Microslip as a Simulated Artificial Mind

Authors:
Yuta Ogai;Takashi Ikegami
Affiliations:
Department of General Systems Sciences, Graduate Schoolof Arts and Sciences, University of Tokyo, Japan;Department of General Systems Sciences, Graduate Schoolof Arts and Sciences, University of Tokyo, Japan
Venue:
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Year:
2008

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Abstract

A microslip is a type of action hesitation we experience in everyday life, which highlights the gap between human action and machine action patterns. By proposing a simple computational model for microslips, we examine the microslip as an implicit parallel dynamics underneath human cognition. Here, an agent, given as a dynamical system of a simple neural architecture, takes one of two choices, whose neural net is evolved using a genetic algorithm. An evolved agent often shows a hierarchy of action primitives and intentionality, and the agent is sensitive to the subtle differences of the object's layout, which results in a complex basin structures in the action-selection landscape.