Displaying 2 of 2 results Multi-Agent eXperimenter clear
We are looking for a new permanent team mate in trustworthy multi-agent systems.
The objective of this thesis is to investigate the uncertain constraints of blockchain systems and to propose a deep reinforcement learning decision-making approach based on utility and rewards for both user and block creator agents.
The thesis will also contribute to develop and extend the agent-based simulation platform Multi-Agent eXperimenter (MAX) of LICIA.