AbstractCommonsense and theorizing about action control agree in assuming that human behavior is (mainly) driven by goals, but no mechanistic theory of what goals are, where they come from, and how they impact action selection is available. Here I develop such a theory that is based on the assumption that GOALs guide Intentional Actions THrough criteria (GOALIATH). The theory is intended to be minimalist and parsimonious with respect to its assumptions, as transparent and mechanistic as possible, and it is based on representational assumptions provided by the Theory of Event Coding (TEC). It holds that goal-directed behavior is guided by selection criteria that activate and create competition between event files that contain action-effect codes matching one or more of the criteria—a competition that eventually settles into a solution favoring the best-matching event file. The criteria are associated with various sources, including biological drives, acquired needs (e.g., of achievement, power, or affiliation), and short-term, sometimes arbitrary, instructed aims. Action selection is, thus, a compromise that tries to satisfy various criteria related to different driving forces, which are also likely to vary in strength over time. Hence, what looks like goal-directed action emerges from, and represents an attempt to satisfy multiple constraints with different origins, purposes, operational characteristics, and timescales—which among other things does not guarantee a high degree of coherence or rationality of the eventual outcome. GOALIATH calls for a radical break with conventional theorizing about the control of goal-directed behavior, as it among other things questions existing cognitive-control theories and dual-route models of action control.
Identification of an unconventional process of instrumental learning characteristically initiated with outcome devaluation-insensitivity and generalized action selection
