Designing an agent that is capable of interacting with another agent is an open problem. An interaction happen when two or more agents perform an action in an environment and they obtain an utility based on the performed joint action.Current multiagent learning techniques do not fare well with agents that change their behavior during a repeated interaction. This happens because they usually do not model the other agents’ behavior and instead make some assumptions that for real scenarios are too restrictive. Furthermore, considering that many applications demand different types of agents to work together this should be an important problem to solve. It does not matter if the domain is cooperative (where agents have a common goal) or competitive (where objectives are different), there is one common aspect: agents must learn how their counterpart is acting and react quickly to changes in behavior.