piece that is owned by the computer that is in column 1 or 6 will attempt to go to a side. When a piece is in column 0 or 7, it is in a very strategic position because it cannot get captured while it is in either of these columns 5: It makes an educated random move, the move will not indanger the piece that is moving or any piece that is on the board. 6: If none of the above are possible it makes a random move. This question is not really specific to any language but if all examples could be in Java that would be great, considering this app is written in android. Does anyone see any room for improvement in this algorithm? Anything that would make it better at playing checkers?

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• How to build a "traffic AI"?

  - by Lunikon

  A project I am working on right now features a lot of "traffic" in the sense of cars moving along roads, aircraft moving aroun an apron etc. As of now the available paths are precalculated, so nodes are generated automatically for crossings which themselves are interconnected by edges. When a character/agent spawns into the world it starts at some node and finds a path to a target node by means of a simply A* algorithm. The agent follows the path and ultimately reaches its destination. No problem so far. Now I need to enable the agents to avoid collisions and to handle complex traffic situations. Since I'm new to the field of AI I looked up several papers/articles on steering behavior but found them to be too low-level. My problem consists less of the actual collision avoidance (which is rather simple in this case because the agents follow strictly defined paths) but of situations like one agent leaving a dead-end while another one wants to enter exactly the same one. Or two agents meeting at a bottleneck which only allows one agent to pass at a time but both need to pass it (according to the optimal route found before) and they need to find a way to let the other one pass first. So basically the main aspect of the problem would be predicting traffic movement to avoid dead-locks. Difficult to describe, but I guess you get what I mean. Do you have any recommendations for me on where to start looking? Any papers, sample projects or similar things that could get me started? I appreciate your help!

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• Must all AI states be able to react to any event?

  - by Prog

  FSMs implemented with the State design pattern are a common way to design AI agents. I am familiar with the State design pattern and know how to implement it. How is this used in games to design AI agents? Consider a simplified class Monster, representing an AI agent: class Monster { State state; // other fields omitted public void update(){ // called every game-loop cycle state.execute(this); } public void setState(State state){ this.state = state; } // irrelevant stuff omitted } There are several State subclasses implementing execute() differently. So far, classic State pattern. AI agents are subject to environmental effects and other objects communicating with them. For example, an AI agent might tell another AI agent to attack (i.e. agent.attack()). Or a fireball might tell an AI agent to fall down. This means that the agent must have methods such as attack() and fallDown(), or commonly some message receiving mechanism to understand such messages. With an FSM, the current State of the agent should be the one taking care of such method calls - i.e. the agent delegates to the current state upon every event. Is this correct? If correct, how is this done? Are all states obligated by their superclass to implement methods such as attack(), fallDown() etc., so the agent can always delegate to them on almost every event? Or is it done in some other way?

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• How to build a "traffic AI"?

  - by Lunikon

  A project I am working on right now features a lot of "traffic" in the sense of cars moving along roads, aircraft moving aroun an apron etc. As of now the available paths are precalculated, so nodes are generated automatically for crossings which themselves are interconnected by edges. When a character/agent spawns into the world it starts at some node and finds a path to a target node by means of a simply A* algorithm. The agent follows the path and ultimately reaches its destination. No problem so far. Now I need to enable the agents to avoid collisions and to handle complex traffic situations. Since I'm new to the field of AI I looked up several papers/articles on steering behavior but found them to be too low-level. My problem consists less of the actual collision avoidance (which is rather simple in this case because the agents follow strictly defined paths) but of situations like one agent leaving a dead-end while another one wants to enter exactly the same one. Or two agents meeting at a bottleneck which only allows one agent to pass at a time but both need to pass it (according to the optimal route found before) and they need to find a way to let the other one pass first. So basically the main aspect of the problem would be predicting traffic movement to avoid dead-locks. Difficult to describe, but I guess you get what I mean. Do you have any recommendations for me on where to start looking? Any papers, sample projects or similar things that could get me started? I appreciate your help!

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• Designing Snake AI

  - by Ronald

  I'm new to this gamedev stackechange but have used the math and cs sites before. So, I'm in a competition to create AI for a snake that will compete with 3 other snakes in 5 minute rounds where the rules are much like the traditional Nokia snake game except that there are 4 snakes, the board is 50x50 and there are a number of small obstacles on the field. Like the Nokia game, your snake grows when you get to the fruit and if you crash into yourself, another snake or the wall you die. The game runs with a 50ms delay between moves and the server sends the new game state every 50ms which the code must analyze and what not and output the next move. The winner is the snake who had the longest length at any point in the game. Tie breakers are decided by kills. So far what I have done is implemented an A* graph search from each snake to determine if my snake is the closest to the apple and if it is, it goes for the apple. Otherwise, I made a neat little algorithm to determine the emptiest area of the board, which my snake goes for, to anticipate the next apple. Other than this I have some small survivability checks to ensure my snake isn't walking into a trap that it can't get out and if it does get stuck, I have something to give it a better chance of getting out. ... Anyway, I've tested my snake on a test server and it does quite well. Generally, my strategy of only going for the apple when its a sure thing and finding space when its not makes it grow faster than any other snakes (some snakes do a similar thing but often just go to the middle or a corner) sometimes it wins these trial games but is more often than not beaten by the same snake who seems to have the edge on survivability(my snake grows quicker but then dies somehow and this other snake just plods slowly along and wins on consistency. So I was wondering about any ideas anyone has to try and improve my snake. Or maybe ideas at a new approach to take. My functions and classes are good so changes that might seem drastic shouldn't be too bad. I encourage all ideas. Any thoughts ??

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• How would you code an AI engine to allow communication in any programming language?

  - by Tokyo Dan

  I developed a two-player iPhone board game. Computer players (AI) can either be local (in the game code) or remote running on a server. In the 2nd case, both client and server code are coded in Lua. On the server the actual AI code is separate from the TCP socket code and coroutine code (which spawns a separate instance of AI for each connecting client). I want to be able to further isolate the AI code so that that part can be a module coded by anyone in their language of choice. How can I do this? What tecniques/technology would enable communication between the Lua TCP socket/coroutine code and the AI module?

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• Better way to do AI Behavior in AS3/Flixel

  - by joon

  I'm making a game in Flixel and I need to program an NPC. It's rapidly turning more complex than I expected. I was wondering if there are any best practices, tutorials or examples that you can refer me to, to see how this is done. I can probably hack it together, which is what I always do, but it would be nice if I can make it maintanable and can add stuff later on. Here's screenshot to give you an idea: The butler will be an NPC that will follow you, or guide you, and talk to you the whole time. EDIT: More specifically: What I have now is a long list of IF statements in the update loop of the butler (about 8 different cases), and all I have covered is his walking behavior. I want him to comment on things and sometimes switch his main behavior to be more aggresive or distant,... Is there any way to keep track of this, or is complex code with many many nested if statements the way to go?

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• Path tables or real time searching for AI?

  - by SirYakalot

  What is the more common practice in commercial games; path lookup tables or real time searches? I've read that in many games path lookup tables are pre-calculated and baked into each map, so to speak, then steering behaviour is used to handle dynamic obstacles. or is it better practice to use optimised hierarchical A* searches? I understand the pro's and cons of each, I'm just curious as to what is most often used in the industry.

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• Adaptive Characters: AI Solution Needs a Problem

  - by Roger F. Gay

  Have sophisticated adaptive programming, will travel - so to speak. I'm part of a group that developed sophisticated learning / adaptive software for robotics. The system "thinks" via its simulator, building and adapting code on its own; and then carries out the best solution. The software can also adapt to new situations, etc. http://mensnewsdaily.com/2007/05/16/robobusiness-robots-with-imagination/ It's easy to imagine using it with automated game characters that will adapt to the players moves and style - the easiest example would be fighting. The more the simulated fighter fights with the human player, the more it learns to counter that players fighting skills. But there should be more. Anyone have any ideas as to how adaptive characters might be interesting in games?

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• Collision Detection fails with AI cars

  - by amit.r007

  I am making a car parking game in flash and AS3 wherein I drive my car along with other AI traffic cars moving along a specified path using Guidelines. I am using CDK for collision detection. The collision detection works fine with few AI cars, but doesn't seems to be working as required for few AI cars. When an AI car is moving on a path in a straight line it works fine.... but when the AI Car turns at 90 degress..... my car goes into the AI car (Overlapping) and it hits at the center of that AI car and then collision is Detected.... ..... I made a New path and used a new Sprite for AI car... but still the problem pursues....

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• What are the possible options for AI path-finding etc when the world is "partitionned"?

  - by Sebastien Diot

  If you anticipate a large persistent game world, and you don't want to end up with some game server crashing due to overload, then you have to design from the ground up a game world that is partitioned in chunks. This is in particular true if you want to run your game servers in the cloud, where each individual VM is relatively week, and memory and CPU are at a premium. I think the biggest challenge here is that the player receives all the parts around the location of the avatar, but mobs/monsters are normally located in the server itself, and can only directly access the data about the part of the world that the server own. So how can we make the AI behave realistically in that context? It can send queries to the other servers that own the neighboring parts, but that sounds rather network intensive and latency prone. It would probably be more performant for each mob AI to be spread over the neighboring parts, and proactively send the relevant info to the part that contains the actual mob atm. That would also reduce the stress in a mob crossing a border between two parts, and therefore "switching server". Have you heard of any AI design that solves those issues? Some kind of distributed AI brain? Maybe some kind of "agent" community working together through message passing?

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• Where can I train my game AI skills? (any upgoing competition?) [on hold]

  - by user1671710

  There are 2 main options - building AI plugin for existing game or entering to some competition. Do you have some concrete tips? Is there any competition which will be soon open? From my research, competitions: http://aichallenge.org (last 2011) http://www.battlecode.org (January 2014) http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp/index.shtml (August 2014) http://aibirds.org (maybe summer 2014) http://www.marioai.org (last 2012) http://www.ice.ci.ritsumei.ac.jp/~ftgaic/index.htm (last 2013) http://www.pacman-vs-ghosts.net (last 2012) http://ai-contest2013.gameloft.com/index/contest (last 2013) http://www.botprize.org/ (last 2012) And maybe more. These are from quick research. Obviously there were many competitions this year but it is difficult to catch it. Main question is: Do you have any information of any currently running AI competition?

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• Best way to implement an AI for Dominion? [on hold]

  - by j will

  I'm creating a desktop client and server backend for the game, Dominion, by Donald X. Vaccarino. I've been reading up on AI techniques and algorithms and I just wanted to what is the best way to implement an AI for such a game? Would it better to look at neural networks, genetic algorithms, decision trees, fuzzy logic, or any other methodology? For those who do not know how Dominion works, check out this part of the wikipedia article: http://en.wikipedia.org/wiki/Dominion_(card_game)#Gameplay

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• What are some ways of making manageable complex AI?

  - by Tetrad

  In the past I've used simple systems like finite state machines (FSMs) or hierarchical FSMs to control AI behavior. For any complex system, this pattern falls apart very quickly. I've heard about behavior trees and it seems like that's the next obvious step, but haven't seen a working implementation or really tried going down that route yet. Are there any other patterns to making manageable yet complex AI behaviors?

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• Do I need path finding to make AI avoid obstacles?

  - by yannicuLar

  How do you know when a path-finding algorithm is really needed? There are contexts, where you just want to improve AI navigation to avoid an object, like a space -ship that won't crash on a planet or a car that already knows where to steer, but needs small corrections to avoid a road bump. As I've seen on similar posts, the obvious solution is to implement some path-finding algorithm, most likely like A*, and let your AI-controlled object to navigate through the path. Now, I have the necessary skills to implement a path-finding algorithm, and I'm not being lazy here, but I'm still a bit skeptical on if this is really needed. I have the impression that path-finding is appropriate to navigate through a maze, or picking a path when there are many alternatives. But in obstacle avoidance, when you do know the path, but need to make slight corrections, is path finding really necessary? Even when the obstacles are too sparse or small ? I mean, in real life, when you're driving and notice a bump on the road, you will just have to pick between steering a bit on the left (and have the bump on your right side) or the other way around. You will not consider stopping, or going backwards. A path finding would be appropriate when you need to pick a route through the city, right ? So, are there any other methods to help AI navigation, except path-finding? And if there are, how do you know when path-fining is the appropriate algorithm ? Thanks for any thoughts

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• Discovering path through unknown territory

  - by TravisG

  Let's say all the AI knows about it's surroundings is a pixel-map that it has which clearly shows walkable terrain and obstacles. I want the AI to be able to traverse this terrain until it finds an exit point. There are some restrictions: There is always a way to the exit in the entire map that the AI walks around in, but there may be dead ends. The path to the exit is always pretty random, meaning that if you stand at crossroads, nothing indicates which direction would be the right one to go. It doesn't matter if the AI reaches a dead end, but it has to be able walk back out of it to a previously not inspected location and continue its search there. Initially, the AI starts out knowing only the starting area of the whole map. As it walks around, new points will be added to the pixel-map as the AI corresponding to the AIs range of sight (think of it like the AI is clearing the fog of war) The problem is in 2D space. All I have is the pixel map. There are no paths in the pixel map which are "too narrow". The AI fits through everything. It shouldn't be a brute force solution. E.g. it would be possible to simply find a path to each pixel in the pixel map that is yet undiscovered (with A*, for example), which will lead to the AI discovering new pixels. This could be repeated until the end is reached. The path doesn't have to be the shortest path (this is impossible without knowing the entire map beforehand), but when movements within the visible area are calculated, the shortest and from a human standpoint most logical path should be taken (e.g. if you can see a way out of your room into a hallway, you would obviously go there instead of exploring the corner of your current room). What kind of approaches to solve this problem are there?

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• What's the proper way to calculate probability for a card game?

  - by Milan Babuškov

  I'm creating AI for a card game, and I run into problem calculating the probability of passing/failing the hand when AI needs to start the hand. Cards are A, K, Q, J, 10, 9, 8, 7 (with A being the strongest) and AI needs to play to not take the hand. Assuming there are 4 cards of the suit left in the game and one is in AI's hand, I need to calculate probability that one of the other players would take the hand. Here's an example: AI player has: J Other 2 players have: A, K, 7 If a single opponent has AK7 then AI would lose. However, if one of the players has A or K without 7, AI would survive. Now, looking at possible distribution, I have: P1 P2 AI --- --- --- AK7 loses AK 7 survives A7 K survives K7 A survives A 7K survives K 7A survives 7 KA survives AK7 loses Looking at this, it seems that there is 75% chance of survival. However, I skipped the permutations that mirror the ones from above. It should be the same, but somehow when I write them all down, it seems that chance is only 50%: P1 P2 AI --- --- --- AK7 loses A7K loses K7A loses KA7 loses 7AK loses 7KA loses AK 7 survives A7 K survives K7 A survives KA 7 survives 7A K survives 7K A survives A K7 survives A 7K survives K 7A survives K A7 survives 7 AK survives 7 KA survives AK7 loses A7K loses K7A loses KA7 loses 7AK loses 7KA loses 12 loses, 12 survivals = 50% chance. Obviously, it should be the same (shouldn't it?) and I'm missing something in one of the ways to calculate. Which one is correct?

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• What data should be cached in a multiplayer server, relative to AI and players?

  - by DevilWithin

  In a virtual place, fully network driven, with an arbitrary number of players and an arbitrary number of enemies, what data should be cached in the server memory, in order to optimize smooth AI simulation? Trying to explain, lets say player A sees player B to E, and enemy A to G. Each of those players, see player A, but not necessarily each other. Same applies to enemies. Think of this question from a topdown perspective please. In many cases, for example, when a player shoots his gun, the server handles the sound as a radial "signal" that every other entity within reach "hear" and react upon. Doing these searches all the time for a whole area, containing possibly a lot of unrelated players and enemies, seems to be an issue, when the budget for each AI agent is so small. Should every entity cache whatever enters and exits from its radius of awareness? Is there a great way to trace the entities close by without flooding the memory with such caches? What about other AI related problems that may arise, after assuming the previous one works well? We're talking about environments with possibly hundreds of enemies, a swarm.

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• AI Game Programming : Bayesian Networks, how to make efficient?

  - by Mahbubur R Aaman

  We know that AI is one of the most important part of Game Programming. Bayesian networks is one of the core part of AI at Game Programming. Bayesian networks are graphs that compactly represent the relationship between random variables for a given problem. These graphs aid in performing reasoning or decision making in the face of uncertainty. Here me, utilizing the monte carlo method and genetic algorithms. But tooks much time and sometimes crashes due to memory. Is there any way to implement efficiently?

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