Swarm behavior systems involves creating systems that mimic the collective behavior of social creatures like ants or bees to solve complex problems. These systems are composed of numerous decentralized, self-organized agents that interact with each other and their environment, leading to emergent, global behavior. This approach is particularly useful in situations where centralized control is difficult or inefficient, such as in robotics, optimization, and resource allocation.
In this thesis we will explore swarm behavior algorithms in heterogeneous application environments, that is, the exploration of swarm systems in which the members of the swarm have different responsabilities and capabilities, as well as environments in which the capabilities between members can be exchanged, shared, or given.
For the implementation of the algorithms we will strive to use Elixir for the swarm behavior algorithms and their heterogeneous communication of capabilities