RoboCup Rescue: search and rescue in large-scale disasters as a domain for autonomous agents research

Kitano, Hiroaki; Tadokoro, Satoshı; Noda, Itsuki; Matsubara, Hitoshi; Takahashi, Tomoichi; Shinjou, A.; Shimada, Shinichi

doi:10.1109/icsmc.1999.816643

Cited by 218 publications

(189 citation statements)

References 2 publications

Supporting

Mentioning

188

Contrasting

Unclassified

Order By: Relevance

“…The rescue agent competition aims to simulate large-scale disasters such as earthquakes and explore new ways of autonomous coordination of heterogeneous rescue teams under adverse conditions (Kitano et al 1999;Tadokoro et al 2000). This competition was first demonstrated during RoboCup 2000 and was later launched as an official competition in 2001.…”

Section: Agent Competitionmentioning

confidence: 99%

RoboCup Rescue Robot and Simulation Leagues

et al. 2013

View full text Add to dashboard Cite

show abstract

Section: Agent Competitionmentioning

confidence: 99%

RoboCup Rescue Robot and Simulation Leagues

et al. 2013

View full text Add to dashboard Cite

show abstract

“…In order to empirically validate our approach, we have applied RMTDP for allocation in BDI teams in two concrete domains: mission rehearsal simulations [38] and RoboCupRescue [21]. We first present the (significant) speed-up gained by our three interactions mentioned above.…”

Section: Introductionmentioning

confidence: 99%

“…This section first describes the two domains that we consider in this paper: an abstract mission rehearsal domain [38] and the RoboCupRescue domain [21]. Each domain requires us to allocate roles to agents in a team.…”

Section: Introductionmentioning

confidence: 99%

“…This paper focuses on the the quantitative evaluation of multiagent teamwork, to provide feedback to aid human developers and possibly to agents participating in a team, on how the team performance in complex domains can be improved. Such quantitative evaluation is especially vital in domains like disaster rescue [21] and mission rehearsal simulations [38], where the performance of the team is linked to important metrics such as loss of human life and property. Both these and other such complex domains exhibit uncertainty, which arises from partial observability and non-determinism in the outcomes of actions.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, in mission rehearsal simulations [38], we need to select the numbers and types of helicopter agents to allocate to different roles in the team. Similarly, in disaster rescue [21], role allocation refers to allocating fire engines and ambulances to fires and it can greatly impact team performance. In such domains, the role allocation chosen directly impacts the team performance, which is linked to metrics like loss of human life and property; and thus, it is critical to find the best role allocation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach

Nair

Tambe

2005

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative for the agents to be able to reason about the rewards (and costs) for their actions in the presence of uncertainty. However, finding the optimal distributed POMDP policy is computationally intractable (NEXPComplete). This paper is focussed on a principled way to combine the two dominant paradigms for building multiagent team plans, namely the "belief-desireintention" (BDI) approach and distributed POMDPs. In this hybrid BDI-POMDP approach, BDI team plans are exploited to improve distributed POMDP tractability and distributed POMDP-based analysis improves BDI team plan performance. Concretely, we focus on role allocation, a fundamental problem in BDI teams -which agents to allocate to the different roles in the team. The hybrid BDI-POMDP approach provides three key contributions. First, unlike prior work in multiagent role allocation, we describe a role allocation technique that takes into account future uncertainties in the domain. The second contribution is a novel decomposition technique, which exploits the structure in the BDI team plans to significantly prune the search space of combinatorially many role allocations. Our third key contribution is a significantly faster policy evaluation algorithm suited for our BDI-POMDP hybrid approach. Finally, we also present experimental results from two domains: mission rehearsal simulation and RoboCupRescue disaster rescue simulation. In the RoboCupRescue domain, we show that the role allocation technique presented in this paper is capable of performing at human expert levels by comparing with the allocations chosen by humans in the actual RoboCupRescue simulation environment.

show abstract

Agent‐Based Simulations for Disaster Rescue Using the DEFACTO Coordination System

Marecki

Schurr

Tambe

2005

Emergent Information Technologies and Enabling Policies for Counter‐Terrorism

View full text Add to dashboard Cite

When addressing terrorist threats we must give special attention to both prevention and disaster response. Enabling effective interactions between agent teams and humans for disaster response is a critical area of research, with encouraging progress in the past few years. However, previous work suffers from two key limitations: (i) limited human situational awareness, reducing human effectiveness in directing agent teams and (ii) the agent team's rigid interaction strategies that limit team performance. This paper focuses on a novel disaster response software prototype, called DEFACTO (Demonstrating Effective Flexible Agent Coordination of Teams through Omnipresence). DEFACTO is based on a software proxy architecture and 3D visualization system, which addresses the two limitations described above.First, the 3D visualization interface enables human virtual omnipresence in the environment, improving human situational awareness and ability to assist agents. Second, generalizing past work on adjustable autonomy, the agent team chooses among a variety of "team-level" interaction strategies, even excluding humans from the loop in extreme circumstances.

show abstract

RoboCup Rescue: search and rescue in large-scale disasters as a domain for autonomous agents research

Cited by 218 publications

References 2 publications

RoboCup Rescue Robot and Simulation Leagues

RoboCup Rescue Robot and Simulation Leagues

Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach

Agent‐Based Simulations for Disaster Rescue Using the DEFACTO Coordination System

Contact Info

Product

Resources

About