single agent vs multiple agent reinforcement learning
A key difference between RL and MARL arises when you consider that other agents are strategic and their behaviour is adaptive. Game theoretical concepts are very important within the scope of MARL and bring in a new range of issues. From a single agent perspective, the environment is non-stationary as every strategic agent is changing their policies to best respond to the each other.

A good discussion on the challenges of MARL can be found here: 
http://busoniu.net/files/papers/marl_chapter_springer.pdf

Regarding your question:
Yes, you can use a single agent RL as long as the preys are not learning. If you plan to apply RL to every agent (hunter and preys), you will find new issues such as convergence problems, etc. There is a lot of research going on around this. To start I would suggest you have a look at some basic and classic concepts such as Fictitious Play and WoLF (Win or Learn Fast).