Introduction to spatially distributed intelligent assistant agents for coordination of human-agent teams' actions

Nourjou, Reza; Hatayama, Michinori; Tatano, Hirokazu

doi:10.1109/ssrr.2011.6106748

Cited by 13 publications

(17 citation statements)

References 5 publications

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“…MASs deal with complex systems by emphasizing the interaction between agents and dividing the system into sub-sectors of the environment and other actors [5]. Task allocation plays an important role in coordinating an MAS within a set of agents [6,7]. Appropriate allocations are critical for the efficient implementation of tasks undertaken in natural hazard environments.…”

Section: Introductionmentioning

confidence: 99%

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Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

Hooshangi

Alesheikh

2018

IJGI

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Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR) operations. The present study aimed to develop a dynamic agent-based simulation model in post-earthquake USAR operations using geospatial information system and multi agent systems (GIS and MASs, respectively). We also propose an approach for dynamic task allocation and establishing collaboration among agents based on contract net protocol (CNP) and interval-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, which consider uncertainty in natural hazards information during agents' decision-making. The decision-making weights were calculated by analytic hierarchy process (AHP). In order to implement the system, earthquake environment was simulated and the damage of the buildings and a number of injuries were calculated in Tehran's District 3: 23%, 37%, 24% and 16% of buildings were in slight, moderate, extensive and completely vulnerable classes, respectively. The number of injured persons was calculated to be 17,238. Numerical results in 27 scenarios showed that the proposed method is more accurate than the CNP method in the terms of USAR operational time (at least 13% decrease) and the number of human fatalities (at least 9% decrease). In interval uncertainty analysis of our proposed simulated system, the lower and upper bounds of uncertain responses are evaluated. The overall results showed that considering uncertainty in task allocation can be a highly advantageous in the disaster environment. Such systems can be used to manage and prepare for natural hazards.

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Section: Introductionmentioning

confidence: 99%

“…In traditional USAR models for disaster environments, task allocation is based on consistent information about the environment [7], while USAR is generally on a large scale and involves many uncertainties [10]. Assuming coordination in environments with no uncertainty is essentially an unrealistic scenario [11].…”

Section: Introductionmentioning

confidence: 99%

Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

Hooshangi

Alesheikh

2018

IJGI

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“…To assign spatially distributed tasks to field units (agents) in USAR management, algorithms were suggested by [4,13]. These algorithms involved geographic information and geospatial analyses in the effective assignment of tasks to agents.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They are spatially distributed in a geographic environment. They perceive their local environment, execute strategic decisions made by the top node, rationally make decisions regarding their own actions, coordinate their actions with each other in a distributed approach, execute tasks, and report to the operation center [4]. An IC, located in the top node, has a global and timely view of the entire disaster situation.…”

Section: Introductionmentioning

confidence: 99%

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

Nourjou¹,

Smith²,

Hatayama³

et al. 2014

IJMLC

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Abstract-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.

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“…The C# programming language was used to implement the core of the GICoordinator [2]. The IC is equipped with a computer that runs GICoordinator, and a simple version of this agent has been developed for field units [6].…”

Section: Introductionmentioning

confidence: 99%

Simulation of an Organization of Spatial Intelligent Agents in the Visual C#.NET Framework

Nourjou¹,

Hatayama²

2014

IJCTE

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Abstract-Problem: This paper investigates the simulation of a community of spatial intelligent agents, an important issue for the implementation and evaluation of distributed algorithms. The research question is how to simulate this organization using Visual C#.NET.Objective: This paper intends to use the C# programming language to develop a simulator. In a simulated environment, a social agent needs to communicate with other agents and respond to received messages.Method: Our approach is to integrate the thread and delegate methods provided by the .NET framework. We enhance the architecture of a spatial intelligent agent in order to embed several in a simulated society. A basic C# program is presented to demonstrate how to implement a contract net protocol (CNP) among three simple agents.Results: Two results were achieved: 1) the responses and actions of three agents during a simulated CNP and 2) a simulated environment that contains distributed spatial intelligent agents that can interact with each other and a human user.Conclusion: The proposed methodology and presented code provide a flexible and efficient framework for C# developers to develop, simulate, and evaluate a society of advanced software agents using the .NET platform.

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Introduction to spatially distributed intelligent assistant agents for coordination of human-agent teams' actions

Cited by 13 publications

References 5 publications

Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

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

Simulation of an Organization of Spatial Intelligent Agents in the Visual C#.NET Framework

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