Searched for: author%3A%22Jarne+Ornia%2C+D.%22
(1 - 6 of 6)
document
Jarne Ornia, D. (author)
Besides facing the same challenges as single-agent systems, the distributed nature of complex multi-agent systems sparks many questions and problems revolving around the constraints imposed by communication. The idea that multi-agent systems require communication to access information, to coordinate or simply to sense the environment they are...
doctoral thesis 2023
document
Adams, S.J.L. (author), Jarne Ornia, D. (author), Mazo, M. (author)
We present a biologically inspired design for swarm foraging based on ant’s pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not require global or relative position measurements and the swarm is fully decentralized and needs no infrastructure in place. Additionally, the system only requires...
journal article 2023
document
Jarne Ornia, D. (author), Mazo, M. (author)
We present an approach to reduce the communication of information needed on a Distributed Q-Learning system inspired by Event Triggered Control (ETC) techniques. We consider a baseline scenario of a Distributed Q-Learning problem on a Markov Decision Process (MDP). Following an event-based approach, N agents sharing a value function explore the...
conference paper 2022
document
Jarne Ornia, D. (author), Zufiria, Pedro J. (author), Mazo, M. (author)
Collaborative multiagent robotic systems, where agents coordinate by modifying a shared environment often result in undesired dynamical couplings that complicate the analysis and experiments when solving a specific problem or task. Simultaneously, biologically inspired robotics rely on simplifying agents and increasing their number to obtain...
journal article 2022
document
Jarne Ornia, D. (author), Mazo, M. (author)
We present an approach to safely reduce the communication required between agents in a Multi-Agent Reinforcement Learning system by exploiting the inherent robustness of the underlying Markov Decision Process. We compute robustness certificate functions (off-line), that give agents a conservative indication of how far their state measurements...
conference paper 2022
document
Jarne Ornia, D. (author), Mazo, M. (author)
Ant Colony algorithms are a set of biologically inspired algorithms used commonly to solve distributed optimization problems. Convergence has been proven in the context of optimization processes, but these proofs are not applicable in the framework of robotic control. In order to use Ant Colony algorithms to control robotic swarms, we present...
conference paper 2020
Searched for: author%3A%22Jarne+Ornia%2C+D.%22
(1 - 6 of 6)