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Intelligent Algorithm for Assignment of Agents to Human Strategy in Centralized Multi-agent Coordination

Reza Nourjou, Stephen F. Smith, Michinori Hatayama, Pedro Szekely

发表年份
2014
引用次数
10

摘要

Problem: Multi-agent coordination is an important issue in the domain of disaster emergency response operations where a team of agents (field units or robots) aims to achieve a joint objective. The responsibility of the Incident Commander (IC) is to (I) specify an effective strategy composed of a number of threads (a set of prioritized sub-problems), (II) appropriately assign/allocate agents to these threads as a strategic decision, and (III) release agents in a timely manner from the assigned threads to adapt a strategic decision to a new situation. Objective: The purpose of this paper is to present an intelligent algorithm that assists a human in multi-agent coordination by providing two key functions: 1) automatically calculate and present a set of feasible alternatives for selecting a choice as a strategic decision in a definite time, and 2) autonomously and in a timely manner identify a subset of assigned agents that should be released from their threads in order to refine a strategic decision. Method: This algorithm expands a decision tree from a state node in which a thread (or several threads) has received a set of new agents from either the IC or a higher thread. Each thread is associated with one level of a decision tree with a number of nodes. A thread calculates a set of efficient coalitions using all the available agents and generates a new node for each coalition to show what agents are allocated to the thread and what agents are released into a lower thread. In real-time, this algorithm continuously observes and monitors the task environment to identify a subset of the assigned agents that cannot provide efficient capabilities for their threads and should be released for assignment to other threads. Results: To gather further insight, this paper applied this algorithm for team coordination to a simulated search & rescue scenario in an earthquake disaster-affected area where the team's goal was to rescue trapped people distributed in five operational zones. The result was an infinite set of alternative scenarios for a human-defined strategy. The calculated alternatives were presented to the IC for selection according to his intuition or for delegation to the system to determine an optimal strategy.

关键词

Computer scienceDistributed computingIntelligent agentAlgorithmArtificial intelligence

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