This paper introduces Honor of Kings Arena, a reinforcement learning (RL) environment
based on the Honor of Kings, one of the world's most popular games at present. Compared …

Learning rational behaviors in open-world games like Minecraft remains to be challenging
for Reinforcement Learning (RL) research due to the compound challenge of partial …

The past few years have seen rapid progress in combining reinforcement learning (RL) with
deep learning. Various breakthroughs ranging from games to robotics have spurred the …

Self-play, characterized by agents' interactions with copies or past versions of itself, has
recently gained prominence in reinforcement learning. This paper first clarifies the …

With the rapid prevalence and explosive development of Multiplayer Online Battle Arena
electronic sports (MOBA esports), much research effort has been devoted to automatically …

Due to the partial observability and communication constraints in many multiagent
reinforcement learning (MARL) tasks, centralized training with decentralized execution …

We study the adaption of soft actor-critic (SAC) from continuous action space to discrete
action space. We revisit vanilla SAC and provide an in-depth understanding of its Q value …

Intelligent game agents are crafted using AI technologies to mimic player behavior and
make decisions autonomously. Over the past decades, the scope of intelligent agents has …

Hero drafting for multiplayer online arena (MOBA) games is crucial because drafting directly
affects the outcome of a match. Both sides take turns to" ban"/" pick" a hero from a roster of …

Recently, many researchers have made successful progress in building the AI systems for
MOBA-game-playing with deep reinforcement learning, such as on Dota 2 and Honor of …