Agent Based Approach in Disaster Rescue Simulation - From Test-Bed of Multiagent System to Practical Application

Takahashi, Tomoichi; Tadokoro, Satoshı; Ohta, Masayuki; Ito, Nobuhiro

doi:10.1007/3-540-45603-1_11

Cited by 21 publications

(16 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the years simulation designers have used various methods for setting human-like behavior in the agents they developed (EDAs). These include, among other methods, statistical-data based modeling [19], pre-specification of agents' roles using a set of parameters according to which the agents act [20], using pre-defined events and reactions [21], defining a number of basic behaviors from which all of the agents' more complex behaviors are constructed [22,23] or using a combination of rules and finite state machines to control an agent's behavior using a layered approach [24]. The main advantages of using EDAs for simulation purposes (compared to recruiting people) are their capabilities of interacting among themselves and scale.…”

Section: Related Workmentioning

confidence: 99%

Agent development as a strategy shaper

Elmalech

Sarne

Agmon

2015

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

This paper studies to what extent agent development changes one's own strategy. While this question has many general implications it is of special interest to the study of peer designed agents (PDAs), which are computer agents developed by non-experts. This latter emerging technology, has been widely advocated in recent literature for the purpose of replacing people in simulations and investigating human behavior. Its main premise is that strategies programmed into these agents reliably reflect, to some extent, the behavior used by their programmers in real life. We show that PDA development has an important side effect that has not been addressed to date-the process that merely attempts to capture one's strategy is also likely to affect the developer's strategy. This result has many implications concerning the appropriate design of PDA-based simulations as well as the validity of using PDAs for studying individual decision making. The phenomenon is demonstrated experimentally, using two very different application domains and several performance measures. Our findings suggest that the effects on one's strategy arise both in situations where it is potentially possible for people to reason about the optimal strategy (in which case PDA development will enhance the use of an optimal strategy) and in those where calculating the optimal strategy is computationally challenging (in which case PDA development will push people to use more effective strategies, on average). Since in our experiments PDA development actually improved the developer's strategy, PDA development can be suggested as a means for improving people's problem solving skills. Finally, we show that the improvement achieved in people's strategies through agent development is not attributed to the expressive aspect of agent development per-se but rather there is a crucial additional gain in the process of designing and programming ones strategy into an agent.

show abstract

Section: Related Workmentioning

confidence: 99%

Agent development as a strategy shaper

Elmalech

Sarne

Agmon

2015

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

show abstract

“…The rescue teams are agents that can take actions against disastrous situations. They can sense the environment, interact with other agents, and plan the next actions according to their objectives, such as searching for victims, rescuing a buried site, calling for cooperation and so on [23]. as the input that agents receive and the outputs that they produce [28].…”

Section: Description Of Multi-agent Modelmentioning

confidence: 99%

“…Different from physical phenomena, we cannot experience landslides repeatedly to collect data that show some relationship between the parameters of rescue operations and the rescue efficiency [23]. Thus we had interviewed some first responders and experts who specialize in on-site search and rescue for advice before we built the conceptual model.…”

Section: Verification and Validationmentioning

confidence: 99%

Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

et al. 2017

View full text Add to dashboard Cite

Abstract:In this paper, we optimize the search and rescue (SAR) in disaster relief through agent-based simulation. We simulate rescue teams' search behaviors with the improved Truncated Lévy walks. Then we propose a cooperative rescue plan based on a distributed auction mechanism, and illustrate it with the case of landslide disaster relief. The simulation is conducted in three scenarios, including "fatal", "serious" and "normal". Compared with the non-cooperative rescue plan, the proposed rescue plan in this paper would increase victims' relative survival probability by 7-15%, increase the ratio of survivors getting rescued by 5.3-12.9%, and decrease the average elapsed time for one site getting rescued by 16.6-21.6%. The robustness analysis shows that search radius can affect the rescue efficiency significantly, while the scope of cooperation cannot. The sensitivity analysis shows that the two parameters, the time limit for completing rescue operations in one buried site and the maximum turning angle for next step, both have a great influence on rescue efficiency, and there exists optimal value for both of them in view of rescue efficiency.

show abstract

“…ABM is very useful in capturing interactions at a macro scale coming from the way agents behave at a micro level. This intrinsic expressive power makes it a proven solution to explore complex real-world scenarios, such as disaster rescue [2], ancient societies resilience [3], epidemiology [4], and economic analysis [5].…”

Section: Introductionmentioning

confidence: 99%

Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models

Pellegrini

Montañola‐Sales²,

Quaglia

et al. 2017

Euro-Par 2016: Parallel Processing Workshops

View full text Add to dashboard Cite

Abstract. Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs' interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models.

show abstract

Agent Based Approach in Disaster Rescue Simulation - From Test-Bed of Multiagent System to Practical Application

Cited by 21 publications

References 1 publication

Agent development as a strategy shaper

Agent development as a strategy shaper

Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models

Contact Info

Product

Resources

About