Groups of humans are often able to find ways to cooperate with one another in complex,
temporally extended social dilemmas. Models based on behavioral economics are only able …

Matrix games like Prisoner's Dilemma have guided research on social dilemmas for
decades. However, they necessarily treat the choice to cooperate or defect as an atomic …

Social dilemmas are situations where individuals face a temptation to increase their payoffs
at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in …

Recent research on reinforcement learning in pure-conflict and pure-common interest
games has emphasized the importance of population heterogeneity. In contrast, studies of …

Multi-agent cooperation is an important feature of the natural world. Many tasks involve
individual incentives that are misaligned with the common good, yet a wide range of …

Humans routinely use conditionally cooperative strategies when interacting in repeated
social dilemmas. They are more likely to cooperate if others cooperated before, and are …

Our social interactions vary over time and they depend on various factors that determine our
preferences and goals, both in personal and professional terms. Researches have shown …

Abstract Since Alan Turing envisioned artificial intelligence, technical progress has often
been measured by the ability to defeat humans in zero-sum encounters (eg, Chess, Poker …

Reward shaping is a well-known technique applied to help reinforcement-learning agents
converge more quickly to near-optimal behavior. In this paper, we introduce\emph {social …

Social dilemmas have attracted extensive interest in the research of multiagent systems in
order to study the emergence of cooperative behaviors among selfish agents …