In this paper, we focus on the problem of finding a periodic allocation strategy for teams of resource-bounded agents. We propose a real-time dynamic algorithm RTDA*, that exploits two key properties to avoid the exponential increase in the state and action spaces associated with multi-agent systems. First, resource allocation at each time period follows an earliest deadline first order (EDF) over agents. Second, the resources are undivided, i.e., the resources allocated to an agent restrict their availability to others over time. We can therefore view each incoming agent as a cyclic individual resource-bounded processing, namely "cyclic progressive reasoning unit" (C-PRU), and solve, off-line, the single agent resource allocation problem. In the on-line phase, our algorithm exploits pre-compiled policies, as heuristic metrics, to build near-optimal joint decisions at each time period.