We present mechanisms, architectures, and an implementation addressing challenges with mobile opportunistic commerce centering on markets and mechanisms that support the procureme...
The problem of optimal policy formulation for teams of resource-limited agents in stochastic environments is composed of two strongly-coupled subproblems: a resource allocation pr...
We explore settings where a principal must make a decision about which action to take to achieve a desired outcome. The principal elicits the probability of achieving the outcome ...
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
We propose Path Disruption Games (PDGs), which consider collaboration between agents attempting stop an adversary from travelling from a source node to a target node in a graph. P...