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—Problem: This paper addresses a centralized scheduling problem in multi-agent systems in which the incident commander (IC) of a disaster-response team aims to coordinate the actions of the field units (rational agents) to minimize the total operation time in uncertain, dynamic, and spatial environments. Objective: The purpose of this paper is to propose an intelligent software system that assists the IC in the dynamic assignment of geospatial-temporal macro tasks to agents under human strategic decisions. This system autonomously executes a heuristic algorithm to minimize the maximum total dependent duration according to human high-level strategies. Results: The result is a schedule composed of macro decisions, each comprised of seven types of information: 1) what task type is going to be accomplished, 2) who (a subset of agents) are assigned to this assignment, 3) where this task is to be performed (a road segment or zone as a macro geospatial object) containing a subset of tasks, 4) when operations start, 5) when operations finish, 6) how many tasks are estimated to be completed, 7) what task types and the estimated number to be revealed (identified " or " enabled) in this location to complete this job. Conclusion: This result, which is a feasible solution for the addressed problem, permits the IC to coordinate agents, partially specify the activities of the agents in time and space, minimize the overall execution time for all the tasks, calculate the correct time to revise the strategic decisions, evaluate the efficiency of the high-level strategy, and estimate the makespan.

Dynamic Assignment of Geospatial-Temporal Macro Tasks to Agents under Human Strategic Decisions for Centralized Scheduling in Multi-Agent Systems