Biomedical subjects
J E Burgos
Publications and source records attributed to J E Burgos.
The S-R issue: its status in behavior analysis and in Donahoe and Palmer's learning and complex behavior.
The central focus of this essay is whether the effect of reinforcement is best viewed as the strengthenng of responding or the strengthening of the environmental control of responding. We make the argument that adherence to Skinner's goal of achieving a moment-to-moment analysis of behavior compels acceptance of the latter view. Moreover, a thoroughgoing commitment to a moment-to-moment analysis undermines the fundamental distinction between the conditioning process instantiated by operant and respondent contingencies while buttressing the crucially important differences in their cumulative outcomes. Computer simulations informed by experimental analyses of behavior and neuroscience are used to illustrate these points.
A selectionist approach to reinforcement.
We describe a principle of reinforcement that draws upon experimental analyses of both behavior and the neurosciences. Some of the implications of this principle for the interpretation of behavior are explored using computer simulations of adaptive neural networks. The simulations indicate that a single reinforcement principle, implemented in a biologically plausible neural network, is competent to produce as its cumulative product networks that can mediate a substantial number of the phenomena generated by respondent and operant contingencies. These include acquisition, extinction, reacquisition, conditioned reinforcement, and stimulus-control phenomena such as blocking and stimulus discrimination. The characteristics of the environment-behavior relations selected by the action of reinforcement on the connectivity of the network are consistent with behavior-analytic formulations: Operants are not elicited but, instead, the network permits them to be guided by the environment. Moreover, the guidance of behavior is context dependent, with the pathways activated by a stimulus determined in part by what other stimuli are acting on the network at that moment. In keeping with a selectionist approach to complexity, the cumulative effects of relatively simple reinforcement processes give promise of simulating the complex behavior of living organisms when acting upon adaptive neural networks.