Questions tagged [game-ai]
For questions related to game design involving AI.
241
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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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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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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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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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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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At what point is AI go-playing expected to plateau?
Are we seeing constant improvements in AIs ability to beat itself at Go, and if so, is it completely unknown when AI may play Go so well that there is no room for improvement, approaching the limit of ...
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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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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 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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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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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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Agent communication in multi agent system
My task is to compare different ways of communication between two(or more) intelligent agents and decide which has the best performance. I've done my research, and it appears that there are two ways ...
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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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Can you save actions from a player into a NEAT config and create a sort of child of that player to then train against?
The question I have is more from interest, as I have seen a few things on the internet about people training an AI using footage of real people playing games.
I was wondering if you could train it ...
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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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How do you determine the optimal policy?
I am following some Grid world examples to understand reinforcement learning. I have a deterministic grid (part of which I have reconstructed below). I am trying to understand how the optimal policy ...
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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 are previous values updated when performing value iteration?
I have been trying to understand how you determine the value for each square in a grid world and I have seen/watched a few different examples to try and apply it to my own grid and I find myself ...
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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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What is the typical AI approach for solving blackjack?
I'm currently developing a blackjack program. Now, I want to create an AI that essentially uses the mathematics of blackjack to make decisions.
So, what is the typical AI approach for solving ...
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Is the new AlphaGo implementation using Generative Adversarial Networks?
I read through the publication Mastering the game of Go without Human Knowledge. It doesn't seem to use GANs, just a new form of search and reinforcement learning.
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Why is tic-tac-toe considered a non-deterministic environment?
I have been reading about deterministic and stochastic environments, when I came up with an article that states that tic-tac-toe is a non-deterministic environment.
But why is that?
An action will ...
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Which are more memory efficient: uninformed or informed search algorithms?
I have extensively researched now for three days straight trying to find which algorithm is better in terms of which algorithm uses up more memory. I know uninformed algorithms, like depth-first ...
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Is there a better way of calculating the chance of winning than $\mu * (1 - (\sigma * f)) * 100$ for the card game schnapsen?
My AI (for the card game schnapsen) currently calculates every possible way the game could end and then evaluates the percentage of winning for every playable card / move. The calculation is done ...
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Could you share with me the tree size, search time and search depth of your implementation of Gomoku with minimax and alpha-beta prunning?
Currently, I am working on a Gomoku AI implementation with minimax + alpha-beta pruning.
I'm targeting these two rules from 'acceptable implementation' in terms of search time and search depth :
...
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Which algorithms can we use on games with high branching factors (e.g. Connect6)?
Connect6 is an example of a game with a very high branching factor. It is about 45 thousand, dwarfing even the impressive Go.
Which algorithms can we use on games with such high branching factors?
I ...
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Historical weakness of GOFAI in relation to partisan combinatorial games?
I was recently perusing the paper Some Studies in Machine Learning Using the Game of Checkers II--Recent Progress (A.L. Samuel, 1967), which is interesting historically.
I was looking at this figure, ...
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What's the difference between poker with public cards and without them?
Example: Texas Holdem poker vs Texas Holdem poker with the same rounds, just with no public cards dealt.
Would algorithms, like CFR, approximate the Nash equilibrium more easily? Could AI that does ...
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What are examples of approaches to create an AI for a fighting robot in an MMO game?
I have an MMO game where I have players. I wanted to invent something new to the game, and add player-bots to make the game be single-playable as well. The AI I want to add is simply only for fighting ...
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