In a nutshell, this book treats the methods, structures, and cases on the representation(s) of the environment in multi-agent systems. The individual agents in the systems are based on the Interactivist-Expectative Theory of Agency and Learning (IETAL). During their sojourn in the environment, the agents interact with it and build their intrinsic representation of it. The interagent communication is solved via imitation conventions of the homogenous agents. Due to the specific interrelation of the drives, motivations, and actions, a multitude of fuzzy structures is used as a base for the formalization of the theory. Original results in the Theory of Fuzzy Graphs, and Fuzzy Algebraic Structures, valued by lattices, posets, and relational structures are also given. Algorithms for detection of the learnability of the environment are given, as well as a discussion on the concept of context within this theory. The phenomenology of the drives and percepts as well as of the imitation is surveyed in detail. Solution of the interagent communication and of the emergence of language in the system is also discussed.
The original experiments with humans investigate the status of some key notions of our theories in human subjects. We also present a variety of hardware and software solutions that have served us in our research and that are flexible enough to serve other researchers in similar experiments, whether they are of simulation nature, emulations on robotic agents, or based on harvesting data from human individuals or groups. In our discussions we focus on important biological concepts from humans that our theories are based on. We discuss actions, motivations, and drives in human subjects, explore the concept formation in related literature, and give our own take on it, as that serves as the base of our discussion on emergence of language in our artificial societies.