Contemporary Animal Learning Theory

By Anthony D. Dickinson. 1981

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Shortcut learning in deep neural networks (2020, background): “phenomenon. Once a predictive cue/feature (say, a light ﬂash) has been associated with an outcome (e.g. food), animals sometimes fail to associate a new, equally predictive cues with the same outcome [42,43,44]. 8 Figure 4. Both human and machine vision generalise, but they generalise very different”
A learning theory perspective on lapse, relapse, and the maintenance of behavior change. (2000, methodology): “These two forms of learning are highly similar (eg, Dickinson, 1980; Mackintosh, 1983; Rescorla, 1987), and although much of what I describe here comes from Pavlovian methods, similar principles apply in the operant case (eg, Bouton & Swartzentruber, 1991).”
Lesions of dorsolateral striatum preserve outcome expectancy but disrupt habit formation in instrumental learning (2004, unknown): “& % # / %# .”
Temporal difference models describe higher-order learning in humans (2004, background): “Most of this work has concentrated on its simplest realization, namely first-order pavlovian fear conditioning; however, the predictions in this paradigm are rudimentary, showing little of the complexities associated with sequences of predictors that are critical in psychological investigations of p”
Uncertainty and Learning (2003, background): “The eld of classical conditioning probes the ways that animals learn predictive relationships in the world, between initially neutral stimuli such as lights and tones, and reinforcers such as food, water or small electric shocks [ 1 , 2]. This sort of learning is obviously a critical adaptive capaci”
Temporal prediction errors in a passive learning task activate human striatum. (2003, background): “This situanimals learn when expectations about the world are ation suggested that different neural structures would violated (Dickinson, 1981; Mackintosh, 1983).”
Time-Derivative Models of Pavlovian Reinforcement (1990, methodology): “The amount of learning is thereby proportional to both the level of CS processing and the level of US processing, as long as these occur at the same time (cf., Dickinson 1980, p. 124; Wagner 1978).”
Knowledge-Based Causal Attribution: The Abnormal Conditions Focus Model (1986, background): “At a different level, the principle of information gain appears to be implicated in animal learning about covariational relations (Dickinson, 1980; Mackintosh, 1983).”