Memorias de investigación
Communications at congresses:
LEARNING IN CONSTRAINED STOCHASTIC DYNAMIC POTENTIAL GAMES
Year:2016

Research Areas
  • Game theory,
  • Engineering,
  • Postal and telecommunications services,
  • Processing and signal analysis

Information
Abstract
We extend earlier works on continuous potential games to the most general case: stochastic time varying environment, stochastic rewards, non-reduced form and constrained state-action sets. We provide conditions for a Markov Nash equilibrium (MNE) of the game to be equivalent to the solution of a single control problem. Then, we address the problem of learning this MNE when the reward and state transition models are unknown. We follow a reinforcement learning approach and extend previous algorithms for working with constrained state-action subsets of real vector spaces. As an application example, we simulate a network flow optimization model, in which the relays have batteries that deplete with a random factor. The results obtained with the proposed framework are close to optimal.
International
Si
Congress
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
970
Place
Shanghai, China
Reviewers
Si
ISBN/ISSN
2379-190X
10.1109/ICASSP.2016.7472542
Start Date
20/03/2016
End Date
25/05/2017
From page
1
To page
5
Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Aplicaciones del Procesado de Señal (GAPS)
  • Centro o Instituto I+D+i: Centro de I+d+i en Procesado de la Información y Telecomunicaciones
  • Departamento: Señales, Sistemas y Radiocomunicaciones