3 citations · 3 across the 1 of their papers we have counts for
5 papers
Modelling Cooperation in Network Games with Spatio-Temporal Complexity
Michiel A. Bakker, Richard Everett, Laura Weidinger +4
The real world is awash with multi-agent problems that require collective action by self-interested agents, from the routing of packets across a computer network to the management…
Negotiating Team Formation Using Deep Reinforcement Learning
Yoram Bachrach, Richard Everett, Edward Hughes +6
When autonomous agents interact in the same environment, they must often cooperate to achieve their goals. One way for agents to cooperate effectively is to form a team, make a bin…
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences
Raphael Köster, Kevin R. McKee, Richard Everett +7
Game theoretic views of convention generally rest on notions of common knowledge and hyper-rational models of individual behavior. However, decades of work in behavioral economics…
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus
Adam D. Cobb, Richard Everett, Andrew Markham +1
In systems of multiple agents, identifying the cause of observed agent dynamics is challenging. Often, these agents operate in diverse, non-stationary environments, where models re…
Inferring agent objectives at different scales of a complex adaptive system
Dieter Hendricks, Adam Cobb, Richard Everett +2
We introduce a framework to study the effective objectives at different time scales of financial market microstructure. The financial market can be regarded as a complex adaptive s…