Mice are social animals and the social context affects their behavior and learning: in isolation only some prosocial behaviors are expressed. One approach to account for the social effects on behavior is to use intelligent cages, such as the Intellicage studied here, which facilitate studies of mice cohorts in a more ecological setting. This contextual advantage is countered by challenges to analyze data in a way to extract group interactions. Often these systems are used only to increase throughput of phenotypization under an assumption that the mice are, in fact, behaving independently. Unless the social effects on the studied behavior are particularly apparent they are often ignored.Here we propose a new conceptual, analytical and computational framework combining point processes with reinforcement learning models for the description, analysis and modeling of individual and group effects of mice learning in the Intellicages. We show that the observed mice behavior in the Intellicage can be naturally described in the language of marked point processes. We demonstrate how different reinforcement models of the behavior, including group effects, can be studied effectively in this framework, using example experiments. With this framework we show strong evidence of subtle social effects on wild type mice learning in Intellicages on top of learning strategies used by each mouse in the studied cohort.