132 citations · 208 across the 17 of their papers we have counts for
3 papers · 1 filter
Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games
Roxana Rădulescu, Timothy Verstraeten, Yijie Zhang +3
Many real-world multi-agent interactions consider multiple distinct criteria, i.e. the payoffs are multi-objective in nature. However, the same multi-objective payoff vector may le…
Deep Reinforcement Learning for Autonomous Driving: A Survey
B Ravi Kiran, Ibrahim Sobh, Victor Talpaert +4
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in…
A utility-based analysis of equilibria in multi-objective normal form games
Roxana Rădulescu, Patrick Mannion, Yijie Zhang +2
In multi-objective multi-agent systems (MOMAS), agents explicitly consider the possible tradeoffs between conflicting objective functions. We argue that compromises between competi…