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Exogenous Rewards for Promoting Cooperation in Scale-Free Networks
The design of mechanisms that encourage pro-social behaviours in populations of self-regarding agents is recognised as a major theoretical challenge within several areas of social, life and engineering sciences.
Clustering
Computer Science and Game Theory
Multiagent Systems
Social and Information Networks
Theoretical Economics
Physics and Society
Artificial Intelligence Development Races in Heterogeneous Settings
Regulation of advanced technologies such as Artificial Intelligence (AI) has become increasingly important, given the associated risks and apparent ethical issues.
Social Diversity Reduces the Complexity and Cost of Fostering Fairness
Institutions and investors are constantly faced with the challenge of appropriately distributing endowments.
Co-evolution of Social and Non-Social Guilt
Resorting to methods from evolutionary game theory, we study analytically, and through extensive numerical and agent-based simulations, whether and how such social and non-social guilt can evolve and deploy, depending on the underlying structure of the populations, or systems, of agents.
Fairness and Deception in Human Interactions with Artificial Agents
Of the many opportunities and challenges this presents, the capacity for artificial agents to shape individual and collective human decision-making in such environments is of particular importance.
Trust AI Regulation? Discerning users are vital to build trust and effective AI regulation
We then consider an alternative solution, where users can condition their trust decision on the effectiveness of the regulators.
