AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …

Cooperation in multi-agent learning (MAL) is a topic at the intersection of numerous
disciplines, including game theory, economics, social sciences, and evolutionary biology …

Benchmarks play an important role in the development of machine learning algorithms. For
example, research in reinforcement learning (RL) has been heavily influenced by available …

Multi-agent reinforcement learning (MARL) methods struggle with the non-stationarity of
multi-agent systems and fail to adaptively learn online when tested with novel agents. Here …

What is appropriateness? Humans navigate a multi-scale mosaic of interlocking notions of
what is appropriate for different situations. We act one way with our friends, another with our …

Multi-agent reinforcement learning (MARL) has recently excelled in solving challenging
cooperative and competitive multi-agent problems in various environments with, mostly, few …

Algorithms play an increasingly important role in economic situations. Often these situations
are strategic, where the artificial intelligence may or may not be cooperative. We study the …

In social psychology, Social Value Orientation (SVO) describes an individual's propensity to
allocate resources between themself and others. In reinforcement learning, SVO has been …

As the field of AI continues to evolve, a significant dimension of this progression is the
development of Large Language Models and their potential to enhance multi-agent artificial …

Artificial Intelligence (AI) holds promise as a technology that can be used to improve
government and economic policy-making. This paper proposes a new research agenda …