Autonomous agents modelling other agents: A comprehensive survey and open problems
Much research in artificial intelligence is concerned with the development of autonomous
agents that can interact effectively with other agents. An important aspect of such agents is …
agents that can interact effectively with other agents. An important aspect of such agents is …
Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques
A negotiation between agents is typically an incomplete information game, where the agents
initially do not know their opponent's preferences or strategy. This poses a challenge, as …
initially do not know their opponent's preferences or strategy. This poses a challenge, as …
[BOOK][B] Artificial intelligence and games
GN Yannakakis, J Togelius - 2018 - Springer
Georgios N. Yannakakis Julian Togelius Page 1 Artificial Intelligence and Games Georgios N.
Yannakakis Julian Togelius Page 2 Artificial Intelligence and Games Page 3 Georgios N …
Yannakakis Julian Togelius Page 2 Artificial Intelligence and Games Page 3 Georgios N …
Opponent modeling in deep reinforcement learning
Opponent modeling is necessary in multi-agent settings where secondary agents with
competing goals also adapt their strategies, yet it remains challenging because of strategies' …
competing goals also adapt their strategies, yet it remains challenging because of strategies' …
A survey of real-time strategy game AI research and competition in StarCraft
This paper presents an overview of the existing work on AI for real-time strategy (RTS)
games. Specifically, we focus on the work around the game StarCraft, which has emerged in …
games. Specifically, we focus on the work around the game StarCraft, which has emerged in …
In the blink of an eye: leveraging blink-induced suppression for imperceptible position and orientation redirection in virtual reality
Immersive computer-generated environments (aka virtual reality, VR) are limited by the
physical space around them, eg, enabling natural walking in VR is only possible by …
physical space around them, eg, enabling natural walking in VR is only possible by …
Multi-agent reinforcement learning for order-dispatching via order-vehicle distribution matching
Improving the efficiency of dispatching orders to vehicles is a research hotspot in online ride-
hailing systems. Most of the existing solutions for order-dispatching are centralized …
hailing systems. Most of the existing solutions for order-dispatching are centralized …
A survey of opponent modeling in adversarial domains
Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …
the behavior of an opponent. This survey presents a comprehensive overview of existing …
A deep policy inference q-network for multi-agent systems
We present DPIQN, a deep policy inference Q-network that targets multi-agent systems
composed of controllable agents, collaborators, and opponents that interact with each other …
composed of controllable agents, collaborators, and opponents that interact with each other …
Agent modeling as auxiliary task for deep reinforcement learning
In this paper we explore how actor-critic methods in deep reinforcement learning, in
particular Asynchronous Advantage Actor-Critic (A3C), can be extended with agent …
particular Asynchronous Advantage Actor-Critic (A3C), can be extended with agent …