3. Partial Reinforcement Theory

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About this Lecture

Lecture

In this lecture, we think about partial reinforcement theory, focusing in particular on: (i) the dramatic economic fallout from gambling addiction; (ii) the process of simple reinforcement, whereby a single behaviour can be encouraged by rewarding its presence; (iii) gambling machines’ usage of partial variable reinforcement by only rewarding the gambler periodically; (iv) the differentiated response to repeated losing, either being to walk away from the loss or to keep playing, with the expectation that a win will be soon.

Course

In this course, Dr Ashok Jansari (Goldsmiths, University of London) explores non-substance addictions, specifically gambling addiction. In the first lecture, we think about how addiction can be described and defined as a concept. In the second lecture, we think about some of the risk factors for developing an addiction. In the third lecture, we think about how gambling machines use partial variable reinforcement, which can generate an addiction. Next, we think about some of the cognitive biases which can lead to addictive behaviour, including the near miss bias, the recall bias, and the gambler’s fallacy. In the fifth and final lecture, we think about some patterns which arise in the process of overcoming addiction, specifically looking at Prochaska’s six-stage model of behaviour change.

Lecturer

Dr Ashok Jansari is a senior lecturer in the Department of Psychology at Goldsmiths, University of London. Dr Jansari’s research interests include memory disorders, prosopagnosia, executive functions, and synaesthesia. Dr Jansari is most famous for his research into prosopagnosia, having made numerous TV appearances, including on BBC1’s The One Show, as well as hosting his own ‘Neuro Talk’ YouTube channel:

https://www.youtube.com/c/DrAshokJansariNeuroTalk/featured

Some of Dr Jansari's recent publications include 'Acquired synaesthesia following 2C-B use' (2019), 'Using virtual reality to investigate multitasking ability in individuals with frontal lobe lesions' (2019), and 'Identification from CCTV: Assessing police super-recogniser ability to spot faces in a crown and susceptibility to change blindness' (2018).