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Reactive Layer in AGI Agent - Implementation of Adaptive Reactive Behavior and Beyond

Basic mechanisms of cognition working in AGI agent are presented. I argue that reactive behavior is the baseline of intelligence – it is the base component working and it can be further extended to produce more intelligent agents. Mechanisms employed at reactive level enable the agent to develop behavior which both explores and exploits the environment with the purpose of receiving highest reward possible. Three fundamental mechanisms are intertwined – action selection, action value estimation and situation discrimination. Whole process of adaptation is completely unsupervised and depends only on reward received from environment. Some technical details of implementation of given mechanisms (BAGIB agent) are described together with implications to other planned parts of “AGI-compliant” architecture. Discussed are several challenges we encounter in AGI, which are not present in usually narrow and domain-limited approach to AI.