Conquer the Citadel was created as the final project for my VR course. The game is a VR roguelike deckbuilder that takes inspiration from games like Slay the Spire and Gloomhaven. Going into it, my teammate and I knew the scope was ambitious, but we managed to implement almost all of the systems we designed for the game. Altogether we managed to implement combat, status effects, a procedural dungeon map, adding cards to your deck, treasures that grant useful passives, multiple-choice events, shops, and two different characters with their own card pools. One interesting design choice we made was to make the cards and enemy AI highly data-driven. This way, we could add new cards and enemies using existing actions without writing any new code.
Designing And Building Stockfighter, Our Programming Game | Kalzumeus Software
Building games that can be understood at a glance
Building games that can be understood at a glance - Zach Gage, GDC 2018
Building games that can be understood at a glance
Building games that can be understood at a glance - Zach Gage, GDC 2018
Pitfalls of Card UIs
I’m currently in the process of rolling out yet another Card UI. Since Pinterest, the end-state of every list view with decent imagery is to become a Card UI. But thar be dragons! I’m here to share some of the pitfalls Paravel have encountered building Card UIs over the years.
Virtual Cards | Old Open Collective Docs
Virtual cards are an additional benefit offered to collectives through some hosts. Hosts create virtual cards and assign them to a Collective. Anyone with access to that card can then use it to make payments on behalf of the Collective. This is particularly useful for covering recurring costs like hosting a website.
TextWorld: A Learning Environment for Text-based Games
We introduce TextWorld, a sandbox learning environment for the training and evaluation of RL agents on text-based games. TextWorld is a Python library that handles interactive play-through of text games, as well as backend functions like state tracking and reward assignment. It comes with a curated list of games whose features and challenges we have analyzed. More significantly, it enables users to handcraft or automatically generate new games. Its generative mechanisms give precise control over the difficulty, scope, and language of constructed games, and can be used to relax challenges inherent to commercial text games like partial observability and sparse rewards. By generating sets of varied but similar games, TextWorld can also be used to study generalization and transfer learning. We cast text-based games in the Reinforcement Learning formalism, use our framework to develop a set of benchmark games, and evaluate several baseline agents on this set and the curated list.
Quickly Training Game-Playing Agents with Machine Learning
Posted by Leopold Haller and Hernan Moraldo, Software Engineers, Google Research In the last two decades, dramatic advances in compute and connecti...
No One Wins in Nuclear War: Social Simulations of High-stakes Military Decision-making
WOPR is a social-simulation environment for studying how organizations make high-stakes decisions, built on a deterministic, replay-validated rules engine and using wargames as the vehicle. We instantiate it first with the published card game Nuclear War, traced against its published rules. We start with military decision-making because of its safety implications and because it needs further study, but the design is not specific to it: the decision- point contract that exposes the engine to agents is reusable across verifiable rule systems. Existing social-simulation work emphasizes persona fidelity and synthetic opinion, but lacks a verifiable rules engine with replay-checkable mechanics and private-channel negotiation. WOPR supplies that engine, and its contract makes every strategic choice an explicit agent decision. The method is agnostic to social-simulation frameworks; we adopt Concordia as the default harness for driving the game. On the same engine, WOPR layers a four-rung press ladder from silence to private single- recipient channels with structured commitments, and instantiates each faction as a collective command-and-control system rather than a single agent. We make all code, example configurations, and replay data publicly available at https://github.com/eilab-gt/wopr.
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Building the Future of Games on ATProto | Birbhouse Games
Game platforms hold too much power over developers. We want to change that by decentralizing games with ATProto — devs own their data, players own their progress, and no payment processor can take it away.
Steam Deck Guide — make the most of your Steam Deck
How to write better (game) libraries
Introduction The aim of this article is to provide a series of good general advice and consideratio…
