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Real-Time Strategy Games

Real-Time Strategy (RTS) tasks involve training an agent to play video games with continuous gameplay and high-level macro-strategic goals such as map control, economic superiority and more.

( Image credit: Multi-platform Version of StarCraft: Brood War in a Docker Container )

Papers

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Showing 1–46 of 46 papers

TitleStatusHype
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine LearningCode1
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetCode1
A Closer Look at Invalid Action Masking in Policy Gradient AlgorithmsCode1
The StarCraft Multi-Agent ChallengeCode1
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for Real-time Strategy GamesCode1
Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy gamesCode0
A Dataset for StarCraft AI \& an Example of Armies ClusteringCode0
Clear the Fog: Combat Value Assessment in Incomplete Information Games with Convolutional Encoder-DecodersCode0
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy GamesCode0
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy GamesCode0
Experiments with Game Tree Search in Real-Time Strategy GamesCode0
Forward Modeling for Partial Observation Strategy Games - A StarCraft DefoggerCode0
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance AnalysisCode0
Macro action selection with deep reinforcement learning in StarCraftCode0
MSC: A Dataset for Macro-Management in StarCraft IICode0
Multi-platform Version of StarCraft: Brood War in a Docker Container: Technical ReportCode0
StarAlgo: A Squad Movement Planning Library for StarCraft using Monte Carlo Tree Search and NegamaxCode0
StarCraft II: A New Challenge for Reinforcement LearningCode0
StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer LearningCode0
STARDATA: A StarCraft AI Research DatasetCode0
Terrain Analysis in StarCraft 1 and 2 as Combinatorial OptimizationCode0
TorchCraft: a Library for Machine Learning Research on Real-Time Strategy GamesCode0
TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full GameCode0
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors—0
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games—0
Implementing a Wall-In Building Placement in StarCraft with Declarative Programming—0
Three-dimensional attention Transformer for state evaluation in real-time strategy games—0
The Design Of "Stratega": A General Strategy Games Framework—0
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games—0
Multi-objective evolution for 3D RTS Micro—0
Combining Strategic Learning and Tactical Search in Real-Time Strategy Games—0
Combinatorial Multi-armed Bandits for Real-Time Strategy Games—0
CortexCompile: Harnessing Cortical-Inspired Architectures for Enhanced Multi-Agent NLP Code Synthesis—0
Deep Learning for Video Game Playing—0
Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey—0
A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents—0
Demonstrating the Feasibility of Automatic Game Balancing—0
Co-evolving Real-Time Strategy Game Micro—0
Neuroevolution for RTS Micro—0
Evolutionary Multi-objective Optimization of Real-Time Strategy Micro—0
On games and simulators as a platform for development of artificial intelligence for command and control—0
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning—0
Reinforcement Learning approach for Real Time Strategy Games Battle city and S3—0
A Survey of Deep Reinforcement Learning in Video Games—0
High-Level Strategy Selection under Partial Observability in StarCraft: Brood War—0
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