In the empirical approach to game-theoretic analysis (EGTA), the model of the game comes
not from declarative representation, but is derived by interrogation of a procedural …

The advent of large-scale distributed systems poses unique engineering challenges. In
open systems such as the internet it is not possible to prescribe the behaviour of all of the …

Wicked problems like sustainable energy and financial market stability are societal
challenges that arise from complex sociotechnical systems in which numerous social …

Progress in machine learning is measured by careful evaluation on problems of outstanding
common interest. However, the proliferation of benchmark suites and environments …

E-commerce increasingly provides opportunities for autonomous bidding agents: computer
programs that bid in electronic markets without direct human intervention. Automated …

Multiagent reinforcement learning (MARL) has benefited significantly from population-based
and game-theoretic training regimes. One approach, Policy-Space Response Oracles …

In multi-issue automated negotiation against unknown opponents, a key part of effective
negotiation is the choice of concession strategy. In this paper, we develop a principled …

Many enterprises that participate in dynamic markets need to make product pricing and
inventory resource utilization decisions in real time. We describe a family of statistical …

Evaluating deep multiagent reinforcement learning (MARL) algorithms is complicated by
stochasticity in training and sensitivity of agent performance to the behavior of other agents …

Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none
scale to normal-form games with many actions and many players, especially those with …