AI for Games | Quark

Neural Game Maker

Making games with AI

Dazzle

Create and play games with AI

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...

Mastering Real-Time Strategy Games with Deep Reinforcement Learning: Mere Mortal Edition

The capabilities of game-playing AIs have grown rapidly over the last few years. This trend has culminated in the defeat of top human players in the complex real-time strategy (RTS) games of DoTA 2…

Scalable decision-making for games of imperfect information

Real-world decision-making generally involves hidden information, that is, information that is unknown to one agent but possessed by another. Unfortunately, the presence of large amounts of hidden information renders established reinforcement learning and search approaches ineffective. Even with multimillion-dollar industrial research efforts1, top-human-level play at Stratego—a board wargame with hidden information on a massive scale—has remained beyond the reach of artificial intelligence (AI). Here we introduce Ataraxos, an AI for Stratego based on general techniques that we developed for both self-play reinforcement learning and test-time search under hidden information. Ataraxos defeated the most decorated human Stratego player of all time by a large margin—achieving, to our knowledge, the first superhuman result in the game’s history—while consuming orders of magnitude less compute and data than previous efforts. Using the same techniques, we built a superhuman AI for Barrage Stratego and state-of-the-art AIs for Hanabi and dou dizhu, all with low cost and high sample efficiency. The success of this approach across adversarial, cooperative and team games establishes a design pattern for reinforcement learning and search that is effective under large amounts of hidden information, a longstanding desideratum of the field of strategic decision-making.

AI Coding is Gambling

GambleAI I’ve been coding a lot with AI since November, when we all noticed it got really good. And it is quite good for instantly generating something th...

ZETIC | On-Device AI for Everything - for any model, on any device, in any framework

Built by ex-Qualcomm AI Engineer. Automate on-device AI deployment with full NPU optimization. Benchmark on 100+ physical devices and ship in hours with just 3 lines of code.

Build your First AI game bot using OpenAI Gym, Keras, TensorFlow in Python

This post will explain about OpenAI Gym and show you how to apply Deep Learning to play a CartPole game.

AIs can’t stop recommending nuclear strikes in war game simulations

Leading AIs from OpenAI, Anthropic and Google opted to use nuclear weapons in simulated war games in 95 per cent of cases

ReBeL: A general game-playing AI bot that excels at poker and more

Combining reinforcement learning with search (RL+Search) has been tremendously successful for perfect-information games. But prior RL+Search algorithms break down in

Game Bots Provide A Different Story For AI

When applied to game systems in the future players will find it harder to distinguish between bot and human players. We will appreciate having AI support in games to help us learn or improve, without ruining the game or requiring deep dives into manuals or tutorial YouTube videos.

Look-ahead Reasoning with a Learned Model in Imperfect Information Games

Test-time reasoning significantly enhances pre-trained AI agents' performance. However, it requires an explicit environment model, often unavailable or overly complex in real-world scenarios....

Tidewave

The complete AI dev toolkit for Phoenix and Rails

pguso/ai-agents-from-scratch

Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.

SambaNova | The Fastest AI Inference Platform

Discover SambaNova - the complete AI platform delivering the fastest AI inference, fine-tuning, and scalable solutions for agentic AI easily integrated into existing data center infrastructures.