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Adaptive Multiple Resources Consumption Control for an Autonomous Rover
TLDR
A new state space representation for multiple consumable resources, which is compact and has suitable access time is presented and obtained via a Markov decision process that is solved off-line. Expand
Distributed Decision-Theoretic Active Perception for Multi-robot Active Information Gathering
TLDR
This paper proposes a distributed decision process where a robot maintains a belief matrix representing its beliefs and beliefs about the beliefs of the other robots to access the relevance of their beliefs and the divergence with each other. Expand
A Decision-Theoretic Scheduling of Resource-Bounded Agents in Dynamic Environments
TLDR
It is claimed that it is possible to dynamically compute good decisions without completely calculating the optimal policy in the dynamic optimisation of resource allocation to a changing set of tasks. 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
Discrete relative states to learn and recognize goals-based behaviors of groups
TLDR
The proposed algorithms achieve the detection of the dangerous person in the crowd, in order to raise an alert and also predict casualties by identifying which groups did not notice the threat and were found more precise and more tolerant to noisy observations. Expand
Meta-level control under uncertainty for handling multiple consumable resources of robots
TLDR
An approach to control the operation of an autonomous rover which operates under multiple resource constraints by combining decomposition of a large MDP into smaller ones, compression of the state space by exploiting characteristics of the multiple resources constraint, construction of local policies for the decomposed MDPs using state space discretization and resource compression, and recomposition of the local policies to obtain a near optimal global policy. Expand
Unknown Area Exploration with an Autonomous Robot using Markov Decision Processes
This paper addresses the problem of exploration of an unknown area by an autonomous robot. The robot decides at each step where it has to move, without any human intervention. The Goal is to gatherExpand
A Distributed Decision-Theoretic Model for Multiagent Active Information Gathering
TLDR
A distributed decision process where a robot maintains a belief matrix representing its beliefs and beliefs about the beliefs of the other robots is proposed, which allows the derivation of a policy for gathering information to make the entropy low and a communication policy to reduce the di-vergence. Expand
Dealing With Groups of Actions in Multiagent Markov Decision Processes
TLDR
This paper adapts H-(PO)MDPs to multi-agent settings by proposing a new approach using action groups to decompose an initial MMDP into a set of dependent Sub-MMDPs where each action group is assigned a corresponding Sub- MMDP. Expand
Navigation Method Selector for an Autonomous Explorer Rover with a Markov Decision Process
TLDR
An automatic navigation method selector using Markov Decision Process (MDP) framework is proposed and Navigation method are modelized in the MDP transitions functions. Expand
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