Hormonal Modulation of Perception in Motivation-Based Action Selection Architectures

The animat approach to artificial intelligence proposes biologically-inspired control mechanisms for autonomous robots. One of the related subproblems is action selection or “what to do next”. Many action selection architectures have been proposed. Motivation-based architectures implement a combination between internal and external stimuli to choose the appropriate behavior. Recent studies have pointed out that a second order mechanism to control motivation-based architectures would improve dramatically their performance. Drawing on the notion of biological hormones we have modeled two of the functionalities ascribed to them in order to improve the adaptivity of motivation-based architectures. We have tested our “hormone-like” mechanisms in dynamic and unpredictable robotic scenarios. We analyze the results in terms of interesting behavioral phenomena that emerge from the interaction of these artificial hormones with the rest of architectural elements.