Corpus ID: 17303773

A Distributed Decision-Theoretic Model for Multiagent Active Information Gathering

@inproceedings{Renoux2014ADD,
  title={A Distributed Decision-Theoretic Model for Multiagent Active Information Gathering},
  author={Jennifer Renoux and A. Mouaddib and Simon Le Gloannec},
  booktitle={MDAI 2014},
  year={2014}
}
Multirobot systems have made tremendous progress in ex-ploration and surveillance. In that kind of problem, agents are not required to perform a given task but should gather as much information as possible. However, information gather-ing tasks usually remain passive. In this paper, we present a multirobot model for active information gathering. In this model, robots explore, assess the relevance, update their be-liefs and communicate the appropriate information to rel-evant robots. To do so… Expand
A decision-theoretic planning approach for multi-robot exploration and event search
TLDR
A distributed decision-theoretic model called MAPING (Multi-Agent Planning for INformation Gathering), in which each agent computes a communication and an exploration strategy by assessing the relevance of an observation for another agent, and includes a forgetting mechanism to ensure that the event-exploration remains open-ended. Expand
Contribution to multiagent planning for active information gathering. (Contribution à la planification multiagent pour la perception active)
TLDR
A new fully decentralized model of multiagent planning for information gathering, called MAPING (Multi-Agent Planning for INformation Gathering), the agents use an extended belief state that contains not only their own beliefs but also approximations of other agents’ beliefs. Expand

References

SHOWING 1-10 OF 32 REFERENCES
Coordinated Multi-Robot Exploration Under Communication Constraints Using Decentralized Markov Decision Processes
TLDR
This paper extends the DVF methodology to address full local observability, limited share of information and communication breaks and applies it in a real-world application consisting of multi-robot exploration where each robot computes locally a strategy that minimizes the interactions between the robots and maximizes the space coverage of the team even under communication constraints. Expand
Reasoning about joint beliefs for execution-time communication decisions
TLDR
This paper presents an approach that generates "centralized" policies for multi-agent POMDPs at plan-time by assuming the presence of free communication, and at run-time, handles the problem of limited communication resources by reasoning about the use of communication as needed for effective execution. Expand
Formal models and algorithms for decentralized decision making under uncertainty
TLDR
Five different formal frameworks, three different optimal algorithms, as well as a series of approximation techniques are analyzed to provide interesting insights into the structure of decentralized problems, the expressiveness of the various models, and the relative advantages and limitations of the different solution techniques. Expand
Decentralized MDPs with sparse interactions
TLDR
A new decision-theoretic model for decentralized sparse-interaction multiagent systems, Dec-SIMDPs, is contributed that explicitly distinguishes the situations in which the agents in the team must coordinate from those in which they can act independently. Expand
POMDP-based online target detection and recognition for autonomous UAVs
TLDR
Experimental results are presented, which demonstrate that Artificial Intelligence techniques like POMDP planning can be successfully applied in order to automatically control perception and mission actions hand-in-hand for complex time-constrained UAV missions. Expand
Memory-Bounded Dynamic Programming for DEC-POMDPs
TLDR
This work presents the first memory-bounded dynamic programming algorithm for finite-horizon decentralized POMDPs, which can handle horizons that are multiple orders of magnitude larger than what was previously possible, while achieving the same or better solution quality. Expand
Active cooperative perception in network robot systems using POMDPs
  • M. Spaan, Tiago Veiga, P. Lima
  • Engineering, Computer Science
  • 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
  • 2010
TLDR
This work shows how to model a typical cooperative perception task in a NRS, namely tracking and classifying people, and presents experiments that show how the proposed approach results in an effective interplay between robot and environment sensors. Expand
MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs
TLDR
This work presents multi-agent A* (MAA*), the first complete and optimal heuristic search algorithm for solving decentralized partially-observable Markov decision problems (DECPOMDPs) with finite horizon, and introduces an anytime variant of MAA*. Expand
The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models
TLDR
A unified framework for multiagent teamwork, the COMmunicative Multiagent Team Decision Problem (COM-MTDP), which combines and extends existing multiagent theories, and provides a basis for the development of novel team coordination algorithms. Expand
Brick& Mortar: an on-line multi-agent exploration algorithm
TLDR
In the experimental evaluation, Brick&Mortar significantly outperforms the competing algorithms, namely ants and multiple depth first search, in terms of exploration time and the observed performance benefits suggest that the algorithm is suitable for safety-critical applications that require rapid area coverage for real-time event detection and response. Expand
...
1
2
3
4
...