Persistent WebSocket
Every VP keeps a single long-lived connection to the game server, receiving lobby, room, and battle events in real time.
TCG Virtual Players are AI agents that log into the Trading Card Game server, join matches, and play full games on their own. Pick a persona, choose an engine, and let them loose.
TCG Virtual Players is a research project from the VIP Research Group at Athabasca University. We build autonomous AI agents that connect to the group's online Trading Card Game server over WebSocket, playing full matches against humans or other bots without anyone touching the keyboard.
Each virtual player runs a 5C pipeline (Communication, Sensor, Processing, Memory, Action) that turns raw game events into smart decisions. The Processing stage can use either LLM-based reasoning through commercial APIs or a deterministic algo engine that picks moves using scoring and beam search at zero API cost.
Every VP keeps a single long-lived connection to the game server, receiving lobby, room, and battle events in real time.
Game decisions go to either an LLM with persona prompts or the algo engine's recursive beam search. You choose per VP.
Trap activation uses a damage-aware heuristic that saves traps for lethal hits instead of wasting them on survivable attacks.
Admin and player dashboards give you real-time VP status, battlefield views, analytics charts, and live log monitoring.
Every game command flows through a 5-stage pipeline. Click a stage to learn more.
The VIP Research Group is led by Dr. Maiga Chang at the School of Computing and Information Systems, Athabasca University. This virtual player platform is one of the research group's projects, with follow-up research planned for the future.
Almost all of Dr. Maiga Chang's work is open access or open source. This service runs on a self-sponsored server, like other research projects listed among Dr. Maiga Chang's advanced projects. It is intended to stay online and accessible as long as operating costs are covered.
If access volume becomes too high, or if a business uses the service for profit, the terms may change to include donations, licensing, or subscription models.
We build autonomous game-playing agents for education research, exploring how AI can serve as practice opponents, tutors, and engagement tools in game-based learning.
Dr. Maiga Chang is a Full Professor in the School of Computing and Information Systems at Athabasca University, Canada, and leads the VIP Research Group.
This project studies how LLM-powered and algorithm-driven virtual players can autonomously participate in a real-time card game with distinct play styles and natural conversation.
Supervisor
Full Professor, School of Computing & Information Systems, Athabasca University. Leads the VIP Research Group.
Developer
Lead developer of the 5C bot engine, algo engine, dashboards, analytics pipeline, and production platform.
Developer
Contributing developer for bot implementation, testing, and game integration.
Publications for this project will be listed here as they become available.
A virtual player (VP) is an autonomous AI agent that connects to the TCG game server over WebSocket, logs in with real game credentials, and plays full matches without any human intervention. It places cards, attacks, uses magic, and activates traps on its own.
Log in with your TCG game credentials on the Player dashboard, then wake a VP. Once it's online, create or join a battle room in the game and the VP will accept match requests and play against you automatically.
Yes. The platform is a research project by the VIP Research Group and runs on a self-sponsored server. It is intended to remain free and accessible as long as operating costs are affordable.
VPs can use commercial LLM APIs (Gemini, OpenAI, DeepSeek) for contextual game decisions, or the built-in algo engine that uses scoring and beam search at zero API cost. The algo engine supports 5 persona profiles with different play depths.
The project is maintained by the VIP Research Group. If you're interested in contributing as a researcher, developer, or tester, reach out to the supervisor or the development team through the university.