Decentralized MDPs provide powerful models of interactions in multi-agent environments, but are often very difficult or even computationally infeasible to solve optimally. Here we...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
The TAC Supply Chain Management (TAC/SCM) game presents a challenging dynamic environment for autonomous decision-making in a salient application domain. Strategic interactions co...
Patrick R. Jordan, Christopher Kiekintveld, Michae...
Calling context enhances program understanding and dynamic analyses by providing a rich representation of program location. Compared to imperative programs, objectoriented program...
As new attacks against Windows-based machines emerge almost on a daily basis, there is an increasing need to “lock down” individual users’ desktop machines in corporate comp...