5 accepted papers
Cooperation among independent learning agents is desirable as it enables reaching collectively rewarding states. Recent work has shown that artificial agents can learn to act pro-socially without the need for predefined cooperative preferences or behavioural heuristics, provided that they can observ
Agents often have individual goals which depend on a group's actions. If agents trust a forecast of collective action and adapt strategically, such prediction can influence outcomes non-trivially, resulting in a form of performative prediction. This effect is ubiquitous in scenarios ranging from pan…
Altruistic cooperation is costly yet socially desirable. As a result, agents struggle to learn cooperative policies through independent reinforcement learning (RL). Indirect reciprocity, where agents consider their interaction partner’s reputation, has been shown to stabilise cooperation in homogene…
Meeting today’s major scientific and societal challenges requires understanding the dynamics of cooperation, coordination, and conflict in complex adaptive systems (CAS). Artificial Intelligence (AI) is intimately connected with these challenges, both as an application domain and as a source of new…
Given the ubiquity of AI-based decisions that affect individuals’ lives, providing transparent explanations about algorithms is ethically sound and often legally mandatory. How do individuals strategically adapt following explanations? What are the consequences of adaptation for algorithmic accuracy…