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Goal-directed decision making : computations and neural circuits
Morris R., Bornstein A., Shenhav A., Academic Press, Inc., San Diego, CA, 2018. 484 pp.  Type: Book (978-0-128120-98-9)
Date Reviewed: Aug 21 2019

In the past few years, many disciplines have merged together for an improved understanding of goal-directed decisions. Such disciplines include neuroscience, psychology, cognitive science, and computer science (CS). This edited book on goal-directed decision making includes contributions from 38 leading experts in those fields. It comprises 19 chapters.

The first chapter discusses how the doctrines of goal-directed learning have enabled research into decision making. The focus is on actions and habits. The next chapter illustrates how concepts such as instrumental divergence can enhance our ideas about goal-directed learning. The third chapter looks at how evidence can be merged over a period of time to facilitate decision making; the focus is on reward-based goal-directed decision making. The next chapter discusses “goal-directed decision making using the economic theory of case-based reasoning.” Chapter 5 looks at how hierarchical learning can help stimulus-response models present environmental structures in a pliable manner; the focus is on learning structures through reinforcement.

Chapter 6 is interesting in that it discusses how small mammals such as rats move through structured environments: by assuming several likely routes. The next chapter is on “arbitration between decision-making systems.” It presents computational precepts that could help us realize how both competition and cooperation between multiple reinforcement learning systems can happen.

Chapter 8 discusses the role of different parts of the prefrontal cortex in goal-directed learning, and chapter 9 looks at the role of subcortical regions in decision making. Chapter 10 focuses on the nucleus accumbens shell and how it learns, and chapter 11 focuses on “the reward prediction error account of phasic dopamine signals in the ventral ... area.” Chapter 12 talks about the orbitofrontal cortex’s role in representing partly discernible state representation for reinforcement learning, a requisite for goal-directed learning. The next chapter “presents the application of decision-making science [for] understanding child development.”

Chapter 14 concentrates on social behavior. The conclusion is that emotions aid in optimizing goal-directed social behavior. The next chapter studies compulsive disorders, and the succeeding two chapters discuss drug addiction and schizophrenia, respectively. Chapter 18 focuses on the subsisting stresses “between psychological and computational classifications that [discern] habitual and goal-directed behavior.” Alternative taxonomies for habitual and goal-directed behavior are considered after highlighting problems with the current taxonomy. The last chapter of the book contains thought-provoking discussions on what is actually meant by reward and reinforcement. It sketches an exciting account of how they may be differentiated.

The book presents current research on goal-directed decision making. Though technically heavy, it will be very useful for scholars, researchers, and students working in disciplines such as neuroscience, psychology, cognitive science, and CS. The chapters end with numerous references to the literature. The book contains many illustrations, including some in color. The index is handy.

Reviewer:  S. V. Nagaraj Review #: CR146666 (1911-0382)
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