Banca de DEFESA: LUCILEIDE MEDEIROS DANTAS DA SILVA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE : LUCILEIDE MEDEIROS DANTAS DA SILVA
DATA : 18/11/2016
HORA: 09:30
LOCAL: Auditório do nPITI
TÍTULO:

Proposal of Q-learning Reinforcement Learning Technique in FPGA

PALAVRAS-CHAVES:

FPGA, Q-learning, Reinforcement Learning, Hardware.

PÁGINAS: 75
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
SUBÁREA: Circuitos Elétricos, Magnéticos e Eletrônicos
ESPECIALIDADE: Circuitos Eletrônicos
RESUMO:

Q-learning is a off-policy reinforcement learning technique which has as main advantage the possibility of obtaining an optimal policy interacting with an unknown model environment. This work proposes a parallel fixed-point Q-learning algorithm architecture, implemented in FPGA. Fundamental to this approach is optimize system processing time. Convergence results are presented. The processing time and occupied area were analyzed for different scenarios and various fixed point formats. Architecture implementation details were featured. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.

MEMBROS DA BANCA:
Presidente - 1837240 - MARCELO AUGUSTO COSTA FERNANDES
Interno - 347628 - ADRIAO DUARTE DORIA NETO
Externo ao Programa - 350241 - JORGE DANTAS DE MELO
Externo ao Programa - 347065 - JOSE ALBERTO NICOLAU DE OLIVEIRA
Externo à Instituição - ALISSON VASCONCELOS DE BRITO - UFPB