Questions tagged [game-ai]
For questions related to game design involving AI.
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Can I use Alpha-Beta Pruning for real life game simulation?
I had an idea to use the this algorithm to simulate real life game scenarios where a player could train and retrain their mistake and be ready for when that situation happens again in real life.
This ...
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Determining minimal state representation for maze game
I came across this question set. It asks following question:
Let’s revisit our bug friends from assignment 2. To recap, you control one or more insects in a rectangular maze-like environment with ...
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How can we create an encoding scheme that captures these relationships between the suits of cards in poker?
In poker, a standard deck of 52 cards is used. Each card has one of 13 ranks, ranging from Ace to Deuce, and one of 4 suits: Spades, Hearts, Diamonds, or Clubs.
The rank of a card is crucial. For ...
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RL agent for autonomous vehicle is able to follow the road but can't avoid crashing at all (Highway-Env / Racetrack Env.)
I coded some deep RL algorithms (DQN and SAC) with tf2/keras to solve an environment where a vehicle needs to follow the track and avoid crashing into one other vehicle (there is only one other ...
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Neural network for game
There is a game for two, which is an NxN field (always the same size). Players take turns. The first player's goal is to connect the two points (not necessarily at the corners) given on this field. ...
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MCTS RAVE performing badly in Board Game AI
I'm using Monte Carlo Tree Search with UCT selection to try and build an AI player for a complex multiplayer board game. My regular UCT MCTS seems to be working fine, winning with random and basic ...
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Modern reinforcement learning for video game NPCs
Recently, I have been reading about the 1996 artificial life game 'Creatures'. The game features NPCs called 'Norns' that use reinforcement learning to learn continuously through interactions with the ...
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Do "procedurally generated" images use a set of base images to generate new images (as AI generated images do)?
I am new here, and apologize if this question is off-topic.
I know that AI generated images are based on a set or database of real images created by real artists.
In game development, I have heard of ...
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Developing character tactics via repeated trials
Let's assume a common game scenario of several characters in a combat arena. Each character has different strengths and weaknesses. The arena has traps and tools. Suppose the characters had only very ...
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How to Represent Boardless Board Game as Input to RL Model?
I am currently doing my thesis project by creating an Imitation Learning (IL) agent that learns to play the board game Hive, which lacks a traditional 2D board. Pieces are placed relative to one ...
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How to use deep learning to train an AI to play a two-player tactic game like rock-papers-scissors?
I want to try to train an AI model that can play a simple two-player tactic game. The game is not rock-papers-scissors, but have similar properties.
Firstly, two players present their moves ...
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How to embed game grid state with walls as an input to neural network
I've read most of the posts on here regarding this subject, however most of them deal with gameboards where there are two different categories of single pieces on a board without walls etc.
My game ...
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How could an AI detect whether an enemy in a game can be blocked off/trapped?
Imagine a game played on a 10x10 grid system where a player can move up down left or right and imagine there are two players on this grid: An enemy and you. In this game, there are walls on the grid ...
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Implementing an RL agent on a variable action space
I've been trying to design and implement a DQN agent as an AI opponent option for a math game I've been working on.
The game is a turn-based grid game, where players alternate making moves and ...
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What do I need to learn to tackle the following problem: make a program that optimizes decisions in the game PlateUp!
So, recently my friends and I have been hooked on a videogame called PlateUp!. The game is kind of a management game where the objective is to succesfully run a restaurant. The game can be roughly ...
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Can humans surpass AI in game-playing?
In the realm of game-playing, such as in the cases of AlphaGo and Deep Blue, can humans ultimately surpass AI in skill? Despite the current dominance of machine learning, what factors may contribute ...
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Which RL algorithm should I use to learn an optimal weight vector?
What is the best practice in order to learn the optimal weight vector $W^*$? By optimal I mean the weights that will produce the agent with the highest win-rate.
I have an agent that plays a ...
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How do you define an action space for a card game with an unlimited and variable hand size?
I'm new to the world of AI and have been primarily reading through the documentation for OpenAI's Gym/Gymnasium in hopes of training an AI to play a board game. One piece of information I haven't been ...
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Do the mathematics of Go imply an AI could solve it, or does a complexity bound imply AI skill will plateau?
Based on the mathematics of Go and the machine learning algorithms used to play it, is there a mathematical limit as to how much of the game-tree space even an AI could learn, because of the inherent ...
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Training model for a board game with large actions space
that has a NxM board, and players take turns putting their "dots" on the board a X,Y coordinate, taking up the space. When a few connected dots surround an opponent dot(s), the surrounding ...
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How to train a neural network for a round based board game?
I'm wondering how to train a neural network for a round based board game like, tic-tac-toe, chess, risk or any other round based game.
Getting the next move by inference seems to be pretty straight ...
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AI in dota2 vs AI in starcraft
I am just curious what AI would be harder to create from a strictly engineering point of view. AI which would win 1vs 1 game with the best player in starcraft or AI which would control a team the ...
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The neural network for a board game with somewhat imperfect information
I am a Software Engineer and I implemented online a pretty complex board game.
Some key rules of the game.
You have some cards in the hand and you can choose different turns.
Build a card of certain ...
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How should I train the players in the game of tag?
I have a simple game of tag, where red player tries to catch the blue player. Red player wins if it catches the blue player in under 10 seconds, but if not, then blue wins.
My goal is to teach the ...
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What is the depth reached by chess-AI agents on a regular computer?
I'm looking for some reference for the number of lookahead steps typically used by chess agents (Stockfish / Leela Chess Zero / others?)
From a quick search, I found that the answer depends on:
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What is the size of 6-players no limit Texas holdem Poker?
What is the number of game states/information sets in 6-players, no limit, Texas Holdem?
A year ago, Pluribus reached a super-human level in 6-players no limit Holdem Poker. I am interested in the ...
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Train Deep Q-Learning Network on a game without source code
So I have some games that I like, and I'd like to create a net that can play them, just for fun. But I don't have their source code, so I can't just pull the information I want and create a state from ...
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How can a neural network learn to play sudoku?
I'm just beginning to understand neural networks and I've performed a couple of successful tests with numerical series where the NN was trained to find the odd one or a missing value. It all works ...
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MCTS with multi actions
I know that MCTS usually is meant for games where each player plays turn by turn and the canonical form of the board is passed through the tree but is it possible for one player to make multiple moves ...
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Find evils with AI (social deduction games)
I’ve been playing a game called Town of Salem lately. The goal of the game is for the town to find and lynch all evils in the town. To lynch someone, they must be voted up to the gallows first. This ...
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Scrabble rack observation with MuZero
Currently I'm trying to implement Scrabble with MuZero.
The $15 \times 15$ game board observation (as input) is of size $27 \times15 \times15$ (26 letters + 1 wildcard) with a value of 0 or 1.
However ...
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Use of virtual worlds (e.g. Second Life) for training Artificial General Intelligence agents?
There is emerging effort for Third Wave Artificial Intelligence (Artificial General Intelligence) (http://hlc.doc.ic.ac.uk/3AI_HLC_2019.html and https://www.darpa.mil/work-with-us/ai-next-campaign) ...
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Could a good poker-playing AI be made that didn't look at its own cards?
A bit ago, I found out that researchers had taught a machine to play Texas Hold'Em at a level that beat most champions. However, that AI had access to the information of what cards it was dealt.
So I ...
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Is it practical to train AlphaZero or MuZero (for indie games) on a personal computer?
Is it practical/affordable to train an AlphaZero/MuZero engine using a residential gaming PC, or would it take thousands of years of training for the AI to learn enough to challenge humans?
I'm having ...
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Help with model architecture for a racing game
I’m working on a model for a racing game using pytorch. The model gets frame from the game as input and produces a controller state as output. The dataset consists of frames from the game and ...
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Which Reinforcement Learning algorithms are efficient for episodic problems?
I have some episodic datasets extracted from a turn-based RTS game in which the current actions leading to the next state doesn’t determine the final solution/outcome of the episode.
The learning is ...
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Is there a neural network in the literature that predicts the next game state based on the current state and the action?
I am trying to find literature on a network architecture that takes the following as in input:
Action (like 'Up', 'Down', etc)
Image of the current state
and outputs:
Image of next state
I already ...
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How should I choose the depth for minimax if I have a strict time constraint?
I am working on a controller that plays Ms. Pac-Man using a minimax algorithm. The controller has a limited time amount in which it can choose a move on each round, otherwise when the time runs out ...
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How to solve peg solitaire with a graph search?
Problem
I've been reading research papers on how to solve a peg solitaire using graph search, but all the papers kind of assume you know how to do the reduction(polynomial time conversion) from the ...
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Do I need to create one or many neural networks to play Risk? [closed]
I have a school project to develop an AI model that plays the Risk board game as optimally as possible. Now, I have made the environment of Risk in Python and I narrowed down my possible machine ...
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Encoding Actions with Parameters in Neural Network Output
I have a task which I would like to teach an AI to perform. The input to the task will a screenshot of the screen and the output at any given time step is one of the following actions:
...
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Unable to achieve expected outputs using NEAT for the snake game
I am trying to implement NEAT for the snake game. My game logic is ready, which is working properly and NEAT configured. But even after 100 generations with 200 genomes per generation, the snakes ...
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What is the Bellman equation for V(s) in the case of a deterministic environment?
I am currently trying to practice reinforcement learning for an agent on a grid. The grid is deterministic. Since the grid is deterministic, to calculate the value for each grid square from the reward ...
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How to make the RL player a perfect/expert (tic-tac-toe/chess) player?
I asked a question related to tic-tac-toe playing in RL. From the answer, it seems to me a lot is dependent on the opponent (rightly so, if we write down the expectation equations).
My questions are (...
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Is there a benefit to starting with MCTS and switching to minimax as the branching factor decreases?
I've invented a deterministic, perfect-information game with a fairly large branching factor (~150) which tapers out dramatically after the midgame (~30 at worst). I need a strong AI. My understanding ...
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What are the best practices of adding noise to game-playing bots?
I write bots that play card games. From time to time, I add noise to their decisions, mainly for two reasons:
Reduce predictability: In games with hidden information the optimal play is a mix between ...
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Deep RL reward design for neuron centerline extraction task
As part of a bigger scope project, I'm training a RL agent that attempts to reconstruct, pixel by pixel, the trajectory of a neuron on a segmented image. To give a better insight on the task that I'm ...
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Detecting cheats visually using AI
I really like to play my favorite 3D shooter game online. Unfortunately, it is really old and cheat protection isn't really common there, but cheaters are! It is very frustrating, because it really ...
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Is it possible to generate "Karel the robot" programs with genetic programming?
Karel the robot is an education software comparable to turtle graphics to teach programming for beginners. It's a virtual stack-based interpreter to run a domain-specific language for moving a robot ...
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Minimax evaluation function for games with score instead of loss/draw/win result
I am trying to create minimax evaluation function for the Ms Pacman game. The goal of the player is to maximize score.
I have some idea about the features that I would like to use in my evaluation ...
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